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source = "registry+https://github.com/rust-lang/crates.io-index" checksum = "34080505efa8e45a4b816c349525ebe327ceaa8559756f0356cba97ef3bf7432" +[[package]] +name = "matrixmultiply" +version = "0.3.10" +source = "registry+https://github.com/rust-lang/crates.io-index" +checksum = "a06de3016e9fae57a36fd14dba131fccf49f74b40b7fbdb472f96e361ec71a08" +dependencies = [ + "autocfg", + "rawpointer", +] + [[package]] name = "memchr" version = "2.7.6" @@ -690,6 +1137,21 @@ dependencies = [ "autocfg", ] +[[package]] +name = "ndarray" +version = "0.17.2" +source = "registry+https://github.com/rust-lang/crates.io-index" +checksum = "520080814a7a6b4a6e9070823bb24b4531daac8c4627e08ba5de8c5ef2f2752d" +dependencies = [ + "matrixmultiply", + "num-complex", + "num-integer", + "num-traits", + "portable-atomic", + "portable-atomic-util", + "rawpointer", +] + [[package]] name = "num" version = "0.4.3" @@ -720,6 +1182,7 @@ version = "0.4.6" source = "registry+https://github.com/rust-lang/crates.io-index" checksum = "73f88a1307638156682bada9d7604135552957b7818057dcef22705b4d509495" dependencies = [ + "bytemuck", "num-traits", ] @@ -761,6 +1224,33 @@ source = "registry+https://github.com/rust-lang/crates.io-index" checksum = "071dfc062690e90b734c0b2273ce72ad0ffa95f0c74596bc250dcfd960262841" dependencies = [ "autocfg", + "libm", +] + +[[package]] +name = "num_cpus" +version = "1.17.0" +source = "registry+https://github.com/rust-lang/crates.io-index" +checksum = "91df4bbde75afed763b708b7eee1e8e7651e02d97f6d5dd763e89367e957b23b" +dependencies = [ + "hermit-abi", + "libc", +] + +[[package]] +name = "numpy" +version = "0.27.1" +source = "registry+https://github.com/rust-lang/crates.io-index" +checksum = "7aac2e6a6e4468ffa092ad43c39b81c79196c2bb773b8db4085f695efe3bba17" +dependencies = [ + "libc", + "ndarray", + "num-complex", + "num-integer", + "num-traits", + "pyo3", + "pyo3-build-config", + "rustc-hash", ] [[package]] @@ -784,6 +1274,34 @@ version = "11.1.5" source = 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"57c0d7b74b563b49d38dae00a0c37d4d6de9b432382b2892f0574ddcae73fd0a" +[[package]] +name = "pest" +version = "2.8.6" +source = "registry+https://github.com/rust-lang/crates.io-index" +checksum = "e0848c601009d37dfa3430c4666e147e49cdcf1b92ecd3e63657d8a5f19da662" +dependencies = [ + "memchr", + "ucd-trie", +] + [[package]] name = "plotters" version = "0.3.7" @@ -837,6 +1365,15 @@ version = "1.11.1" source = "registry+https://github.com/rust-lang/crates.io-index" checksum = "f84267b20a16ea918e43c6a88433c2d54fa145c92a811b5b047ccbe153674483" +[[package]] +name = "portable-atomic-util" +version = "0.2.7" +source = "registry+https://github.com/rust-lang/crates.io-index" +checksum = "c2a106d1259c23fac8e543272398ae0e3c0b8d33c88ed73d0cc71b0f1d902618" +dependencies = [ + "portable-atomic", +] + [[package]] name = "ppv-lite86" version = "0.2.21" @@ -857,17 +1394,37 @@ dependencies = [ "ppvm-tableau", ] +[[package]] +name = "ppvm-lindblad" +version = "0.1.0" +dependencies = [ + "approx", + "fxhash", + "ndarray", + "num", + "ppvm-runtime", + "quspin-expm", + "quspin-types", + "rayon", + "sprs", +] + [[package]] name = "ppvm-python-native" version = "0.1.0" dependencies = [ "bnum", + "dashmap", + "fxhash", "num", + "numpy", "paste", + "ppvm-lindblad", "ppvm-runtime", "ppvm-stim", "ppvm-tableau", "pyo3", + "rayon", ] [[package]] @@ -950,7 +1507,27 @@ source = "registry+https://github.com/rust-lang/crates.io-index" checksum = "479ca8adacdd7ce8f1fb39ce9ecccbfe93a3f1344b3d0d97f20bc0196208f62b" dependencies = [ "proc-macro2", - "syn", + "syn 2.0.106", +] + +[[package]] +name = "primitive-types" +version = "0.12.2" +source = "registry+https://github.com/rust-lang/crates.io-index" +checksum = "0b34d9fd68ae0b74a41b21c03c2f62847aa0ffea044eee893b4c140b37e244e2" +dependencies = [ + "fixed-hash", + "impl-codec", + "uint", +] + +[[package]] +name = "proc-macro-crate" +version = "3.5.0" +source = "registry+https://github.com/rust-lang/crates.io-index" +checksum = "e67ba7e9b2b56446f1d419b1d807906278ffa1a658a8a5d8a39dcb1f5a78614f" +dependencies = [ + "toml_edit", ] [[package]] @@ -973,7 +1550,7 @@ dependencies = [ "bitflags", "num-traits", "rand 0.9.4", - "rand_chacha", + "rand_chacha 0.9.0", "rand_xorshift", "regex-syntax 0.8.6", "rusty-fork", @@ -1037,7 +1614,7 @@ dependencies = [ "proc-macro2", "pyo3-macros-backend", "quote", - "syn", + "syn 2.0.106", ] [[package]] @@ -1050,7 +1627,7 @@ dependencies = [ "proc-macro2", "pyo3-build-config", "quote", - "syn", + "syn 2.0.106", ] [[package]] @@ -1068,6 +1645,28 @@ dependencies = [ "proc-macro2", ] +[[package]] +name = "quspin-expm" +version = "0.1.0" +source = "git+https://github.com/QuSpin/QuSpin-rust?rev=6f4a1581e14d5258c9aeb684b4aec964bdff4e34#6f4a1581e14d5258c9aeb684b4aec964bdff4e34" +dependencies = [ + "ndarray", + "num-complex", + "quspin-types", + "rayon", +] + +[[package]] +name = "quspin-types" +version = "0.1.0" +source = "git+https://github.com/QuSpin/QuSpin-rust?rev=6f4a1581e14d5258c9aeb684b4aec964bdff4e34#6f4a1581e14d5258c9aeb684b4aec964bdff4e34" +dependencies = [ + "ndarray", + "num-complex", + "ruint", + "thiserror", +] + [[package]] name = "r-efi" version = "5.3.0" @@ -1080,13 +1679,24 @@ version = "0.7.0" source = "registry+https://github.com/rust-lang/crates.io-index" checksum = "dc33ff2d4973d518d823d61aa239014831e521c75da58e3df4840d3f47749d09" +[[package]] +name = "rand" +version = "0.8.6" +source = "registry+https://github.com/rust-lang/crates.io-index" +checksum = "5ca0ecfa931c29007047d1bc58e623ab12e5590e8c7cc53200d5202b69266d8a" +dependencies = [ + "libc", + "rand_chacha 0.3.1", + "rand_core 0.6.4", +] + [[package]] name = "rand" version = "0.9.4" source = "registry+https://github.com/rust-lang/crates.io-index" checksum = "44c5af06bb1b7d3216d91932aed5265164bf384dc89cd6ba05cf59a35f5f76ea" dependencies = [ - "rand_chacha", + "rand_chacha 0.9.0", "rand_core 0.9.5", ] @@ -1101,6 +1711,16 @@ dependencies = [ "rand_core 0.10.0", ] +[[package]] +name = "rand_chacha" +version = "0.3.1" +source = "registry+https://github.com/rust-lang/crates.io-index" +checksum = "e6c10a63a0fa32252be49d21e7709d4d4baf8d231c2dbce1eaa8141b9b127d88" +dependencies = [ + "ppv-lite86", + "rand_core 0.6.4", +] + [[package]] name = "rand_chacha" version = "0.9.0" @@ -1111,6 +1731,15 @@ dependencies = [ "rand_core 0.9.5", ] +[[package]] +name = "rand_core" +version = "0.6.4" +source = "registry+https://github.com/rust-lang/crates.io-index" +checksum = "ec0be4795e2f6a28069bec0b5ff3e2ac9bafc99e6a9a7dc3547996c5c816922c" +dependencies = [ + "getrandom 0.2.17", +] + [[package]] name = "rand_core" version = "0.9.5" @@ -1135,6 +1764,12 @@ dependencies = [ "rand_core 0.9.5", ] +[[package]] +name = "rawpointer" +version = "0.2.1" +source = "registry+https://github.com/rust-lang/crates.io-index" +checksum = "60a357793950651c4ed0f3f52338f53b2f809f32d83a07f72909fa13e4c6c1e3" + [[package]] name = "rayon" version = "1.11.0" @@ -1210,6 +1845,80 @@ version = "0.8.6" source = "registry+https://github.com/rust-lang/crates.io-index" checksum = "caf4aa5b0f434c91fe5c7f1ecb6a5ece2130b02ad2a590589dda5146df959001" +[[package]] +name = "rlp" +version = "0.5.2" +source = "registry+https://github.com/rust-lang/crates.io-index" +checksum = "bb919243f34364b6bd2fc10ef797edbfa75f33c252e7998527479c6d6b47e1ec" +dependencies = [ + "bytes", + "rustc-hex", +] + +[[package]] +name = "ruint" +version = "1.18.0" +source = "registry+https://github.com/rust-lang/crates.io-index" +checksum = "0298da754d1395046b0afdc2f20ee76d29a8ae310cd30ffa84ed42acba9cb12a" +dependencies = [ + "alloy-rlp", + "ark-ff 0.3.0", + "ark-ff 0.4.2", + "ark-ff 0.5.0", + "bytes", + "fastrlp 0.3.1", + "fastrlp 0.4.0", + "num-bigint", + "num-integer", + "num-traits", + "parity-scale-codec", + "primitive-types", + "proptest", + "rand 0.8.6", + "rand 0.9.4", + "rlp", + "ruint-macro", + "serde_core", + "valuable", + "zeroize", +] + +[[package]] +name = "ruint-macro" +version = "1.2.1" +source = "registry+https://github.com/rust-lang/crates.io-index" +checksum = "48fd7bd8a6377e15ad9d42a8ec25371b94ddc67abe7c8b9127bec79bebaaae18" + +[[package]] +name = "rustc-hash" +version = "2.1.2" +source = "registry+https://github.com/rust-lang/crates.io-index" +checksum = "94300abf3f1ae2e2b8ffb7b58043de3d399c73fa6f4b73826402a5c457614dbe" + +[[package]] +name = "rustc-hex" +version = "2.1.0" +source = "registry+https://github.com/rust-lang/crates.io-index" +checksum = "3e75f6a532d0fd9f7f13144f392b6ad56a32696bfcd9c78f797f16bbb6f072d6" + +[[package]] +name = "rustc_version" +version = "0.3.3" +source = "registry+https://github.com/rust-lang/crates.io-index" +checksum = "f0dfe2087c51c460008730de8b57e6a320782fbfb312e1f4d520e6c6fae155ee" +dependencies = [ + "semver 0.11.0", +] + +[[package]] +name = "rustc_version" +version = "0.4.1" +source = "registry+https://github.com/rust-lang/crates.io-index" +checksum = "cfcb3a22ef46e85b45de6ee7e79d063319ebb6594faafcf1c225ea92ab6e9b92" +dependencies = [ + "semver 1.0.27", +] + [[package]] name = "rustix" version = "1.1.2" @@ -1262,12 +1971,30 @@ version = "1.2.0" source = "registry+https://github.com/rust-lang/crates.io-index" checksum = "94143f37725109f92c262ed2cf5e59bce7498c01bcc1502d7b9afe439a4e9f49" +[[package]] +name = "semver" +version = "0.11.0" +source = "registry+https://github.com/rust-lang/crates.io-index" +checksum = "f301af10236f6df4160f7c3f04eec6dbc70ace82d23326abad5edee88801c6b6" +dependencies = [ + "semver-parser", +] + [[package]] name = "semver" version = "1.0.27" source = "registry+https://github.com/rust-lang/crates.io-index" checksum = "d767eb0aabc880b29956c35734170f26ed551a859dbd361d140cdbeca61ab1e2" +[[package]] +name = "semver-parser" +version = "0.10.3" +source = "registry+https://github.com/rust-lang/crates.io-index" +checksum = "9900206b54a3527fdc7b8a938bffd94a568bac4f4aa8113b209df75a09c0dec2" +dependencies = [ + "pest", +] + [[package]] name = "serde" version = "1.0.228" @@ -1295,7 +2022,7 @@ checksum = "d540f220d3187173da220f885ab66608367b6574e925011a9353e4badda91d79" dependencies = [ "proc-macro2", "quote", - "syn", + "syn 2.0.106", ] [[package]] @@ -1329,6 +2056,20 @@ version = "1.15.1" source = "registry+https://github.com/rust-lang/crates.io-index" checksum = "67b1b7a3b5fe4f1376887184045fcf45c69e92af734b7aaddc05fb777b6fbd03" +[[package]] +name = "sprs" +version = "0.11.4" +source = "registry+https://github.com/rust-lang/crates.io-index" +checksum = "6dca58a33be2188d4edc71534f8bafa826e787cc28ca1c47f31be3423f0d6e55" +dependencies = [ + "ndarray", + "num-complex", + "num-traits", + "num_cpus", + "rayon", + "smallvec", +] + [[package]] name = "stacker" version = "0.1.24" @@ -1342,6 +2083,12 @@ dependencies = [ "windows-sys 0.61.2", ] +[[package]] +name = "static_assertions" +version = "1.1.0" +source = "registry+https://github.com/rust-lang/crates.io-index" +checksum = "a2eb9349b6444b326872e140eb1cf5e7c522154d69e7a0ffb0fb81c06b37543f" + [[package]] name = "stim-parser" version = "0.1.0" @@ -1357,6 +2104,17 @@ version = "0.11.1" source = "registry+https://github.com/rust-lang/crates.io-index" checksum = "7da8b5736845d9f2fcb837ea5d9e2628564b3b043a70948a3f0b778838c5fb4f" +[[package]] +name = "syn" +version = "1.0.109" +source = "registry+https://github.com/rust-lang/crates.io-index" +checksum = "72b64191b275b66ffe2469e8af2c1cfe3bafa67b529ead792a6d0160888b4237" +dependencies = [ + "proc-macro2", + "quote", + "unicode-ident", +] + [[package]] name = "syn" version = "2.0.106" @@ -1410,7 +2168,7 @@ checksum = "ebc4ee7f67670e9b64d05fa4253e753e016c6c95ff35b89b7941d6b856dec1d5" dependencies = [ "proc-macro2", "quote", - "syn", + "syn 2.0.106", ] [[package]] @@ -1423,6 +2181,60 @@ dependencies = [ "serde_json", ] +[[package]] +name = "toml_datetime" +version = "1.1.1+spec-1.1.0" +source = "registry+https://github.com/rust-lang/crates.io-index" +checksum = "3165f65f62e28e0115a00b2ebdd37eb6f3b641855f9d636d3cd4103767159ad7" +dependencies = [ + "serde_core", +] + +[[package]] +name = "toml_edit" +version = "0.25.6+spec-1.1.0" +source = "registry+https://github.com/rust-lang/crates.io-index" +checksum = "0db3bae107c9522f86d361697dee1d7386a2ddcf659d5aea5159819a21a3c4a7" +dependencies = [ + "indexmap", + "toml_datetime", + "toml_parser", + "winnow", +] + +[[package]] +name = "toml_parser" +version = "1.1.2+spec-1.1.0" +source = "registry+https://github.com/rust-lang/crates.io-index" +checksum = "a2abe9b86193656635d2411dc43050282ca48aa31c2451210f4202550afb7526" +dependencies = [ + "winnow", +] + +[[package]] +name = "typenum" +version = "1.20.1" +source = "registry+https://github.com/rust-lang/crates.io-index" +checksum = "b6f5e870be6c3b371b77fe0ee0bafb859fa4964b4404c27de1d380043c4dda20" + +[[package]] +name = "ucd-trie" +version = "0.1.7" +source = "registry+https://github.com/rust-lang/crates.io-index" +checksum = "2896d95c02a80c6d6a5d6e953d479f5ddf2dfdb6a244441010e373ac0fb88971" + +[[package]] +name = "uint" +version = "0.9.5" +source = "registry+https://github.com/rust-lang/crates.io-index" +checksum = "76f64bba2c53b04fcab63c01a7d7427eadc821e3bc48c34dc9ba29c501164b52" +dependencies = [ + "byteorder", + "crunchy", + "hex", + "static_assertions", +] + [[package]] name = "unarray" version = "0.1.4" @@ -1459,6 +2271,12 @@ version = "0.0.4" source = "registry+https://github.com/rust-lang/crates.io-index" checksum = "6d49784317cd0d1ee7ec5c716dd598ec5b4483ea832a2dced265471cc0f690ae" +[[package]] +name = "valuable" +version = "0.1.1" +source = "registry+https://github.com/rust-lang/crates.io-index" +checksum = "ba73ea9cf16a25df0c8caa16c51acb937d5712a8429db78a3ee29d5dcacd3a65" + [[package]] name = "version_check" version = "0.9.5" @@ -1490,6 +2308,12 @@ dependencies = [ "winapi-util", ] +[[package]] +name = "wasi" +version = "0.11.1+wasi-snapshot-preview1" +source = "registry+https://github.com/rust-lang/crates.io-index" +checksum = "ccf3ec651a847eb01de73ccad15eb7d99f80485de043efb2f370cd654f4ea44b" + [[package]] name = "wasi" version = "0.14.7+wasi-0.2.4" @@ -1540,7 +2364,7 @@ dependencies = [ "log", "proc-macro2", "quote", - "syn", + "syn 2.0.106", "wasm-bindgen-shared", ] @@ -1562,7 +2386,7 @@ checksum = "9f07d2f20d4da7b26400c9f4a0511e6e0345b040694e8a75bd41d578fa4421d7" dependencies = [ "proc-macro2", "quote", - "syn", + "syn 2.0.106", "wasm-bindgen-backend", "wasm-bindgen-shared", ] @@ -1607,7 +2431,7 @@ dependencies = [ "bitflags", "hashbrown 0.15.5", "indexmap", - "semver", + "semver 1.0.27", ] [[package]] @@ -1717,6 +2541,15 @@ version = "0.52.6" source = "registry+https://github.com/rust-lang/crates.io-index" checksum = "589f6da84c646204747d1270a2a5661ea66ed1cced2631d546fdfb155959f9ec" +[[package]] +name = "winnow" +version = "1.0.3" +source = "registry+https://github.com/rust-lang/crates.io-index" +checksum = "0592e1c9d151f854e6fd382574c3a0855250e1d9b2f99d9281c6e6391af352f1" +dependencies = [ + "memchr", +] + [[package]] name = "wit-bindgen" version = "0.46.0" @@ -1753,7 +2586,7 @@ dependencies = [ "heck", "indexmap", "prettyplease", - "syn", + "syn 2.0.106", "wasm-metadata", "wit-bindgen-core", "wit-component", @@ -1769,7 +2602,7 @@ dependencies = [ "prettyplease", "proc-macro2", "quote", - "syn", + "syn 2.0.106", "wit-bindgen-core", "wit-bindgen-rust", ] @@ -1803,7 +2636,7 @@ dependencies = [ "id-arena", "indexmap", "log", - "semver", + "semver 1.0.27", "serde", "serde_derive", "serde_json", @@ -1837,5 +2670,25 @@ checksum = "88d2b8d9c68ad2b9e4340d7832716a4d21a22a1154777ad56ea55c51a9cf3831" dependencies = [ "proc-macro2", "quote", - "syn", + "syn 2.0.106", +] + +[[package]] +name = "zeroize" +version = "1.9.0" +source = "registry+https://github.com/rust-lang/crates.io-index" +checksum = "e13c156562582aa81c60cb29407084cdb54c4164760106ab78e6c5b0858cf64e" +dependencies = [ + "zeroize_derive", +] + +[[package]] +name = "zeroize_derive" +version = "1.5.0" +source = "registry+https://github.com/rust-lang/crates.io-index" +checksum = "3c50655cbb0fe3fc43170059e702f1ce5e19b84cec58dc87b037a09935c2f328" +dependencies = [ + "proc-macro2", + "quote", + "syn 2.0.106", ] diff --git a/Cargo.toml b/Cargo.toml index e319ce0e7..dc4a85acb 100644 --- a/Cargo.toml +++ b/Cargo.toml @@ -14,6 +14,7 @@ ppvm-sym = { version = "0.1.0", path = "crates/ppvm-sym" } members = [ "crates/ppvm-runtime", "crates/ppvm-sym", + "crates/ppvm-lindblad", "crates/ppvm-python-native", "crates/ppvm-tableau", "crates/ppvm-stim", "crates/stim-parser", diff --git a/crates/ppvm-lindblad/Cargo.toml b/crates/ppvm-lindblad/Cargo.toml new file mode 100644 index 000000000..89e57bb5f --- /dev/null +++ b/crates/ppvm-lindblad/Cargo.toml @@ -0,0 +1,24 @@ +[package] +name = "ppvm-lindblad" +version = "0.1.0" +edition = "2024" +description = "Direct Heisenberg-picture Lindbladian evolution on an adaptive Pauli-string basis." + +[dependencies] +fxhash = "0.2.1" +ndarray = "0.17" +num = "0.4.3" +ppvm-runtime = { version = "0.1.0", path = "../ppvm-runtime" } +rayon = "1.11" +sprs = { version = "0.11", default-features = false, features = ["multi_thread"] } +# Matrix-exponential action (Al-Mohy & Higham). NOTE: QuSpin-rust currently has +# no LICENSE file; this pin is a placeholder pending a permissive license being +# added upstream (the authors are co-authors of the ppvm paper). +quspin-expm = { git = "https://github.com/QuSpin/QuSpin-rust", rev = "6f4a1581e14d5258c9aeb684b4aec964bdff4e34" } +# `QuSpinError` (the error type returned by the `LinearOperator` trait methods +# we implement in `mf_expm.rs`) is not re-exported from `quspin-expm`'s root, +# so we depend on `quspin-types` directly. Same git rev as `quspin-expm`. +quspin-types = { git = "https://github.com/QuSpin/QuSpin-rust", rev = "6f4a1581e14d5258c9aeb684b4aec964bdff4e34" } + +[dev-dependencies] +approx = "0.5.1" diff --git a/crates/ppvm-lindblad/src/config.rs b/crates/ppvm-lindblad/src/config.rs new file mode 100644 index 000000000..0395fd195 --- /dev/null +++ b/crates/ppvm-lindblad/src/config.rs @@ -0,0 +1,27 @@ +// SPDX-FileCopyrightText: 2026 The PPVM Authors +// SPDX-License-Identifier: Apache-2.0 + +//! Configuration objects for the predictor-corrector stepper. + +/// Policy options for a single predictor-corrector step +/// ([`crate::LindbladSpec::pc_step`] / [`crate::LindbladSpec::pc_step_timed`]). +/// +/// These are the per-run *tuning knobs*, kept separate from the per-call data +/// (`basis`, `coeffs`, `dt`, `protected`) so the step functions don't grow an +/// unwieldy positional-argument list. +#[derive(Debug, Clone, Copy)] +pub struct PcStepConfig { + /// Leakage-rate threshold for basis growth: a leakage Pauli is appended to + /// the basis only if its `|coeff|` exceeds `tau_add`. Larger values keep the + /// basis smaller (faster, less accurate); it also drives the streaming + /// Cauchy-Schwarz prune in [`crate::LindbladSpec::leakage_with_prune`]. + pub tau_add: f64, + /// Magnitude prune applied after the corrector: basis entries whose + /// `|coeff|` is below `drop_tol` are discarded (protected words are always + /// kept). `drop_tol <= 0.0` disables pruning. + pub drop_tol: f64, + /// When `Some(n)`, run the entire step inside a freshly built rayon thread + /// pool of `n` threads (useful for benchmarking parallel scaling). When + /// `None`, the global rayon pool is used. + pub num_threads: Option, +} diff --git a/crates/ppvm-lindblad/src/error.rs b/crates/ppvm-lindblad/src/error.rs new file mode 100644 index 000000000..e0c1eb5f0 --- /dev/null +++ b/crates/ppvm-lindblad/src/error.rs @@ -0,0 +1,76 @@ +// SPDX-FileCopyrightText: 2026 The PPVM Authors +// SPDX-License-Identifier: Apache-2.0 + +//! Error type for [`crate::LindbladSpec`] construction and stepping. + +use crate::MAX_QUBITS; +use std::fmt; + +/// Errors raised when constructing a [`crate::LindbladSpec`]. +#[derive(Debug, Clone)] +pub enum Error { + TooManyQubits { + got: usize, + }, + LengthMismatch { + what: &'static str, + a: usize, + b: usize, + }, + InvalidPauliCode { + code: u8, + }, + InvalidPauliChar { + c: char, + }, + WrongLength { + expected: usize, + got: usize, + }, + NegativeRate { + index: usize, + rate: f64, + }, + EmptyLincomb { + index: usize, + }, + Internal(String), +} + +impl fmt::Display for Error { + fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result { + match self { + Error::TooManyQubits { got } => { + write!( + f, + "LindbladSpec supports n_qubits ≤ {MAX_QUBITS}; got {got}" + ) + } + Error::LengthMismatch { what, a, b } => { + write!(f, "{what}: expected matching lengths, got {a} and {b}") + } + Error::InvalidPauliCode { code } => write!( + f, + "Pauli code must be 0 (I), 1 (X), 2 (Z), or 3 (Y); got {code}" + ), + Error::InvalidPauliChar { c } => { + write!(f, "invalid Pauli character '{c}'; expected I, X, Y, or Z") + } + Error::WrongLength { expected, got } => { + write!(f, "Pauli string has length {got} but n_qubits = {expected}") + } + Error::NegativeRate { index, rate } => { + write!(f, "jump rate must be non-negative; got γ_{index} = {rate}") + } + Error::EmptyLincomb { index } => { + write!( + f, + "jump {index}: lincomb must contain at least one Pauli term" + ) + } + Error::Internal(msg) => write!(f, "internal error: {msg}"), + } + } +} + +impl std::error::Error for Error {} diff --git a/crates/ppvm-lindblad/src/expm.rs b/crates/ppvm-lindblad/src/expm.rs new file mode 100644 index 000000000..d5c7b5e9c --- /dev/null +++ b/crates/ppvm-lindblad/src/expm.rs @@ -0,0 +1,99 @@ +// SPDX-FileCopyrightText: 2026 The PPVM Authors +// SPDX-License-Identifier: Apache-2.0 + +//! Support pieces for the `quspin-expm`-backed `exp(t·A)·b` engine. +//! +//! The hand-rolled scaling-and-squaring engine that once lived here has been +//! retired in favour of the external `quspin-expm` crate (driven from +//! [`crate::mf_expm`]). What remains is the shared scaffolding the new path +//! still relies on: the `(m, s)` selection table [`THETA`] / [`select_ms`] +//! from Al-Mohy & Higham (2011), used to pick the Taylor partition handed to +//! `quspin-expm`'s `from_parts`. + +/// `θ_m` table from Al-Mohy & Higham (2011), Table A.3, for double +/// precision (unit roundoff `u = 2^{-53}`). +/// +/// `θ_m` bounds `‖A‖₁` such that the degree-`m` Taylor polynomial +/// approximates `exp(A)` to within `u`. We pick `(m, s)` with +/// `s ≥ ⌈‖tA‖₁ / θ_m⌉` and minimise `m·s` (total SpMV count). +pub(crate) const THETA: &[(u32, f64)] = &[ + (1, 2.29e-16), + (2, 2.58e-8), + (3, 1.39e-5), + (4, 3.40e-4), + (5, 2.40e-3), + (6, 9.07e-3), + (7, 2.38e-2), + (8, 5.00e-2), + (9, 8.96e-2), + (10, 1.44e-1), + (11, 2.14e-1), + (12, 3.00e-1), + (13, 4.00e-1), + (14, 5.14e-1), + (15, 6.41e-1), + (16, 7.81e-1), + (17, 9.31e-1), + (18, 1.09), + (19, 1.26), + (20, 1.44), + (21, 1.62), + (22, 1.82), + (23, 2.01), + (24, 2.22), + (25, 2.43), + (26, 2.64), + (27, 2.86), + (28, 3.08), + (29, 3.31), + (30, 3.54), +]; + +/// Pick `(m, s)` minimising `s·m` subject to `s ≥ ⌈t_norm / θ_m⌉, s ≥ 1`. +/// Restricted to `m ≤ 30`; for larger norms `s` simply grows linearly. +/// When `max_m` is set, only entries with `m ≤ max_m` are considered. +pub(crate) fn select_ms(t_norm: f64, max_m: Option) -> (u32, u32) { + if t_norm <= 0.0 { + return (1, 1); + } + let mut best_m = 1u32; + let mut best_s = 1u32; + let mut best_cost = u64::MAX; + for &(m, theta) in THETA { + if let Some(cap) = max_m { + if m > cap { + continue; + } + } + let s_f = (t_norm / theta).ceil(); + let s = if s_f >= 1.0 { s_f as u32 } else { 1 }; + let cost = (m as u64) * (s as u64); + if cost < best_cost { + best_cost = cost; + best_m = m; + best_s = s; + } + } + (best_m, best_s) +} + +#[cfg(test)] +mod tests { + use super::*; + + #[test] + fn ms_selection_sane() { + // tiny norm → small m, s = 1 + let (m, s) = select_ms(1e-9, None); + assert!(m <= 5, "expected small m for tiny norm, got m={m}"); + assert_eq!(s, 1); + + // moderate norm → m·s should be ~10-50 + let (m, s) = select_ms(1.0, None); + assert!((m * s) <= 50, "moderate norm cost too high: m={m} s={s}"); + + // large norm → s grows + let (_m, s) = select_ms(100.0, None); + assert!(s >= 20, "large norm should require many steps, got s={s}"); + } +} diff --git a/crates/ppvm-lindblad/src/lib.rs b/crates/ppvm-lindblad/src/lib.rs new file mode 100644 index 000000000..7a0871815 --- /dev/null +++ b/crates/ppvm-lindblad/src/lib.rs @@ -0,0 +1,1372 @@ +// SPDX-FileCopyrightText: 2026 The PPVM Authors +// SPDX-License-Identifier: Apache-2.0 + +//! Direct Heisenberg-picture Lindbladian evolution on an adaptive +//! Pauli-string basis. +//! +//! For a Hermitian Pauli Hamiltonian `H = Σ c_i P_i` and jump operators +//! `L_k = Σ_a λ_{k,a} P_{k,a}` (each a Hermitian-Pauli linear combination +//! with possibly complex coefficients) with rates `γ_k ≥ 0`, the adjoint +//! Lindbladian acts on a single Pauli string `p` as +//! +//! ```text +//! L*(p) = i [H, p] + Σ_k γ_k ( L_k† p L_k − 1/2 {L_k† L_k, p} ). +//! ``` +//! +//! Two jump shapes are supported with separate code paths: +//! +//! - **Hermitian Pauli** (`L = P`, `λ ∈ ℝ`): the dissipator collapses to a +//! diagonal `-2γ` on Pauli strings that anti-commute with `P`. Same fast +//! path used by every dephasing-style model. +//! +//! - **General** (complex `λ_a`, e.g. `σ± = (X ± iY)/2`): the dissipator +//! becomes a double sum `Σ_{a,b} λ_a* λ_b P_a p P_b` plus a Pauli- +//! linear-combination anti-commutator with `L†L`, which is precomputed +//! once at construction. Intermediate coefficients are complex; the +//! result is real because `L*` preserves Hermiticity, so we cast back +//! to `f64` at the boundary (with a debug-only check that `|Im|` is at +//! FP noise). +//! +//! Pauli strings are stored as [`ppvm_runtime::word::PauliWord`] backed by +//! `[u64; 2]` (≤128 qubits) with cached hashes for fast HashMap lookup. The +//! hot-path commutator/product loops bypass the higher-level word API and +//! operate directly on raw `u64` chunks for speed. + +use fxhash::{FxBuildHasher, FxHashMap, FxHashSet}; +use num::Complex; +use ppvm_runtime::traits::PauliWordTrait; +use ppvm_runtime::word::PauliWord; +use rayon::prelude::*; +use std::time::Instant; + +pub mod config; +mod error; +pub mod expm; +mod mf_expm; + +pub use config::PcStepConfig; +pub use error::Error; + +/// Number of 64-bit words used to back a [`Word`]'s X/Z bit-pair storage. +/// +/// A Pauli string is stored as a fixed-width `[u64; W_U64]` pair of bitsets +/// (one `u64` array for the X bits, one for the Z bits). Each `u64` packs 64 +/// qubits, so `W_U64` u64 words cover `64 · W_U64` qubits. The width is a +/// compile-time constant rather than a runtime-sized `Vec` on purpose: an +/// inline fixed array keeps the whole word in a single cache line, makes the +/// hot-path commutator/product loops branch-free over a known iteration count, +/// and gives O(1) clone/hash without heap indirection. Widen this constant +/// (and rebuild) to support more qubits at a proportional memory/per-op cost. +const W_U64: usize = 2; + +/// Maximum number of qubits supported by [`Word`] (`= 64 · W_U64`). +/// +/// The fixed-width `[u64; W_U64]` bit-pair backing (see [`W_U64`]) packs 64 +/// qubits per `u64`, so the current `W_U64 = 2` covers up to 128 qubits. +/// There is nothing fundamental about the value — it is purely the storage +/// width chosen for cache-friendly O(1) Pauli ops. Constructing a +/// [`LindbladSpec`] (or any [`Word`]) for more than `MAX_QUBITS` qubits is +/// rejected with [`Error::TooManyQubits`] rather than silently truncated. +pub const MAX_QUBITS: usize = 64 * W_U64; + +/// The Pauli-word storage type used throughout this crate. +/// +/// A fixed-width `[u64; W_U64]` bit-pair array (X bits + Z bits) packing up to +/// [`MAX_QUBITS`] qubits with no heap allocation, so commutator/product/hash +/// operations are cache-friendly and O(1). The `FxBuildHasher` matches the +/// hash used by the `FxHashMap` keys we wrap with; `REHASH=true` means +/// `set()` keeps the cached hash in sync. +pub type Word = PauliWord<[u64; W_U64], FxBuildHasher, true>; + +/// Per-phase timing breakdown (microseconds) returned by +/// [`LindbladSpec::pc_step_timed`]. +#[derive(Default, Clone, Copy, Debug)] +pub struct PcStepTimings { + pub leakage1_us: u64, + pub expand1_us: u64, + pub gencsr1_us: u64, + pub expm1_us: u64, + pub leakage2_us: u64, + pub expand2_us: u64, + pub gencsr2_us: u64, + pub expm2_us: u64, +} + +impl PcStepTimings { + pub fn total_us(&self) -> u64 { + self.leakage1_us + + self.expand1_us + + self.gencsr1_us + + self.expm1_us + + self.leakage2_us + + self.expand2_us + + self.gencsr2_us + + self.expm2_us + } +} + +// ────────────────── codec helpers ────────────────── + +/// Build a [`Word`] from a length-`n_qubits` slice of Pauli codes +/// (`0=I, 1=X, 2=Z, 3=Y`). Sets all bits and rehashes once. +pub fn word_from_codes(codes: &[u8]) -> Result { + let n_qubits = codes.len(); + if n_qubits > MAX_QUBITS { + return Err(Error::TooManyQubits { got: n_qubits }); + } + let mut w = Word::new(n_qubits); + for (q, &b) in codes.iter().enumerate() { + if b > 3 { + return Err(Error::InvalidPauliCode { code: b }); + } + if b & 1 != 0 { + w.xbits.set(q, true); + } + if b & 2 != 0 { + w.zbits.set(q, true); + } + } + w.rehash(); + Ok(w) +} + +/// Inverse of [`word_from_codes`]: write `n_qubits` Pauli codes into `out`. +pub fn codes_from_word(w: &Word, out: &mut [u8]) { + debug_assert_eq!(out.len(), w.n_qubits()); + for (q, slot) in out.iter_mut().enumerate() { + let xb = w.xbits[q] as u8; + let zb = w.zbits[q] as u8; + *slot = xb | (zb << 1); + } +} + +/// Parse a `"IXYZ..."` string into a [`Word`] together with the list of +/// qubits where the Pauli is non-identity (the term's support). +pub fn parse_pauli_string(s: &str, n_qubits: usize) -> Result<(Word, Vec), Error> { + if n_qubits > MAX_QUBITS { + return Err(Error::TooManyQubits { got: n_qubits }); + } + let chars: Vec = s.chars().filter(|c| *c != '_').collect(); + if chars.len() != n_qubits { + return Err(Error::WrongLength { + expected: n_qubits, + got: chars.len(), + }); + } + let mut w = Word::new(n_qubits); + let mut support = Vec::new(); + for (q, c) in chars.into_iter().enumerate() { + match c { + 'I' => {} + 'X' => { + w.xbits.set(q, true); + support.push(q as u32); + } + 'Z' => { + w.zbits.set(q, true); + support.push(q as u32); + } + 'Y' => { + w.xbits.set(q, true); + w.zbits.set(q, true); + support.push(q as u32); + } + other => return Err(Error::InvalidPauliChar { c: other }), + } + } + w.rehash(); + Ok((w, support)) +} + +/// Compute the support (non-identity qubits) of `w`. +fn word_support(w: &Word, out: &mut Vec) { + out.clear(); + for q in 0..w.n_qubits() { + if w.xbits[q] || w.zbits[q] { + out.push(q as u32); + } + } +} + +// ────────────────── Pauli algebra ────────────────── +// +// Phase encoding: `Pauli product P·Q = ω · R` where `ω = i^phase` and +// `phase ∈ {0,1,2,3}` ↔ `ω ∈ {1, i, -1, -i}`. The per-byte XOR/AND +// formulas are the same ones used by `PhasedPauliWord::mul_assign` in +// `ppvm-runtime`. + +#[inline(always)] +fn phase_factor(phase: u8) -> Complex { + match phase & 3 { + 0 => Complex::new(1.0, 0.0), + 1 => Complex::new(0.0, 1.0), + 2 => Complex::new(-1.0, 0.0), + _ => Complex::new(0.0, -1.0), + } +} + +/// `true` if Pauli words `a` and `b` anti-commute. +/// +/// Two Pauli strings anti-commute iff +/// `popcount(a.x & b.z) + popcount(a.z & b.x)` is odd. +#[inline(always)] +fn anti_commutes(a: &Word, b: &Word) -> bool { + let mut bits: u32 = 0; + for i in 0..W_U64 { + bits += (a.xbits.data[i] & b.zbits.data[i]).count_ones(); + bits += (a.zbits.data[i] & b.xbits.data[i]).count_ones(); + } + bits & 1 == 1 +} + +/// Fused product `h · p`: returns `(out, eps)` where `out = h ⊕ p` and +/// +/// - `eps = 0` if `h` and `p` commute (caller should skip — `[h,p] = 0`), +/// - `eps = -2.0` if `h·p` has phase `+i` (so `i·[h,p] = -2·out`), +/// - `eps = +2.0` if `h·p` has phase `-i` (so `i·[h,p] = +2·out`). +#[inline(always)] +fn comm_product(h: &Word, p: &Word) -> (Word, f64) { + let mut out = Word::new(h.n_qubits()); + let mut sign_count: u32 = 0; + let mut imag_count: u32 = 0; + for i in 0..W_U64 { + let a = h.xbits.data[i]; + let b = h.zbits.data[i]; + let c = p.xbits.data[i]; + let d = p.zbits.data[i]; + let sign = (a & b & c & !d) | (a & !b & !c & d) | (!a & b & c & d); + let imag = (a & !b & d) | (a & !c & d) | (!a & b & c) | (b & c & !d); + sign_count += sign.count_ones(); + imag_count += imag.count_ones(); + out.xbits.data[i] = a ^ c; + out.zbits.data[i] = b ^ d; + } + out.rehash(); + let phase = (2 * sign_count + imag_count) & 3; + let eps = match phase { + 1 => -2.0, + 3 => 2.0, + _ => 0.0, + }; + (out, eps) +} + +/// Full Pauli product `p · q`: returns `(out, phase)` where the product +/// is `ω · out` with `ω = i^phase`. +#[inline(always)] +fn pauli_mul(p: &Word, q: &Word) -> (Word, u8) { + let mut out = Word::new(p.n_qubits()); + let mut sign_count: u32 = 0; + let mut imag_count: u32 = 0; + for i in 0..W_U64 { + let a = p.xbits.data[i]; + let b = p.zbits.data[i]; + let c = q.xbits.data[i]; + let d = q.zbits.data[i]; + let sign = (a & b & c & !d) | (a & !b & !c & d) | (!a & b & c & d); + let imag = (a & !b & d) | (a & !c & d) | (!a & b & c) | (b & c & !d); + sign_count += sign.count_ones(); + imag_count += imag.count_ones(); + out.xbits.data[i] = a ^ c; + out.zbits.data[i] = b ^ d; + } + out.rehash(); + (out, ((2 * sign_count + imag_count) & 3) as u8) +} + +// ────────────────── Spec types ────────────────── + +/// Parsed Hamiltonian term. +#[derive(Clone)] +struct HTerm { + word: Word, + coeff: f64, +} + +/// One Pauli term in a complex linear combination (a single summand of +/// `L = Σ_a λ_a P_a` or of the precomputed `L†L`). +#[derive(Clone)] +struct PauliTerm { + word: Word, + coeff: Complex, +} + +/// One jump operator `L_k` with rate `γ_k`. The `HermitianPauli` variant +/// is a fast path; `General` handles arbitrary complex Pauli sums. +#[derive(Clone)] +enum JumpKind { + HermitianPauli { + word: Word, + rate: f64, + }, + General { + terms: Vec, // L = Σ_a λ_a P_a + dagger_dagger: Vec, // L†L = Σ_c μ_c P_c (μ_c ∈ ℝ) + rate: f64, + }, +} + +/// Expand `L†L = (Σ_a λ_a P_a)† (Σ_b λ_b P_b) = Σ_{a,b} λ_a* λ_b P_a P_b` +/// as a Pauli linear combination, dropping FP-noise zeros. Coefficients are +/// real because `L†L` is Hermitian; we keep them complex for arithmetic +/// uniformity. +fn precompute_ldagger_l(terms: &[PauliTerm]) -> Vec { + let zero = Complex::new(0.0, 0.0); + let mut acc: FxHashMap> = FxHashMap::default(); + for a in terms { + for b in terms { + let (word, phase) = pauli_mul(&a.word, &b.word); + let coeff = a.coeff.conj() * b.coeff * phase_factor(phase); + *acc.entry(word).or_insert(zero) += coeff; + } + } + acc.into_iter() + .filter(|(_, c)| c.norm() > 1e-14) + .map(|(word, coeff)| PauliTerm { word, coeff }) + .collect() +} + +/// Precompiled Lindbladian. Constructed once from string-form Hamiltonian +/// terms + jump operators; reused across many calls to [`Self::action`], +/// [`Self::leakage`], [`Self::generator`]. `L*(p)` is recomputed fresh on +/// every call — empirical benchmarks showed that the previous global +/// `action_cache` hurt wall time for sparse-local Hamiltonians (hash-map +/// lookup ≳ recompute) and consumed several KB per cached Pauli word, which +/// blocked us from reaching the basis sizes needed for L=41 sweeps. +pub struct LindbladSpec { + n_qubits: usize, + h_terms: Vec, + j_kinds: Vec, + /// `h_support[q]` = indices of Hamiltonian terms acting on qubit `q`. + h_support: Vec>, + /// `j_support[q]` = indices of jumps whose support contains qubit `q`. + j_support: Vec>, +} + +/// User-facing description of one jump operator: a complex Pauli linear +/// combination together with its rate. +#[derive(Clone, Debug)] +pub struct JumpInput { + /// `(pauli_string, λ)` pairs forming `L_k = Σ_a λ_a P_a`. + pub lincomb: Vec<(String, Complex)>, + /// Non-negative GKSL rate `γ_k`. + pub rate: f64, +} + +impl LindbladSpec { + /// Construct a Lindbladian spec from Hamiltonian terms and jump operators. + /// + /// `h_terms` are `(pauli_string, coefficient)` pairs forming the Hermitian + /// Hamiltonian. Each jump operator is a complex Pauli linear combination; + /// a length-1 jump with imaginary part `0` is routed to the Hermitian-Pauli + /// fast path (with rate scaled by the squared real coefficient). + pub fn new( + n_qubits: usize, + h_terms: &[(String, f64)], + jumps: &[JumpInput], + ) -> Result { + if n_qubits > MAX_QUBITS { + return Err(Error::TooManyQubits { got: n_qubits }); + } + + let mut h_parsed: Vec = Vec::with_capacity(h_terms.len()); + let mut h_support_idx: Vec> = vec![Vec::new(); n_qubits]; + for (i, (s, c)) in h_terms.iter().enumerate() { + let (word, support) = parse_pauli_string(s, n_qubits)?; + for q in support { + h_support_idx[q as usize].push(i as u32); + } + h_parsed.push(HTerm { word, coeff: *c }); + } + + let mut j_kinds: Vec = Vec::with_capacity(jumps.len()); + let mut j_support_idx: Vec> = vec![Vec::new(); n_qubits]; + for (k, jump) in jumps.iter().enumerate() { + if jump.rate < 0.0 { + return Err(Error::NegativeRate { + index: k, + rate: jump.rate, + }); + } + if jump.lincomb.is_empty() { + return Err(Error::EmptyLincomb { index: k }); + } + + // Fast path: single-term, purely real → Hermitian Pauli. + if jump.lincomb.len() == 1 && jump.lincomb[0].1.im == 0.0 { + let (s, c) = &jump.lincomb[0]; + let (word, support) = parse_pauli_string(s, n_qubits)?; + for q in support { + j_support_idx[q as usize].push(k as u32); + } + j_kinds.push(JumpKind::HermitianPauli { + word, + rate: jump.rate * c.re * c.re, + }); + continue; + } + + // General path: parse all terms, precompute L†L, record union support. + let mut terms: Vec = Vec::with_capacity(jump.lincomb.len()); + let mut union_support: std::collections::BTreeSet = + std::collections::BTreeSet::new(); + for (s, c) in &jump.lincomb { + let (word, support) = parse_pauli_string(s, n_qubits)?; + for q in &support { + union_support.insert(*q); + } + terms.push(PauliTerm { word, coeff: *c }); + } + for q in union_support { + j_support_idx[q as usize].push(k as u32); + } + let dagger_dagger = precompute_ldagger_l(&terms); + j_kinds.push(JumpKind::General { + terms, + dagger_dagger, + rate: jump.rate, + }); + } + + Ok(Self { + n_qubits, + h_terms: h_parsed, + j_kinds, + h_support: h_support_idx, + j_support: j_support_idx, + }) + } + + pub fn n_qubits(&self) -> usize { + self.n_qubits + } + + pub fn num_h_terms(&self) -> usize { + self.h_terms.len() + } + + pub fn num_jump_terms(&self) -> usize { + self.j_kinds.len() + } + + /// Conservative upper bound on `max_{p, w} |⟨w| L*(p) |p⟩|`, the + /// largest coefficient any single input Pauli can produce in any + /// single output Pauli through one action of `L*`. Used by + /// [`Self::leakage`] to safely prune candidates whose accumulated + /// partial sum + remaining-contribution budget cannot reach the + /// `tau_add` keep threshold (Cauchy-Schwarz style streaming bound). + /// + /// The bound is `2 · max |h_i|` (commutator factor) plus a per-jump + /// term. For the common case of Hermitian-Pauli H and Hermitian-Pauli + /// jumps this collapses to `2 · max(|h_i|, γ_k)`. + pub fn max_action_coef(&self) -> f64 { + let mut m = 0.0_f64; + for h in &self.h_terms { + // `i [H_i, p]` has coefficient `±2 i · h_i · eps`; magnitude ≤ 2|h_i|. + m = m.max(2.0 * h.coeff.abs()); + } + for jk in &self.j_kinds { + match jk { + JumpKind::HermitianPauli { rate, .. } => { + // sandwich + anticommutator → max |2γ| on anticommuting p + m = m.max(2.0 * rate.abs()); + } + JumpKind::General { + terms, + rate, + dagger_dagger, + } => { + let lam_sum: f64 = terms.iter().map(|t| t.coeff.norm()).sum(); + let dd_sum: f64 = dagger_dagger.iter().map(|t| t.coeff.norm()).sum(); + // Sandwich `γ Σ_{a,b} λ_a* λ_b P_a p P_b`: per-output ≤ γ · (Σ|λ|)² + // L†L anticommutator: per-output ≤ γ · Σ|c_dd| + m = m.max(rate * (lam_sum * lam_sum + dd_sum)); + } + } + } + m + } + + /// Apply `L*` to a single Pauli string `p`. Returns the output Pauli + /// strings and their real coefficients (zero entries omitted). + pub fn action(&self, p: &Word) -> Vec<(Word, f64)> { + let mut out: FxHashMap = FxHashMap::default(); + let mut s1 = Vec::new(); + let mut s2 = Vec::new(); + self.accumulate_action(p, 1.0, &mut out, &mut s1, &mut s2); + out.into_iter().filter(|(_, c)| *c != 0.0).collect() + } + + /// Off-basis component of `L*( Σ_j coeffs[j] · basis[j] )`. Output + /// strings that lie in `basis` or in `protected` are dropped. + pub fn leakage( + &self, + basis: &[Word], + coeffs: &[f64], + protected: &[Word], + ) -> Result, Error> { + self.leakage_with_prune(basis, coeffs, protected, None) + } + + /// Like [`Self::leakage`], but when `tau_add` is `Some(τ)` runs the + /// streaming Cauchy-Schwarz prune: after each chunk the remaining + /// possible contribution to any not-yet-final candidate is bounded + /// by `max_action_coef × Σ_{i not yet processed} |c_i|`. Entries + /// whose `|partial_sum| + remaining_bound < τ` are dropped. The + /// final keep filter `|sum| ≥ τ` is still applied by the caller. + /// + /// Processing the largest-`|c|` basis indices first shrinks the + /// remaining budget fastest, so the prune kicks in earlier. + /// Memory savings depend on how skewed the `coeffs` distribution + /// is — power-law distributions win the most. Worst case (uniform + /// `|c|`): the bound stays above `τ` until late in the basis, + /// pruning kicks in only near the end, savings approach zero. + pub fn leakage_with_prune( + &self, + basis: &[Word], + coeffs: &[f64], + protected: &[Word], + tau_add: Option, + ) -> Result, Error> { + if basis.len() != coeffs.len() { + return Err(Error::LengthMismatch { + what: "basis and coeffs", + a: basis.len(), + b: coeffs.len(), + }); + } + // Hash-only membership tables: storing 8-byte `u64` keys instead + // of 48-byte Words shrinks the in-basis structure ~6×, keeping it + // in L3 (and often L2) at basis sizes where the full-Word version + // would spill to DRAM. + let in_basis: FxHashMap = basis.iter().map(|w| (word_hash(w), ())).collect(); + let protected_set: FxHashMap = + protected.iter().map(|w| (word_hash(w), ())).collect(); + + // Streaming-prune setup. If `tau_add` is None, fall through to the + // un-pruned path (process basis in original order, no prune). + let (order, mut remaining_budget): (Vec, f64) = if tau_add.is_some() { + let mut idx: Vec = (0..basis.len()).collect(); + // Descending sort by |c|: process largest-magnitude contributors + // first so the Cauchy-Schwarz remaining bound shrinks fast. + idx.sort_by(|&a, &b| { + coeffs[b] + .abs() + .partial_cmp(&coeffs[a].abs()) + .unwrap_or(std::cmp::Ordering::Equal) + }); + let max_coef = self.max_action_coef(); + let total: f64 = coeffs.iter().map(|c| c.abs()).sum(); + (idx, max_coef * total) + } else { + ((0..basis.len()).collect(), f64::INFINITY) + }; + let max_coef = self.max_action_coef(); + let tau = tau_add.unwrap_or(0.0); + + const CHUNK_SIZE: usize = 4096; + let mut merged: FxHashMap = FxHashMap::default(); + for chunk_indices in order.chunks(CHUNK_SIZE) { + // Rayon fold/reduce: each worker folds its share of the chunk into + // a thread-local `FxHashMap`, then maps are pairwise reduced. This + // avoids materialising the full `Vec>` of every + // term before merging — intermediates stay one-map-per-active-task + // instead of one-Vec-per-basis-element. The fold accumulator also + // carries the per-thread scratch buffers (`s1`, `s2`, `lm`) used by + // `compute_action_terms`, reused across all items folded by that + // task. Sum coefficients per key; identical final map. + let chunk_merged: FxHashMap = chunk_indices + .par_iter() + .fold( + || { + ( + FxHashMap::::default(), + Vec::::with_capacity(self.n_qubits), + Vec::::with_capacity(128), + FxHashMap::>::with_capacity_and_hasher( + 128, + FxBuildHasher::default(), + ), + ) + }, + |(mut acc, mut s1, mut s2, mut lm), &i| { + let p = &basis[i]; + let c = coeffs[i]; + let terms = self.compute_action_terms(p, &mut s1, &mut s2, &mut lm); + for (w, v) in terms.iter() { + let h = word_hash(w); + if !in_basis.contains_key(&h) && !protected_set.contains_key(&h) { + *acc.entry(w.clone()).or_insert(0.0) += c * *v; + } + } + (acc, s1, s2, lm) + }, + ) + .map(|(acc, ..)| acc) + .reduce(FxHashMap::default, |a, b| { + // Merge the smaller map into the larger to minimise work. + let (mut big, small) = if a.len() >= b.len() { (a, b) } else { (b, a) }; + for (k, val) in small { + *big.entry(k).or_insert(0.0) += val; + } + big + }); + for (k, val) in chunk_merged { + *merged.entry(k).or_insert(0.0) += val; + } + + if tau_add.is_some() { + // Decrement the remaining-contribution budget by what this + // chunk has now processed. Once `remaining_budget < τ`, + // every entry has `|true_sum| ≤ |partial_sum| + remaining`, + // so we can drop entries with `|partial_sum| < τ − remaining`. + let chunk_abs_sum: f64 = chunk_indices.iter().map(|&i| coeffs[i].abs()).sum(); + remaining_budget = (remaining_budget - max_coef * chunk_abs_sum).max(0.0); + if remaining_budget < tau { + let threshold = tau - remaining_budget; + merged.retain(|_, &mut v| v.abs() >= threshold); + } + } + } + Ok(merged.into_iter().filter(|(_, c)| *c != 0.0).collect()) + } + + /// Sparse generator matrix in COO form: returns `(row, col, val)` + /// triplets. Row = output Pauli's position in `basis`; col = input + /// Pauli's position. Output Paulis not in `basis` are silently dropped. + /// + /// Precondition: `basis` must not contain duplicate Pauli words + /// (asserted in debug builds). + pub fn generator(&self, basis: &[Word]) -> Vec<(usize, usize, f64)> { + let index = build_basis_index(basis); + + // The cached `L*(p)` is already a deduplicated `Vec<(Word, f64)>`, + // so we can iterate it directly without going through a per-task + // `FxHashMap` accumulator (which was the previous hot spot). + let local: Vec> = basis + .par_iter() + .enumerate() + .map_init( + || { + ( + Vec::::with_capacity(self.n_qubits), + Vec::::with_capacity(128), + FxHashMap::>::with_capacity_and_hasher( + 128, + FxBuildHasher::default(), + ), + ) + }, + |(s1, s2, lm), (col, p)| { + let terms = self.compute_action_terms(p, s1, s2, lm); + let mut out = Vec::with_capacity(terms.len()); + for (w, v) in terms.iter() { + if let Some(&row) = index.get(w) { + out.push((row as usize, col, *v)); + } + } + out + }, + ) + .collect(); + + // Pre-allocate the flat output to avoid sequential push reallocation. + let total: usize = local.iter().map(|v| v.len()).sum(); + let mut flat = Vec::with_capacity(total); + for v in local { + flat.extend(v); + } + flat + } + + /// Matrix-free SpMV: `y ← M · x` where `M` is the in-basis-restricted + /// generator (the in-basis-restricted generator `M`, never materialised). + /// For each basis column `j` with `x[j] != 0`, + /// compute `L*(basis[j])`, look up each output Pauli in `basis_index`, + /// and accumulate `v · x[j]` into `y` at the matching row. + /// + /// `basis_index` must be the `Word → row` map for `basis` (use + /// [`build_basis_index`]). It is the caller's responsibility to build + /// it once and reuse across all SpMVs within an expm call. + /// + /// Threading uses `rayon::current_num_threads()` per-task dense + /// accumulators, reduced into `y` at the end. Peak transient memory is + /// roughly `T × n × 8 B` where `T` = thread count, `n` = basis size. + pub fn spmv_matrix_free( + &self, + basis: &[Word], + basis_index: &FxHashMap, + x: &[f64], + y: &mut [f64], + ) { + debug_assert_eq!(basis.len(), x.len()); + debug_assert_eq!(basis.len(), y.len()); + let n = basis.len(); + if n == 0 { + return; + } + let num_threads = rayon::current_num_threads().max(1); + let chunk_size = n.div_ceil(num_threads); + + let partial_ys: Vec> = basis + .par_chunks(chunk_size) + .enumerate() + .map(|(chunk_idx, chunk)| { + let c_offset = chunk_idx * chunk_size; + let mut y_local = vec![0.0; n]; + let mut s1 = Vec::::with_capacity(self.n_qubits); + let mut s2 = Vec::::with_capacity(128); + let mut lm = FxHashMap::>::with_capacity_and_hasher( + 128, + FxBuildHasher::default(), + ); + for (c_local, p) in chunk.iter().enumerate() { + let c = c_offset + c_local; + let xc = x[c]; + if xc == 0.0 { + continue; + } + let terms = self.compute_action_terms(p, &mut s1, &mut s2, &mut lm); + for (w, v) in terms.iter() { + if let Some(&row) = basis_index.get(w) { + y_local[row as usize] += *v * xc; + } + } + } + y_local + }) + .collect(); + + // Sequential reduce. T × n adds; at T=8, n=10⁶ this is ~8M adds + // (~10 ms), trivial vs the action evaluations above. + y.fill(0.0); + for partial in &partial_ys { + for (yi, &pi) in y.iter_mut().zip(partial.iter()) { + *yi += pi; + } + } + } + + /// Apply `L*` to the Pauli sum `Σ_j coeffs[j] · basis[j]` and return + /// the result as a (Word → real coefficient) map. The basis of the + /// returned operator is determined by the action — entries appear + /// for every Pauli that `L*` reaches with nonzero coefficient. + /// + /// Same parallel structure and chunked merge as [`Self::leakage`], + /// without the in-basis / protected filter: this returns the full + /// `L*(O)`, not just its off-basis component. + pub fn compute_action_sum( + &self, + basis: &[Word], + coeffs: &[f64], + ) -> Result, Error> { + if basis.len() != coeffs.len() { + return Err(Error::LengthMismatch { + what: "basis and coeffs", + a: basis.len(), + b: coeffs.len(), + }); + } + const CHUNK_SIZE: usize = 4096; + let mut merged: FxHashMap = FxHashMap::default(); + for chunk_start in (0..basis.len()).step_by(CHUNK_SIZE) { + let chunk_end = (chunk_start + CHUNK_SIZE).min(basis.len()); + let chunk_basis = &basis[chunk_start..chunk_end]; + let chunk_coeffs = &coeffs[chunk_start..chunk_end]; + let local: Vec> = chunk_basis + .par_iter() + .zip(chunk_coeffs.par_iter()) + .map_init( + || { + ( + Vec::::with_capacity(self.n_qubits), + Vec::::with_capacity(128), + FxHashMap::>::with_capacity_and_hasher( + 128, + FxBuildHasher::default(), + ), + ) + }, + |(s1, s2, lm), (p, &c)| { + let terms = self.compute_action_terms(p, s1, s2, lm); + terms.into_iter().map(|(w, v)| (w, c * v)).collect() + }, + ) + .collect(); + for v in local { + for (k, val) in v { + *merged.entry(k).or_insert(0.0) += val; + } + } + } + Ok(merged) + } + + /// One classical RK4 step on `O ← O + dt · L*(O)`, expanding the basis + /// naturally as the action explores new strings. After the step, drops + /// any string whose absolute coefficient is below `drop_tol` (protected + /// words always kept). No predictor-corrector enrichment, no Krylov + /// machinery, no CSR build — just four matrix-free action evaluations + /// followed by a magnitude prune. + /// + /// Per-step local truncation error is `O(dt^5)` from the integrator. + /// **Stability** requires `dt ≤ 2.78 / ‖L*‖` (RK4 absolute-stability + /// boundary). For an n-qubit lattice Hamiltonian with bounded local + /// terms this typically means `dt ≲ O(1) / n`; the dissipator further + /// shrinks the bound at large `γ`. Violating the bound is **not + /// signalled** — the trajectory will norm-conserve but individual Pauli + /// coefficients diverge to oscillating ±large values that cancel; the + /// observable looks fine, the basis still grows, but local quantities + /// like MSD blow up. Always verify against a small in-band + /// truncation case (e.g. against ED, or against [`Self::pc_step`] + /// which is unconditionally stable) before trusting tight-`drop_tol` + /// results at large `dt`. + /// + /// For stiff problems where the stability bound is restrictive, prefer + /// [`Self::pc_step`], which integrates `exp(dt·L*)` via Krylov scaling- + /// and-squaring and is unconditionally stable in `dt`. + /// + /// `num_threads`, when set, runs the entire step inside a freshly built + /// rayon thread pool of that size. + pub fn rk4_step( + &self, + basis: &mut Vec, + coeffs: &mut Vec, + dt: f64, + drop_tol: f64, + protected: &[Word], + num_threads: Option, + ) -> Result<(), Error> { + if let Some(n) = num_threads { + let pool = rayon::ThreadPoolBuilder::new() + .num_threads(n) + .build() + .map_err(|e| Error::Internal(format!("rayon pool build: {e}")))?; + pool.install(|| self.rk4_step_inner(basis, coeffs, dt, drop_tol, protected)) + } else { + self.rk4_step_inner(basis, coeffs, dt, drop_tol, protected) + } + } + + fn rk4_step_inner( + &self, + basis: &mut Vec, + coeffs: &mut Vec, + dt: f64, + drop_tol: f64, + protected: &[Word], + ) -> Result<(), Error> { + // Helper: convert HashMap form back to (Vec, Vec) so we + // can hand it to compute_action_sum, which expects slices. + fn map_to_vecs(m: FxHashMap) -> (Vec, Vec) { + let n = m.len(); + let mut b = Vec::with_capacity(n); + let mut c = Vec::with_capacity(n); + for (w, v) in m { + b.push(w); + c.push(v); + } + (b, c) + } + + // Helper: returns a fresh map representing O + α · K, where O is + // (basis, coeffs) and K is a HashMap. We seed `out` with K (which + // is typically smaller / has different support than O) so the + // .entry() merges are fewer. + fn scale_add( + basis: &[Word], + coeffs: &[f64], + k: &FxHashMap, + alpha: f64, + ) -> FxHashMap { + let mut out: FxHashMap = + FxHashMap::with_capacity_and_hasher(basis.len() + k.len(), FxBuildHasher::default()); + for (p, &c) in basis.iter().zip(coeffs.iter()) { + out.insert(p.clone(), c); + } + for (w, v) in k { + *out.entry(w.clone()).or_insert(0.0) += alpha * v; + } + out + } + + // k1 = L*(O) + let k1 = self.compute_action_sum(basis, coeffs)?; + + // k2 = L*(O + dt/2 · k1) + let (b1, c1) = map_to_vecs(scale_add(basis, coeffs, &k1, dt / 2.0)); + let k2 = self.compute_action_sum(&b1, &c1)?; + drop(b1); + drop(c1); + + // k3 = L*(O + dt/2 · k2) + let (b2, c2) = map_to_vecs(scale_add(basis, coeffs, &k2, dt / 2.0)); + let k3 = self.compute_action_sum(&b2, &c2)?; + drop(b2); + drop(c2); + + // k4 = L*(O + dt · k3) + let (b3, c3) = map_to_vecs(scale_add(basis, coeffs, &k3, dt)); + let k4 = self.compute_action_sum(&b3, &c3)?; + drop(b3); + drop(c3); + + // O_new = O + dt/6 · (k1 + 2 k2 + 2 k3 + k4) + let dt6 = dt / 6.0; + let est_cap = basis.len() + k1.len() + k2.len() + k3.len() + k4.len(); + let mut out_map: FxHashMap = + FxHashMap::with_capacity_and_hasher(est_cap, FxBuildHasher::default()); + for (p, &c) in basis.iter().zip(coeffs.iter()) { + out_map.insert(p.clone(), c); + } + for (w, v) in &k1 { + *out_map.entry(w.clone()).or_insert(0.0) += dt6 * v; + } + for (w, v) in &k2 { + *out_map.entry(w.clone()).or_insert(0.0) += dt6 * 2.0 * v; + } + for (w, v) in &k3 { + *out_map.entry(w.clone()).or_insert(0.0) += dt6 * 2.0 * v; + } + for (w, v) in &k4 { + *out_map.entry(w.clone()).or_insert(0.0) += dt6 * v; + } + drop(k1); + drop(k2); + drop(k3); + drop(k4); + + // Prune below drop_tol; never drop a protected word, even if its + // coefficient happens to land below threshold. + let protected_hashes: FxHashSet = protected.iter().map(word_hash).collect(); + if drop_tol > 0.0 { + out_map.retain(|w, &mut v| { + v.abs() >= drop_tol || protected_hashes.contains(&word_hash(w)) + }); + } + + // Repack into the caller's Vec storage. + basis.clear(); + coeffs.clear(); + basis.reserve(out_map.len()); + coeffs.reserve(out_map.len()); + for (w, v) in out_map { + basis.push(w); + coeffs.push(v); + } + Ok(()) + } + + /// Predictor-corrector adaptive step. + /// + /// Mutates `basis` (may grow) and `coeffs` in place to reflect the + /// state at time `t + dt`. The step is: + /// + /// 1. **First-hop expansion**: compute leakage from the current state + /// and append any leakage Pauli with `|coeff| > tau_add` to the + /// basis (with starting coefficient 0). + /// 2. **Predictor**: apply `exp(dt · M)` to `coeffs` on the enlarged + /// basis, yielding a predicted state. + /// 3. **Second-hop expansion**: compute leakage from the *predicted* + /// state and append any further leakage strings — these are the + /// second-hop Paulis the predictor flowed into but did not yet have + /// in basis. + /// 4. **Corrector**: redo `exp(dt · M)` on the doubly-enlarged basis + /// starting from the saved pre-step coefficients. + /// + /// Lifts the per-step truncation error from `O(dt²)` (single-hop) to + /// `O(dt³)`. Strings in `protected` are never added to the basis as + /// leakage targets — typically the observable's support, which the + /// caller wants tracked exactly. + /// + /// `num_threads`, when set, runs the entire step inside a freshly built + /// rayon thread pool of that size — useful for benchmarking parallel + /// scaling. When `None`, the global rayon pool is used. + /// + /// The matrix-exponential action is computed matrix-free via the external + /// `quspin-expm` engine; the in-basis generator is never materialised. + /// + /// Policy options (`tau_add`, `drop_tol`, `num_threads`) are bundled in + /// [`PcStepConfig`]. + pub fn pc_step( + &self, + basis: &mut Vec, + coeffs: &mut Vec, + dt: f64, + protected: &[Word], + cfg: PcStepConfig, + ) -> Result<(), Error> { + if let Some(n) = cfg.num_threads { + let pool = rayon::ThreadPoolBuilder::new() + .num_threads(n) + .build() + .map_err(|e| Error::Internal(format!("rayon pool build: {e}")))?; + pool.install(|| self.pc_step_inner(basis, coeffs, dt, protected, cfg)) + } else { + self.pc_step_inner(basis, coeffs, dt, protected, cfg) + } + } + + /// Same as [`Self::pc_step`] but also returns a per-phase timing + /// breakdown (microseconds), for profiling parallel scaling and hot + /// spots. Output: `(leakage1, expand1, gencsr1, expm1, leakage2, + /// expand2, gencsr2, expm2)`. + /// + /// Policy options (`tau_add`, `drop_tol`, `num_threads`) are bundled in + /// [`PcStepConfig`]. + pub fn pc_step_timed( + &self, + basis: &mut Vec, + coeffs: &mut Vec, + dt: f64, + protected: &[Word], + cfg: PcStepConfig, + ) -> Result { + if let Some(n) = cfg.num_threads { + let pool = rayon::ThreadPoolBuilder::new() + .num_threads(n) + .build() + .map_err(|e| Error::Internal(format!("rayon pool build: {e}")))?; + pool.install(|| self.pc_step_inner_timed(basis, coeffs, dt, protected, cfg)) + } else { + self.pc_step_inner_timed(basis, coeffs, dt, protected, cfg) + } + } + + fn pc_step_inner_timed( + &self, + basis: &mut Vec, + coeffs: &mut Vec, + dt: f64, + protected: &[Word], + cfg: PcStepConfig, + ) -> Result { + let PcStepConfig { + tau_add, drop_tol, .. + } = cfg; + let mut t = PcStepTimings::default(); + + let t0 = Instant::now(); + let leak = self.leakage_with_prune(basis, coeffs, protected, Some(tau_add))?; + t.leakage1_us = t0.elapsed().as_micros() as u64; + + let t0 = Instant::now(); + for (w, v) in leak { + if v.abs() > tau_add { + basis.push(w); + coeffs.push(0.0); + } + } + t.expand1_us = t0.elapsed().as_micros() as u64; + + // Predictor: expm1. `coeffs` is read-only here, so we don't clone + // it — it serves as the pre-step input for the corrector below as + // well. + let t0 = Instant::now(); + let coeffs_predict = self.expm_step(basis, dt, coeffs); + t.expm1_us = t0.elapsed().as_micros() as u64; + + let t0 = Instant::now(); + let leak2 = self.leakage_with_prune(basis, &coeffs_predict, protected, Some(tau_add))?; + t.leakage2_us = t0.elapsed().as_micros() as u64; + drop(coeffs_predict); + + let t0 = Instant::now(); + for (w, v) in leak2 { + if v.abs() > tau_add { + basis.push(w); + coeffs.push(0.0); + } + } + t.expand2_us = t0.elapsed().as_micros() as u64; + + let t0 = Instant::now(); + *coeffs = self.expm_step(basis, dt, coeffs); + t.expm2_us = t0.elapsed().as_micros() as u64; + + prune_basis(basis, coeffs, drop_tol, protected); + + Ok(t) + } + + fn pc_step_inner( + &self, + basis: &mut Vec, + coeffs: &mut Vec, + dt: f64, + protected: &[Word], + cfg: PcStepConfig, + ) -> Result<(), Error> { + let PcStepConfig { + tau_add, drop_tol, .. + } = cfg; + // 1. First-hop expansion. After this, `coeffs` contains the pre-step + // coefficients followed by zeros for the newly-added leakage strings. + // We rely on `coeffs` itself as the pre-step buffer for the corrector + // — no `.clone()` is needed because `expm_step` only borrows it. + let leak = self.leakage_with_prune(basis, coeffs, protected, Some(tau_add))?; + for (w, v) in leak { + if v.abs() > tau_add { + basis.push(w); + coeffs.push(0.0); + } + } + // 2. Predictor: `expm_step` reads `coeffs` immutably and returns a + // new owned vector with the predicted state. + let coeffs_predict = self.expm_step(basis, dt, coeffs); + // 3. Second-hop expansion from the predicted state. After leakage2 + // we no longer need `coeffs_predict`. Extend `coeffs` with zeros for + // any newly-added second-hop strings so it remains a valid input + // (pre-step state) for the corrector. + let leak2 = self.leakage_with_prune(basis, &coeffs_predict, protected, Some(tau_add))?; + drop(coeffs_predict); + for (w, v) in leak2 { + if v.abs() > tau_add { + basis.push(w); + coeffs.push(0.0); + } + } + // 4. Corrector: redo from pre-step state on the doubly-enlarged basis. + *coeffs = self.expm_step(basis, dt, coeffs); + // 5. Prune basis entries below `drop_tol` (protected words never dropped). + prune_basis(basis, coeffs, drop_tol, protected); + Ok(()) + } + + /// Compute `exp(dt · M) · b` for the in-basis-restricted generator `M`, + /// matrix-free, via the external `quspin-expm` engine + /// ([`mf_expm::expm_apply_mf`]). The generator is never materialised and + /// the quspin engine selects its own truncation tolerance. + fn expm_step(&self, basis: &[Word], dt: f64, b: &[f64]) -> Vec { + mf_expm::expm_apply_mf(self, basis, dt, b) + } + + /// Compute the unscaled list of `(output, coefficient)` pairs that + /// `L*(p)` contributes (without the input coefficient). + fn compute_action_terms( + &self, + p: &Word, + scratch_support: &mut Vec, + scratch_cands: &mut Vec, + scratch_local: &mut FxHashMap>, + ) -> Vec<(Word, f64)> { + word_support(p, scratch_support); + let zero = Complex::new(0.0, 0.0); + scratch_local.clear(); + let local = scratch_local; + + // ── i [H, p] ───────────────────────────────────────────────── + candidate_terms(scratch_support, &self.h_support, scratch_cands); + for &i in scratch_cands.iter() { + let h = &self.h_terms[i as usize]; + let (r, eps) = comm_product(&h.word, p); + if eps != 0.0 { + *local.entry(r).or_insert(zero) += Complex::new(h.coeff * eps, 0.0); + } + } + + // ── dissipator ─────────────────────────────────────────────── + candidate_terms(scratch_support, &self.j_support, scratch_cands); + for &k in scratch_cands.iter() { + match &self.j_kinds[k as usize] { + JumpKind::HermitianPauli { word, rate } => { + if anti_commutes(word, p) { + *local.entry(p.clone()).or_insert(zero) += Complex::new(-2.0 * *rate, 0.0); + } + } + JumpKind::General { + terms, + dagger_dagger, + rate, + } => { + let rate_c = Complex::new(*rate, 0.0); + // Sandwich: γ Σ_{a,b} λ_a* λ_b P_a p P_b. + for a in terms { + let (r_ap, phi1) = pauli_mul(&a.word, p); + for b in terms { + let (s, phi2) = pauli_mul(&r_ap, &b.word); + let coeff = + a.coeff.conj() * b.coeff * phase_factor(phi1 + phi2) * rate_c; + *local.entry(s).or_insert(zero) += coeff; + } + } + // -1/2 γ {L†L, p}. For Hermitian Pauli P_c and Pauli p, + // {P_c, p} = 2·sign·R if they commute (P_c·p = sign·R), + // = 0 if they anti-commute. + for c_term in dagger_dagger { + let (r, phase) = pauli_mul(&c_term.word, p); + if phase & 1 == 0 { + let sign = if phase == 0 { 1.0 } else { -1.0 }; + let coeff = -c_term.coeff * rate_c * Complex::new(sign, 0.0); + *local.entry(r).or_insert(zero) += coeff; + } + } + } + } + } + + // L* preserves Hermiticity; imaginary parts must cancel to FP noise. + // `drain()` empties `scratch_local` so its allocation can be reused + // by the next call on the same thread (`Vec` keeps capacity). + local + .drain() + .filter_map(|(w, c)| { + debug_assert!( + c.im.abs() < 1e-9, + "L*(p) produced non-real coefficient {c}; bug in dissipator" + ); + if c.re == 0.0 { None } else { Some((w, c.re)) } + }) + .collect() + } + + /// Accumulate `scale · L*(p)` into `out`. + fn accumulate_action( + &self, + p: &Word, + scale: f64, + out: &mut FxHashMap, + scratch_support: &mut Vec, + scratch_cands: &mut Vec, + ) { + let mut scratch_local = FxHashMap::default(); + let terms = + self.compute_action_terms(p, scratch_support, scratch_cands, &mut scratch_local); + for (w, c) in terms.iter() { + *out.entry(w.clone()).or_insert(0.0) += scale * c; + } + } +} + +/// Compact 64-bit hash of a [`Word`], used as the key in cache-friendly +/// membership tables. +/// +/// `PauliWord::hash` writes its cached `u64` into the supplied `Hasher`; +/// running it through `FxHasher` once mixes the bits enough that the +/// resulting `u64` is well-distributed when stored as a key in a downstream +/// `FxHashMap` (whose outer hash function then needs only a cheap multiply +/// on a `u64` key). The whole call is ~2-5 ns and never touches `Word`'s +/// 32-byte payload, which is the entire point: an `FxHashMap` +/// over the basis has a working set ~6× smaller than `FxHashMap` +/// and stays in L2/L3 well past basis 10⁶. +#[inline(always)] +fn word_hash(w: &Word) -> u64 { + use std::hash::{Hash, Hasher}; + let mut h = fxhash::FxHasher::default(); + w.hash(&mut h); + h.finish() +} + +/// Compact `basis` / `coeffs` in place: drop entries whose absolute +/// coefficient is below `drop_tol` unless the word appears in `protected`. +/// No-op when `drop_tol ≤ 0`. +fn prune_basis(basis: &mut Vec, coeffs: &mut Vec, drop_tol: f64, protected: &[Word]) { + if drop_tol <= 0.0 { + return; + } + debug_assert_eq!(basis.len(), coeffs.len()); + let protected_set: FxHashSet<&Word> = protected.iter().collect(); + let mut write = 0; + for read in 0..basis.len() { + if coeffs[read].abs() >= drop_tol || protected_set.contains(&basis[read]) { + if write != read { + basis.swap(write, read); + coeffs.swap(write, read); + } + write += 1; + } + } + basis.truncate(write); + coeffs.truncate(write); +} + +/// Build a `word → row` map for a basis assumed to contain unique Pauli +/// words; debug-asserts the uniqueness invariant. +pub fn build_basis_index(basis: &[Word]) -> FxHashMap { + let mut index: FxHashMap = FxHashMap::default(); + for (i, w) in basis.iter().enumerate() { + let prev = index.insert(w.clone(), i as u32); + debug_assert!( + prev.is_none(), + "basis contains duplicate Pauli word at positions {} and {}", + prev.unwrap(), + i, + ); + } + index +} + +/// Union of `index[q]` for each `q ∈ p_support`, deduped. +#[inline] +fn candidate_terms(p_support: &[u32], index: &[Vec], scratch: &mut Vec) { + scratch.clear(); + for &q in p_support { + scratch.extend_from_slice(&index[q as usize]); + } + scratch.sort_unstable(); + scratch.dedup(); +} + +#[cfg(test)] +mod tests { + use super::*; + + fn jump_hpauli(s: &str, rate: f64) -> JumpInput { + JumpInput { + lincomb: vec![(s.to_string(), Complex::new(1.0, 0.0))], + rate, + } + } + + #[test] + fn z_dephasing_action_on_x() { + // L = Z on a single qubit; L*(X) = γ(ZXZ - X) = γ(-X - X) = -2γ X. + let spec = LindbladSpec::new( + 1, + &[("X".to_string(), 0.0)], // no Hamiltonian + &[jump_hpauli("Z", 0.5)], + ) + .unwrap(); + let (x, _) = parse_pauli_string("X", 1).unwrap(); + let terms = spec.action(&x); + assert_eq!(terms.len(), 1); + assert!((terms[0].1 - (-1.0)).abs() < 1e-12); // -2·0.5 = -1 + } + + #[test] + fn amplitude_damping_action_on_z() { + // Single-qubit σ⁻ jump: L*(Z) = -γ(I + Z). With γ=1 we expect + // I coefficient = -1, Z coefficient = -1. + let sigma_minus = JumpInput { + lincomb: vec![ + ("X".to_string(), Complex::new(0.5, 0.0)), + ("Y".to_string(), Complex::new(0.0, -0.5)), + ], + rate: 1.0, + }; + let spec = LindbladSpec::new(1, &[], &[sigma_minus]).unwrap(); + let (z, _) = parse_pauli_string("Z", 1).unwrap(); + let terms = spec.action(&z); + let (i_word, _) = parse_pauli_string("I", 1).unwrap(); + let mut i_coeff = 0.0; + let mut z_coeff = 0.0; + for (w, c) in &terms { + if w == &i_word { + i_coeff = *c; + } else if w == &z { + z_coeff = *c; + } + } + assert!((i_coeff - (-1.0)).abs() < 1e-10, "I coeff = {i_coeff}"); + assert!((z_coeff - (-1.0)).abs() < 1e-10, "Z coeff = {z_coeff}"); + } + + #[test] + fn word_codec_roundtrip() { + let codes = [0u8, 1, 2, 3, 1, 0, 3, 2]; + let w = word_from_codes(&codes).unwrap(); + let mut out = vec![0u8; codes.len()]; + codes_from_word(&w, &mut out); + assert_eq!(out.as_slice(), &codes); + } +} diff --git a/crates/ppvm-lindblad/src/mf_expm.rs b/crates/ppvm-lindblad/src/mf_expm.rs new file mode 100644 index 000000000..3b1522edc --- /dev/null +++ b/crates/ppvm-lindblad/src/mf_expm.rs @@ -0,0 +1,179 @@ +// SPDX-FileCopyrightText: 2026 The PPVM Authors +// SPDX-License-Identifier: Apache-2.0 + +//! Matrix-free `exp(dt · L*) · b` for the real (`f64`) path, driven by the +//! external `quspin-expm` crate. +//! +//! Instead of materialising the in-basis-restricted generator as a CSR, we +//! wrap the Lindbladian action in a [`MfOp`] implementing +//! [`quspin_types::LinearOperator`] and feed it to +//! [`quspin_expm::ExpmOp::from_parts`]. Using `from_parts` (rather than +//! `ExpmOp::new`) supplies the diagonal shift `μ`, the partition count `s`, +//! and the truncation order `m*` directly, which BYPASSES quspin's adaptive +//! parameter selection. As a consequence the 1-norm *estimator* and +//! `dot_transpose` are never invoked on the single-vector `apply` path — only +//! [`LinearOperator::dot`] runs, inside the Taylor/Horner loop. +//! +//! The shift `μ` and the exact column 1-norm of `A − μ·I` are computed in one +//! matrix-free pass over the basis (the same `(m, s)` selection table as the +//! retired hand-rolled engine in [`crate::expm`]). + +use crate::{LindbladSpec, Word, build_basis_index, expm}; +use fxhash::FxHashMap; +use quspin_types::{ExpmComputation, LinearOperator, QuSpinError}; +use rayon::prelude::*; + +/// Borrowed matrix-free view of the in-basis-restricted Lindbladian +/// generator `M` (the in-basis-restricted generator `M`, never +/// materialised). +/// +/// Borrowed, not owned: `quspin-types` provides a blanket +/// `LinearOperator` impl for `&T`, so `ExpmOp::from_parts(op, …)` accepts a +/// `MfOp` by value while it keeps borrowing `spec` / `basis`. +pub(crate) struct MfOp<'a> { + spec: &'a LindbladSpec, + basis: &'a [Word], + /// `Word → row` map for `basis`; built once and reused across every + /// `dot` in the Taylor loop. + index: FxHashMap, +} + +impl LinearOperator for MfOp<'_> { + fn dim(&self) -> usize { + self.basis.len() + } + + fn parallel_hint(&self) -> bool { + // `dot` parallelises internally over basis columns, and we drive the + // sequential single-vector `apply` path; never let quspin run its + // persistent-thread pool on top of our rayon parallelism. + false + } + + fn dot(&self, overwrite: bool, input: &[f64], output: &mut [f64]) -> Result<(), QuSpinError> { + if overwrite { + self.spec + .spmv_matrix_free(self.basis, &self.index, input, output); + } else { + let mut tmp = vec![0.0; output.len()]; + self.spec + .spmv_matrix_free(self.basis, &self.index, input, &mut tmp); + for (o, t) in output.iter_mut().zip(tmp.iter()) { + *o += *t; + } + } + Ok(()) + } + + fn trace(&self) -> f64 { + // Computed eagerly in `expm_apply_mf`; never reached on the + // `from_parts` + single-vector `apply` path. + unreachable!("MfOp::trace not used on the from_parts apply path") + } + + fn onenorm(&self, _shift: f64) -> f64 { + unreachable!("MfOp::onenorm not used on the from_parts apply path") + } + + fn dot_transpose( + &self, + _overwrite: bool, + _input: &[f64], + _output: &mut [f64], + ) -> Result<(), QuSpinError> { + Err(QuSpinError::RuntimeError( + "MfOp: dot_transpose not used on the from_parts apply path".into(), + )) + } + + fn dot_many( + &self, + _overwrite: bool, + _input: ndarray::ArrayView2<'_, f64>, + _output: ndarray::ArrayViewMut2<'_, f64>, + ) -> Result<(), QuSpinError> { + Err(QuSpinError::RuntimeError( + "MfOp: dot_many not used on the from_parts apply path".into(), + )) + } + + fn dot_chunk( + &self, + _overwrite: bool, + _input: &[f64], + _output_chunk: &mut [f64], + _row_start: usize, + ) -> Result<(), QuSpinError> { + Err(QuSpinError::RuntimeError( + "MfOp: dot_chunk not used on the from_parts apply path".into(), + )) + } + + fn dot_transpose_chunk( + &self, + _input: &[f64], + _output: &[::Atomic], + _rows: std::ops::Range, + ) -> Result<(), QuSpinError> { + Err(QuSpinError::RuntimeError( + "MfOp: dot_transpose_chunk not used on the from_parts apply path".into(), + )) + } +} + +/// Compute `exp(dt · M) · coeffs` for the in-basis-restricted generator +/// `M`, matrix-free, via `quspin-expm`. Returns a fresh `Vec` of length +/// `basis.len()`. +/// +/// One matrix-free pass extracts the diagonal shift `μ = tr(M)/n` and the +/// exact column 1-norm of `M − μ·I`; from `‖dt·(M−μI)‖₁` we pick the Taylor +/// partition `(m*, s)` and hand everything to +/// [`quspin_expm::ExpmOp::from_parts`]. +pub(crate) fn expm_apply_mf(spec: &LindbladSpec, basis: &[Word], dt: f64, coeffs: &[f64]) -> Vec { + let n = basis.len(); + if n == 0 { + return Vec::new(); + } + + // Single matrix-free pass: per column gather `raw = Σ|coeff|` and the + // diagonal entry `diag` (coeff of the term whose output Word == the input + // Word). From these we get `trace = Σ diag`, `μ = trace/n`, and the + // column 1-norm of `M − μ·I`: per column it is + // `raw − |diag| + |diag − μ|`. + let per_col: Vec<(f64, f64)> = basis + .par_iter() + .map(|p| { + let terms = spec.action(p); + let mut raw = 0.0; + let mut diag = 0.0; + for (w, c) in &terms { + raw += c.abs(); + if w == p { + diag = *c; + } + } + (raw, diag) + }) + .collect(); + + let trace: f64 = per_col.iter().map(|(_, d)| *d).sum(); + let mu = trace / n as f64; + let onenorm = per_col + .iter() + .map(|(raw, diag)| raw - diag.abs() + (diag - mu).abs()) + .fold(0.0_f64, f64::max); + + let (m_star, s) = expm::select_ms(dt.abs() * onenorm, None); + + let op = MfOp { + spec, + basis, + index: build_basis_index(basis), + }; + let expm = quspin_expm::ExpmOp::from_parts(op, dt, mu, s as usize, m_star as usize, 1e-12_f64); + + let mut v = coeffs.to_vec(); + expm.apply(ndarray::ArrayViewMut1::from(v.as_mut_slice())) + .expect("expm apply"); + v +} diff --git a/crates/ppvm-python-native/Cargo.toml b/crates/ppvm-python-native/Cargo.toml index ce22f3de3..01987b189 100644 --- a/crates/ppvm-python-native/Cargo.toml +++ b/crates/ppvm-python-native/Cargo.toml @@ -10,9 +10,14 @@ crate-type = ["cdylib"] [dependencies] bnum = "0.13.0" +dashmap = "6.1.0" +fxhash = "0.2.1" num = "0.4.3" +numpy = "0.27" paste = "1.0.15" +ppvm-lindblad = { version = "0.1.0", path = "../ppvm-lindblad" } ppvm-runtime = { version = "0.1.0", path = "../ppvm-runtime" } ppvm-stim = { version = "0.1.0", path = "../ppvm-stim" } ppvm-tableau = { version = "0.1.0", path = "../ppvm-tableau" } pyo3 = { version = "0.27.0", features = ["multiple-pymethods"] } +rayon = "1.11" diff --git a/crates/ppvm-python-native/src/lib.rs b/crates/ppvm-python-native/src/lib.rs index 8924db9dc..9fd268994 100644 --- a/crates/ppvm-python-native/src/lib.rs +++ b/crates/ppvm-python-native/src/lib.rs @@ -5,6 +5,7 @@ use pyo3::prelude::*; pub mod interface; pub mod interface_tableau; +pub mod lindblad; pub mod stim_program; #[pymodule] @@ -148,4 +149,8 @@ pub mod ppvm_python_native { // Stim #[pymodule_export] pub use crate::stim_program::PyStimProgram; + + // Lindbladian time evolution shim + #[pymodule_export] + pub use crate::lindblad::LindbladSpec; } diff --git a/crates/ppvm-python-native/src/lindblad.rs b/crates/ppvm-python-native/src/lindblad.rs new file mode 100644 index 000000000..67db15d4a --- /dev/null +++ b/crates/ppvm-python-native/src/lindblad.rs @@ -0,0 +1,403 @@ +// SPDX-FileCopyrightText: 2026 The PPVM Authors +// SPDX-License-Identifier: Apache-2.0 + +//! PyO3 wrapper around [`ppvm_lindblad::LindbladSpec`]. +//! +//! All algorithmic work — Pauli arithmetic, active-site iteration, cache +//! management, and the dissipator branches (Hermitian Pauli fast path vs +//! general complex Pauli sum) — lives in the [`ppvm_lindblad`] crate. This +//! module is responsible only for the Python boundary: decoding the +//! `(N, n_qubits)` numpy uint8 arrays into [`ppvm_lindblad::Word`] vectors, +//! and re-encoding outputs back into numpy. + +use std::collections::HashMap; + +use num::Complex; +use numpy::{IntoPyArray, PyArray1, PyArray2, PyArrayMethods, PyReadonlyArray1, PyReadonlyArray2}; +use ppvm_lindblad::{ + JumpInput, LindbladSpec as CoreSpec, PcStepConfig, Word, codes_from_word, word_from_codes, +}; +use pyo3::{exceptions::PyValueError, prelude::*}; + +type PyPauliMap<'py> = (Bound<'py, PyArray2>, Bound<'py, PyArray1>); +type PyCoo<'py> = ( + Bound<'py, PyArray1>, + Bound<'py, PyArray1>, + Bound<'py, PyArray1>, +); + +fn map_err(e: ppvm_lindblad::Error) -> PyErr { + PyValueError::new_err(e.to_string()) +} + +/// Reject a basis that contains the same Pauli word at two distinct rows. +/// Duplicate rows would silently overwrite each other in the generator's +/// row-index map and produce an incorrect sparse matrix. +fn assert_basis_unique(basis: &[Word]) -> PyResult<()> { + let mut seen: HashMap<&Word, usize> = HashMap::with_capacity(basis.len()); + for (i, w) in basis.iter().enumerate() { + if let Some(prev) = seen.insert(w, i) { + return Err(PyValueError::new_err(format!( + "basis contains duplicate Pauli word at row {prev} and row {i}" + ))); + } + } + Ok(()) +} + +/// Decode a `(N, n_qubits)` uint8 ndarray view into `N` packed [`Word`]s. +fn decode_basis(view: &numpy::ndarray::ArrayView2, n_qubits: usize) -> PyResult> { + let n_basis = view.shape()[0]; + let n_cols = view.shape()[1]; + if n_cols != n_qubits { + return Err(PyValueError::new_err(format!( + "basis has {n_cols} columns but spec.n_qubits = {n_qubits}" + ))); + } + let mut out = Vec::with_capacity(n_basis); + let mut row_buf = vec![0u8; n_qubits]; + for i in 0..n_basis { + let row = view.row(i); + for (q, slot) in row_buf.iter_mut().enumerate() { + *slot = row[q]; + } + out.push(word_from_codes(&row_buf).map_err(map_err)?); + } + Ok(out) +} + +/// Pack `Vec<(Word, f64)>` into the standard PyO3 return shape. +fn pack_pauli_map<'py>( + py: Python<'py>, + pairs: Vec<(Word, f64)>, + n_qubits: usize, +) -> PyResult> { + let m = pairs.len(); + let mut basis = vec![0u8; m * n_qubits]; + let mut coeffs = vec![0f64; m]; + for (i, (w, c)) in pairs.into_iter().enumerate() { + codes_from_word(&w, &mut basis[i * n_qubits..(i + 1) * n_qubits]); + coeffs[i] = c; + } + let basis_arr = basis + .into_pyarray(py) + .reshape([m, n_qubits]) + .map_err(|e| PyValueError::new_err(format!("reshape failed: {e}")))?; + Ok((basis_arr, coeffs.into_pyarray(py))) +} + +/// PyO3 facade exposing the Lindbladian shim to Python. +#[pyclass] +pub struct LindbladSpec { + inner: CoreSpec, +} + +#[pymethods] +impl LindbladSpec { + /// Construct a Lindbladian spec from Hamiltonian terms and jump operators. + /// + /// `jump_lincombs[k]` is a list of `(pauli_string, real, imag)` triples + /// encoding `L_k = Σ_a (re + i·im) P_a`. A length-1 jump with `im == 0` + /// is routed to the Hermitian-Pauli fast path (with rate scaled by `re²`). + #[new] + #[pyo3(signature = (n_qubits, h_terms, h_coeffs, jump_lincombs, jump_rates))] + fn new( + n_qubits: usize, + h_terms: Vec, + h_coeffs: Vec, + jump_lincombs: Vec>, + jump_rates: Vec, + ) -> PyResult { + if h_terms.len() != h_coeffs.len() { + return Err(PyValueError::new_err( + "h_terms and h_coeffs must have the same length", + )); + } + if jump_lincombs.len() != jump_rates.len() { + return Err(PyValueError::new_err( + "jump_lincombs and jump_rates must have the same length", + )); + } + let h: Vec<(String, f64)> = h_terms.into_iter().zip(h_coeffs).collect(); + let jumps: Vec = jump_lincombs + .into_iter() + .zip(jump_rates) + .map(|(lincomb, rate)| JumpInput { + lincomb: lincomb + .into_iter() + .map(|(s, re, im)| (s, Complex::new(re, im))) + .collect(), + rate, + }) + .collect(); + let inner = CoreSpec::new(n_qubits, &h, &jumps).map_err(map_err)?; + Ok(Self { inner }) + } + + #[getter] + fn n_qubits(&self) -> usize { + self.inner.n_qubits() + } + + #[getter] + fn num_h_terms(&self) -> usize { + self.inner.num_h_terms() + } + + #[getter] + fn num_jump_terms(&self) -> usize { + self.inner.num_jump_terms() + } + + /// Apply `L*` to a single Pauli string `p`. + fn action<'py>( + &self, + py: Python<'py>, + p: PyReadonlyArray1<'py, u8>, + ) -> PyResult> { + let p_slice = p.as_slice()?; + let p_word = word_from_codes(p_slice).map_err(map_err)?; + let pairs = self.inner.action(&p_word); + pack_pauli_map(py, pairs, self.inner.n_qubits()) + } + + /// Off-basis component of `L*( Σ_j coeffs[j] · basis[j] )`. + #[pyo3(signature = (basis, coeffs, protected = None))] + fn leakage<'py>( + &self, + py: Python<'py>, + basis: PyReadonlyArray2<'py, u8>, + coeffs: PyReadonlyArray1<'py, f64>, + protected: Option>, + ) -> PyResult> { + let n_q = self.inner.n_qubits(); + let basis_view = basis.as_array(); + let basis_words = decode_basis(&basis_view, n_q)?; + let coeffs_slice = coeffs.as_slice()?; + if coeffs_slice.len() != basis_words.len() { + return Err(PyValueError::new_err(format!( + "coeffs has length {} but basis has {} rows", + coeffs_slice.len(), + basis_words.len() + ))); + } + let protected_words: Vec = if let Some(ref prot) = protected { + let pv = prot.as_array(); + decode_basis(&pv, n_q)? + } else { + Vec::new() + }; + let pairs = self + .inner + .leakage(&basis_words, coeffs_slice, &protected_words) + .map_err(map_err)?; + pack_pauli_map(py, pairs, n_q) + } + + /// One predictor-corrector adaptive step. + /// + /// Internally: expand basis with first-hop leakage, predictor step + /// (`exp(dt·M)`), expand again with second-hop leakage from the + /// predicted state, then redo the step from the pre-step coefficients + /// on the doubly-enlarged basis. The matrix exponential is computed in + /// Rust via Al-Mohy & Higham scaling-and-squaring; no scipy required. + /// + /// Returns `(new_basis, new_coeffs)`. + #[pyo3(signature = ( + basis, coeffs, dt, tau_add, + drop_tol = 0.0, + protected = None, + num_threads = None, + ))] + #[allow(clippy::too_many_arguments)] + fn pc_step<'py>( + &self, + py: Python<'py>, + basis: PyReadonlyArray2<'py, u8>, + coeffs: PyReadonlyArray1<'py, f64>, + dt: f64, + tau_add: f64, + drop_tol: f64, + protected: Option>, + num_threads: Option, + ) -> PyResult> { + let n_q = self.inner.n_qubits(); + let basis_view = basis.as_array(); + let mut basis_words = decode_basis(&basis_view, n_q)?; + assert_basis_unique(&basis_words)?; + let mut coeffs_vec = coeffs.as_slice()?.to_vec(); + if coeffs_vec.len() != basis_words.len() { + return Err(PyValueError::new_err(format!( + "coeffs has length {} but basis has {} rows", + coeffs_vec.len(), + basis_words.len() + ))); + } + let protected_words: Vec = if let Some(ref p) = protected { + decode_basis(&p.as_array(), n_q)? + } else { + Vec::new() + }; + self.inner + .pc_step( + &mut basis_words, + &mut coeffs_vec, + dt, + &protected_words, + PcStepConfig { + tau_add, + drop_tol, + num_threads, + }, + ) + .map_err(map_err)?; + + // Pack output. Basis may have grown; coeffs has the same new length. + let pairs: Vec<(Word, f64)> = basis_words.into_iter().zip(coeffs_vec).collect(); + pack_pauli_map(py, pairs, n_q) + } + + /// Same as [`Self::pc_step`] but also returns a dict mapping phase + /// name → microseconds spent in that phase, for profiling. + #[pyo3(signature = ( + basis, coeffs, dt, tau_add, + drop_tol = 0.0, + protected = None, + num_threads = None, + ))] + #[allow(clippy::too_many_arguments)] + fn pc_step_timed<'py>( + &self, + py: Python<'py>, + basis: PyReadonlyArray2<'py, u8>, + coeffs: PyReadonlyArray1<'py, f64>, + dt: f64, + tau_add: f64, + drop_tol: f64, + protected: Option>, + num_threads: Option, + ) -> PyResult<(PyPauliMap<'py>, Bound<'py, pyo3::types::PyDict>)> { + let n_q = self.inner.n_qubits(); + let basis_view = basis.as_array(); + let mut basis_words = decode_basis(&basis_view, n_q)?; + assert_basis_unique(&basis_words)?; + let mut coeffs_vec = coeffs.as_slice()?.to_vec(); + if coeffs_vec.len() != basis_words.len() { + return Err(PyValueError::new_err(format!( + "coeffs has length {} but basis has {} rows", + coeffs_vec.len(), + basis_words.len() + ))); + } + let protected_words: Vec = if let Some(ref p) = protected { + decode_basis(&p.as_array(), n_q)? + } else { + Vec::new() + }; + let timings = self + .inner + .pc_step_timed( + &mut basis_words, + &mut coeffs_vec, + dt, + &protected_words, + PcStepConfig { + tau_add, + drop_tol, + num_threads, + }, + ) + .map_err(map_err)?; + + let pairs: Vec<(Word, f64)> = basis_words.into_iter().zip(coeffs_vec).collect(); + let map = pack_pauli_map(py, pairs, n_q)?; + let d = pyo3::types::PyDict::new(py); + d.set_item("leakage1_us", timings.leakage1_us)?; + d.set_item("expand1_us", timings.expand1_us)?; + d.set_item("gencsr1_us", timings.gencsr1_us)?; + d.set_item("expm1_us", timings.expm1_us)?; + d.set_item("leakage2_us", timings.leakage2_us)?; + d.set_item("expand2_us", timings.expand2_us)?; + d.set_item("gencsr2_us", timings.gencsr2_us)?; + d.set_item("expm2_us", timings.expm2_us)?; + Ok((map, d)) + } + + /// One classical RK4 step on the adjoint Lindbladian. Matrix-free: no + /// CSR, no Krylov, no predictor-corrector enrichment. Four action + /// evaluations per step, basis grows naturally, magnitude-prune at end. + #[pyo3(signature = ( + basis, coeffs, dt, + drop_tol = 0.0, + protected = None, + num_threads = None, + ))] + #[allow(clippy::too_many_arguments)] + fn rk4_step<'py>( + &self, + py: Python<'py>, + basis: PyReadonlyArray2<'py, u8>, + coeffs: PyReadonlyArray1<'py, f64>, + dt: f64, + drop_tol: f64, + protected: Option>, + num_threads: Option, + ) -> PyResult> { + let n_q = self.inner.n_qubits(); + let basis_view = basis.as_array(); + let mut basis_words = decode_basis(&basis_view, n_q)?; + assert_basis_unique(&basis_words)?; + let mut coeffs_vec = coeffs.as_slice()?.to_vec(); + if coeffs_vec.len() != basis_words.len() { + return Err(PyValueError::new_err(format!( + "coeffs has length {} but basis has {} rows", + coeffs_vec.len(), + basis_words.len() + ))); + } + let protected_words: Vec = if let Some(ref p) = protected { + decode_basis(&p.as_array(), n_q)? + } else { + Vec::new() + }; + self.inner + .rk4_step( + &mut basis_words, + &mut coeffs_vec, + dt, + drop_tol, + &protected_words, + num_threads, + ) + .map_err(map_err)?; + let pairs: Vec<(Word, f64)> = basis_words.into_iter().zip(coeffs_vec).collect(); + pack_pauli_map(py, pairs, n_q) + } + + /// Sparse generator matrix in COO form: `(rows, cols, vals)`. + fn generator<'py>( + &self, + py: Python<'py>, + basis: PyReadonlyArray2<'py, u8>, + ) -> PyResult> { + let n_q = self.inner.n_qubits(); + let basis_view = basis.as_array(); + let basis_words = decode_basis(&basis_view, n_q)?; + assert_basis_unique(&basis_words)?; + let triplets = self.inner.generator(&basis_words); + let total = triplets.len(); + let mut rows = Vec::with_capacity(total); + let mut cols = Vec::with_capacity(total); + let mut vals = Vec::with_capacity(total); + for (r, c, v) in triplets { + rows.push(r as u64); + cols.push(c as u64); + vals.push(v); + } + Ok(( + rows.into_pyarray(py), + cols.into_pyarray(py), + vals.into_pyarray(py), + )) + } +} diff --git a/crates/ppvm-runtime/Cargo.toml b/crates/ppvm-runtime/Cargo.toml index 5a4072543..3e1cf9cdd 100644 --- a/crates/ppvm-runtime/Cargo.toml +++ b/crates/ppvm-runtime/Cargo.toml @@ -53,3 +53,7 @@ harness = false [[bench]] name = "micro" harness = false + +[[bench]] +name = "truncation-weight" +harness = false diff --git a/crates/ppvm-runtime/benches/trotter.rs b/crates/ppvm-runtime/benches/trotter.rs index 50d75af03..2fbd84be4 100644 --- a/crates/ppvm-runtime/benches/trotter.rs +++ b/crates/ppvm-runtime/benches/trotter.rs @@ -3,10 +3,12 @@ use criterion::{Criterion, criterion_group, criterion_main}; use ppvm_runtime::prelude::*; -use ppvm_runtime::strategy::CoefficientThreshold; +use ppvm_runtime::strategy::{CoefficientThreshold, CombinedStrategy, MaxPauliWeight}; use rayon::current_num_threads; -fn trotter_func>( +fn trotter_func< + T: Config>, +>( state: &mut PauliSum, n: usize, total_time: &f64, @@ -43,7 +45,9 @@ fn trotter_func>( } } -pub fn benchmark_suite_trotter>( +pub fn benchmark_suite_trotter< + T: Config>, +>( c: &mut Criterion, name: impl AsRef, ) { @@ -56,7 +60,8 @@ pub fn benchmark_suite_trotter = PauliSum::builder() .n_qubits(n_qubits) .strategy(strat) @@ -91,34 +96,28 @@ pub fn benchmark_suite_trotter>( - c, - "ByteF64GxHashMap<2, CoefficientThreshold>", - ); - benchmark_suite_trotter::>( - c, - "ByteF64FxHashMap<2, CoefficientThreshold>", - ); - benchmark_suite_trotter::>( - c, - "ByteF64FxDashMap<2, CoefficientThreshold>", - ); - benchmark_suite_trotter::>( - c, - "ByteF64GxDashMap<2, CoefficientThreshold>", - ); - benchmark_suite_trotter::>( - c, - "ByteF64FxIndexMap<2, CoefficientThreshold>", - ); - benchmark_suite_trotter::>( - c, - "ByteF64GxIndexMap<2, CoefficientThreshold>", - ); + benchmark_suite_trotter::< + config::gxhash::ByteF64<2, CombinedStrategy>, + >(c, "ByteF64GxHashMap<2, CoefficientThreshold>"); + benchmark_suite_trotter::< + config::fxhash::ByteF64<2, CombinedStrategy>, + >(c, "ByteF64FxHashMap<2, CoefficientThreshold>"); + benchmark_suite_trotter::< + config::dashmap::ByteFxHashF64<2, CombinedStrategy>, + >(c, "ByteF64FxDashMap<2, CoefficientThreshold>"); + benchmark_suite_trotter::< + config::dashmap::ByteGxHashF64<2, CombinedStrategy>, + >(c, "ByteF64GxDashMap<2, CoefficientThreshold>"); + benchmark_suite_trotter::< + config::indexmap::ByteFxHashF64<2, CombinedStrategy>, + >(c, "ByteF64FxIndexMap<2, CoefficientThreshold>"); + benchmark_suite_trotter::< + config::indexmap::ByteGxHashF64<2, CombinedStrategy>, + >(c, "ByteF64GxIndexMap<2, CoefficientThreshold>"); } criterion_group!(benches, trotter_benchmarks); diff --git a/crates/ppvm-runtime/benches/truncation-weight.rs b/crates/ppvm-runtime/benches/truncation-weight.rs new file mode 100644 index 000000000..b93e074b1 --- /dev/null +++ b/crates/ppvm-runtime/benches/truncation-weight.rs @@ -0,0 +1,169 @@ +// SPDX-FileCopyrightText: 2026 The PPVM Authors +// SPDX-License-Identifier: Apache-2.0 + +//! Micro-benchmark for the cost of `MaxPauliWeight` truncation on a +//! pre-built `PauliSum`. Compares three strategies: +//! - `MaxPauliWeight(w)` alone (single retain pass, weight check only) +//! - `CoefficientThreshold(eps)` alone (single retain pass, coeff check only) +//! - `CombinedStrategy(threshold, weight)` (two sequential retain passes) +//! +//! Mirrored on the Julia side by +//! `julia-benchmarks/benches/truncation-weight.jl`, which uses +//! PauliPropagation.jl's `truncate!` — a *single* walk with a combined +//! predicate. The point of comparison is the two-passes-vs-one structural +//! difference between Rust's `CombinedStrategy` and PP.jl's `truncate!`. + +use std::time::Duration; + +use criterion::{Criterion, criterion_group, criterion_main}; +use ppvm_runtime::config::fxhash::ByteF64; +use ppvm_runtime::prelude::*; +use ppvm_runtime::strategy::{CoefficientThreshold, CombinedStrategy, MaxPauliWeight}; + +const N_QUBITS: usize = 128; +const N: usize = 16; +const N_TERMS: usize = 1000; +const COEFF_EPS: f64 = 1e-12; + +type Word = as Config>::PauliWordType; + +fn configure() -> Criterion { + Criterion::default() + .warm_up_time(Duration::from_secs(1)) + .measurement_time(Duration::from_secs(3)) + .sample_size(50) +} + +/// Build `N_TERMS` Pauli terms each with exactly `target_weight` +/// non-identity slots (clamped to `N_QUBITS`). Positions are spread by +/// stride to fit `target_weight` distinct slots; Pauli choices depend +/// on `k` so terms are mostly distinct. +fn make_terms(target_weight: usize) -> Vec<(Word, f64)> { + let paulis = [Pauli::X, Pauli::Y, Pauli::Z]; + let weight = target_weight.min(N_QUBITS); + let stride = (N_QUBITS / weight.max(1)).max(1); + let mut terms = Vec::with_capacity(N_TERMS); + for k in 0..N_TERMS { + let mut word = Word::new(N_QUBITS); + for w in 0..weight { + let pos = (k + w * stride) % N_QUBITS; + word.set(pos, paulis[(k.wrapping_mul(31) + w) % 3]); + } + terms.push((word, 1.0 / (k as f64 + 1.0))); + } + terms +} + +fn build_state(strat: St, terms: &[(Word, f64)]) -> PauliSum> +where + St: Strategy + Copy, +{ + let mut state: PauliSum> = PauliSum::builder() + .n_qubits(N_QUBITS) + .capacity(terms.len() * 2) + .strategy(strat) + .build(); + for (w, c) in terms { + state += (w.clone(), *c); + } + state +} + +const PROFILES: &[(&str, usize)] = &[ + ("w3", 3), + ("w50", 50), + ("w120", 120), +]; + +const CUTOFFS: &[(&str, usize)] = &[ + ("10", 10), + ("100", 100), + ("1000", 1000), + ("max", usize::MAX), +]; + +fn bench_max_weight_alone(c: &mut Criterion) { + let mut group = c.benchmark_group("max-weight-only"); + for &(profile, weight) in PROFILES { + let terms = make_terms(weight); + for &(cutoff_name, cutoff) in CUTOFFS { + let state = build_state(MaxPauliWeight(cutoff), &terms); + println!( + "[max-weight-only/{profile}/cut-{cutoff_name}] state.len()={}", + state.len() + ); + group.bench_function(format!("{profile}/cut-{cutoff_name}"), |b| { + b.iter_batched_ref( + || state.clone(), + |s| s.truncate(), + criterion::BatchSize::SmallInput, + ); + }); + } + } + group.finish(); +} + +fn bench_coeff_threshold_alone(c: &mut Criterion) { + let mut group = c.benchmark_group("coeff-threshold-only"); + for &(profile, weight) in PROFILES { + let terms = make_terms(weight); + let state = build_state(CoefficientThreshold(COEFF_EPS), &terms); + println!( + "[coeff-threshold-only/{profile}] state.len()={}", + state.len() + ); + group.bench_function(profile, |b| { + b.iter_batched_ref( + || state.clone(), + |s| s.truncate(), + criterion::BatchSize::SmallInput, + ); + }); + } + group.finish(); +} + +fn bench_combined(c: &mut Criterion) { + let mut group = c.benchmark_group("combined"); + for &(profile, weight) in PROFILES { + let terms = make_terms(weight); + for &(cutoff_name, cutoff) in CUTOFFS { + let strat = CombinedStrategy(CoefficientThreshold(COEFF_EPS), MaxPauliWeight(cutoff)); + let state = build_state(strat, &terms); + group.bench_function(format!("{profile}/cut-{cutoff_name}"), |b| { + b.iter_batched_ref( + || state.clone(), + |s| s.truncate(), + criterion::BatchSize::SmallInput, + ); + }); + } + } + group.finish(); +} + +/// Clone-only baseline so the user can subtract it from the truncate +/// numbers if desired. `iter_batched_ref` excludes setup time, so this +/// shouldn't be necessary — but worth confirming. +fn bench_clone_baseline(c: &mut Criterion) { + let mut group = c.benchmark_group("clone-baseline"); + for &(profile, weight) in PROFILES { + let terms = make_terms(weight); + let state = build_state(NoStrategy, &terms); + group.bench_function(profile, |b| { + b.iter(|| state.clone()); + }); + } + group.finish(); +} + +criterion_group! { + name = benches; + config = configure(); + targets = bench_max_weight_alone, + bench_coeff_threshold_alone, + bench_combined, + bench_clone_baseline +} +criterion_main!(benches); diff --git a/crates/ppvm-runtime/src/loss/data.rs b/crates/ppvm-runtime/src/loss/data.rs index e1c2615ac..884f6b010 100644 --- a/crates/ppvm-runtime/src/loss/data.rs +++ b/crates/ppvm-runtime/src/loss/data.rs @@ -131,12 +131,72 @@ impl PauliWordTrait for Lossy self.zbits.set(index, value); } + #[inline] fn weight(&self) -> usize { - (self.xbits | self.zbits | self.lbits).count_ones() + let xs: &[u8] = bytemuck::bytes_of(&self.xbits.data); + let zs: &[u8] = bytemuck::bytes_of(&self.zbits.data); + let ls: &[u8] = bytemuck::bytes_of(&self.lbits.data); + debug_assert_eq!(xs.len(), zs.len()); + debug_assert_eq!(xs.len(), ls.len()); + + let mut total: u32 = 0; + let (mut i, n) = (0usize, xs.len()); + + while i + 8 <= n { + let x = u64::from_ne_bytes(xs[i..i + 8].try_into().unwrap()); + let z = u64::from_ne_bytes(zs[i..i + 8].try_into().unwrap()); + let l = u64::from_ne_bytes(ls[i..i + 8].try_into().unwrap()); + total += (x | z | l).count_ones(); + i += 8; + } + if i + 4 <= n { + let x = u32::from_ne_bytes(xs[i..i + 4].try_into().unwrap()); + let z = u32::from_ne_bytes(zs[i..i + 4].try_into().unwrap()); + let l = u32::from_ne_bytes(ls[i..i + 4].try_into().unwrap()); + total += (x | z | l).count_ones(); + i += 4; + } + if i + 2 <= n { + let x = u16::from_ne_bytes(xs[i..i + 2].try_into().unwrap()); + let z = u16::from_ne_bytes(zs[i..i + 2].try_into().unwrap()); + let l = u16::from_ne_bytes(ls[i..i + 2].try_into().unwrap()); + total += (x | z | l).count_ones(); + i += 2; + } + if i < n { + total += (xs[i] | zs[i] | ls[i]).count_ones(); + } + + total as usize } + #[inline] fn loss_weight(&self) -> usize { - self.lbits.count_ones() + let ls: &[u8] = bytemuck::bytes_of(&self.lbits.data); + + let mut total: u32 = 0; + let (mut i, n) = (0usize, ls.len()); + + while i + 8 <= n { + let l = u64::from_ne_bytes(ls[i..i + 8].try_into().unwrap()); + total += l.count_ones(); + i += 8; + } + if i + 4 <= n { + let l = u32::from_ne_bytes(ls[i..i + 4].try_into().unwrap()); + total += l.count_ones(); + i += 4; + } + if i + 2 <= n { + let l = u16::from_ne_bytes(ls[i..i + 2].try_into().unwrap()); + total += l.count_ones(); + i += 2; + } + if i < n { + total += ls[i].count_ones(); + } + + total as usize } fn rehash(&mut self) { diff --git a/crates/ppvm-runtime/src/strategy.rs b/crates/ppvm-runtime/src/strategy.rs index a5804249d..087c1a80d 100644 --- a/crates/ppvm-runtime/src/strategy.rs +++ b/crates/ppvm-runtime/src/strategy.rs @@ -78,6 +78,14 @@ impl Strategy for MaxPauliWeight { W: PauliWordTrait, M: ACMap, { + // `usize::MAX` is the conventional "disabled" sentinel (matches + // `Default::default()`). Skip the retain pass entirely — saves a + // full bucket walk per `truncate()` call when callers (e.g. the + // Python binding) pass `MaxPauliWeight(usize::MAX)` to opt out + // of weight truncation without changing the strategy type. + if self.0 == usize::MAX { + return; + } map.retain(|k, _| k.weight() <= self.max_weight()); } } @@ -152,6 +160,11 @@ impl Strategy for MaxLossWeight { M: ACMap, W: PauliWordTrait, { + // Skip the retain pass when callers pass `usize::MAX` to opt out + // of loss-weight truncation without changing the strategy type. + if self.0 == usize::MAX { + return; + } map.retain(|k, _| k.loss_weight() <= self.0); } } diff --git a/crates/ppvm-runtime/src/traits/coefficient.rs b/crates/ppvm-runtime/src/traits/coefficient.rs index f2a836d11..3128f3eda 100644 --- a/crates/ppvm-runtime/src/traits/coefficient.rs +++ b/crates/ppvm-runtime/src/traits/coefficient.rs @@ -56,6 +56,7 @@ impl Coefficient for f64 { Float::sin_cos(*self) } + #[inline] fn cutoff(&self, threshold: f64) -> bool { self.abs() < threshold } @@ -76,6 +77,7 @@ pub trait ComplexCoefficient: Coefficient { } impl Coefficient for num::complex::Complex { + #[inline] fn cutoff(&self, threshold: f64) -> bool { self.norm() < threshold } diff --git a/crates/ppvm-runtime/src/word/data.rs b/crates/ppvm-runtime/src/word/data.rs index 477ecfe9c..4b5295108 100644 --- a/crates/ppvm-runtime/src/word/data.rs +++ b/crates/ppvm-runtime/src/word/data.rs @@ -144,8 +144,39 @@ impl Paul self.zbits.set(index, value); } + #[inline] fn weight(&self) -> usize { - (self.xbits | self.zbits).count_ones() + let xs: &[u8] = bytemuck::bytes_of(&self.xbits.data); + let zs: &[u8] = bytemuck::bytes_of(&self.zbits.data); + debug_assert_eq!(xs.len(), zs.len()); + + let mut total: u32 = 0; + let (mut i, n) = (0usize, xs.len()); + + // u64 chunks — one popcnt per chunk (x86 +popcnt; AArch64 CNT+ADDV). + while i + 8 <= n { + let x = u64::from_ne_bytes(xs[i..i + 8].try_into().unwrap()); + let z = u64::from_ne_bytes(zs[i..i + 8].try_into().unwrap()); + total += (x | z).count_ones(); + i += 8; + } + if i + 4 <= n { + let x = u32::from_ne_bytes(xs[i..i + 4].try_into().unwrap()); + let z = u32::from_ne_bytes(zs[i..i + 4].try_into().unwrap()); + total += (x | z).count_ones(); + i += 4; + } + if i + 2 <= n { + let x = u16::from_ne_bytes(xs[i..i + 2].try_into().unwrap()); + let z = u16::from_ne_bytes(zs[i..i + 2].try_into().unwrap()); + total += (x | z).count_ones(); + i += 2; + } + if i < n { + total += (xs[i] | zs[i]).count_ones(); + } + + total as usize } fn rehash(&mut self) { diff --git a/julia-benchmarks/Manifest.toml b/julia-benchmarks/Manifest.toml index ec1916a95..3c050de35 100644 --- a/julia-benchmarks/Manifest.toml +++ b/julia-benchmarks/Manifest.toml @@ -15,11 +15,28 @@ weakdeps = ["ChainRulesCore", "Test"] AbstractFFTsChainRulesCoreExt = "ChainRulesCore" AbstractFFTsTestExt = "Test" +[[deps.AbstractTrees]] +git-tree-sha1 = "2d9c9a55f9c93e8887ad391fbae72f8ef55e1177" +uuid = "1520ce14-60c1-5f80-bbc7-55ef81b5835c" +version = "0.4.5" + +[[deps.AcceleratedKernels]] +deps = ["ArgCheck", "GPUArraysCore", "KernelAbstractions", "Markdown", "UnsafeAtomics"] +git-tree-sha1 = "0de01460ed11e90b42ce666c8ed0265bad59aa6a" +uuid = "6a4ca0a5-0e36-4168-a932-d9be78d558f1" +version = "0.4.3" + + [deps.AcceleratedKernels.extensions] + AcceleratedKernelsoneAPIExt = "oneAPI" + + [deps.AcceleratedKernels.weakdeps] + oneAPI = "8f75cd03-7ff8-4ecb-9b8f-daf728133b1b" + [[deps.Adapt]] -deps = ["LinearAlgebra", "Requires"] -git-tree-sha1 = "7e35fca2bdfba44d797c53dfe63a51fabf39bfc0" +deps = ["LinearAlgebra"] +git-tree-sha1 = "7715e5b2b186c4d9b664d299d2c9e48b9a778c88" uuid = "79e6a3ab-5dfb-504d-930d-738a2a938a0e" -version = "4.4.0" +version = "4.6.1" weakdeps = ["SparseArrays", "StaticArrays"] [deps.Adapt.extensions] @@ -32,6 +49,11 @@ git-tree-sha1 = "9876e1e164b144ca45e9e3198d0b689cadfed9ff" uuid = "66dad0bd-aa9a-41b7-9441-69ab47430ed8" version = "1.1.3" +[[deps.ArgCheck]] +git-tree-sha1 = "f9e9a66c9b7be1ad7372bbd9b062d9230c30c5ce" +uuid = "dce04be8-c92d-5529-be00-80e4d2c0e197" +version = "2.5.0" + [[deps.ArgTools]] uuid = "0dad84c5-d112-42e6-8d28-ef12dabb789f" version = "1.1.2" @@ -49,15 +71,33 @@ uuid = "7d9fca2a-8960-54d3-9f78-7d1dccf2cb97" version = "0.5.4" [[deps.Arpack_jll]] -deps = ["Artifacts", "CompilerSupportLibraries_jll", "JLLWrappers", "Libdl", "OpenBLAS_jll", "Pkg"] -git-tree-sha1 = "5ba6c757e8feccf03a1554dfaf3e26b3cfc7fd5e" +deps = ["Artifacts", "CompilerSupportLibraries_jll", "JLLWrappers", "Libdl", "libblastrampoline_jll"] +git-tree-sha1 = "7f54761502ff149a9d492e4acefe9805898e29b3" uuid = "68821587-b530-5797-8361-c406ea357684" -version = "3.5.1+1" +version = "3.5.2+0" [[deps.Artifacts]] uuid = "56f22d72-fd6d-98f1-02f0-08ddc0907c33" version = "1.11.0" +[[deps.Atomix]] +deps = ["UnsafeAtomics"] +git-tree-sha1 = "b8651b2eb5796a386b0398a20b519a6a6150f75c" +uuid = "a9b6321e-bd34-4604-b9c9-b65b8de01458" +version = "1.1.3" + + [deps.Atomix.extensions] + AtomixCUDAExt = "CUDA" + AtomixMetalExt = "Metal" + AtomixOpenCLExt = "OpenCL" + AtomixoneAPIExt = "oneAPI" + + [deps.Atomix.weakdeps] + CUDA = "052768ef-5323-5732-b1bb-66c8b64840ba" + Metal = "dde4c033-4e86-420c-a63e-0dd931031962" + OpenCL = "08131aa3-fb12-5dee-8b74-c09406e224a2" + oneAPI = "8f75cd03-7ff8-4ecb-9b8f-daf728133b1b" + [[deps.AutoHashEquals]] git-tree-sha1 = "4ec6b48702dacc5994a835c1189831755e4e76ef" uuid = "15f4f7f2-30c1-5605-9d31-71845cf9641f" @@ -80,21 +120,21 @@ uuid = "ab8c0f59-4072-4e0d-8f91-a91e1495eb26" version = "0.1.0" [[deps.BenchmarkTools]] -deps = ["Compat", "JSON", "Logging", "Printf", "Profile", "Statistics", "UUIDs"] -git-tree-sha1 = "7fecfb1123b8d0232218e2da0c213004ff15358d" +deps = ["Compat", "JSON", "Logging", "PrecompileTools", "Printf", "Profile", "Statistics", "UUIDs"] +git-tree-sha1 = "9670d3febc2b6da60a0ae57846ba74670290653f" uuid = "6e4b80f9-dd63-53aa-95a3-0cdb28fa8baf" -version = "1.6.3" +version = "1.8.0" [[deps.BitFlags]] -git-tree-sha1 = "0691e34b3bb8be9307330f88d1a3c3f25466c24d" +git-tree-sha1 = "bbe1079eecf9c9fbb52765193ad2bae27ae09bc8" uuid = "d1d4a3ce-64b1-5f1a-9ba4-7e7e69966f35" -version = "0.1.9" +version = "0.1.10" [[deps.BitIntegers]] deps = ["Random"] -git-tree-sha1 = "f98cfeaba814d9746617822032d50a31c9926604" +git-tree-sha1 = "091d591a060e43df1dd35faab3ca284925c48e46" uuid = "c3b6d118-76ef-56ca-8cc7-ebb389d030a1" -version = "0.3.5" +version = "0.3.7" [[deps.Bits]] deps = ["Test"] @@ -109,16 +149,16 @@ uuid = "6e34b625-4abd-537c-b88f-471c36dfa7a0" version = "1.0.9+0" [[deps.Cairo_jll]] -deps = ["Artifacts", "Bzip2_jll", "CompilerSupportLibraries_jll", "Fontconfig_jll", "FreeType2_jll", "Glib_jll", "JLLWrappers", "LZO_jll", "Libdl", "Pixman_jll", "Xorg_libXext_jll", "Xorg_libXrender_jll", "Zlib_jll", "libpng_jll"] -git-tree-sha1 = "fde3bf89aead2e723284a8ff9cdf5b551ed700e8" +deps = ["Artifacts", "Bzip2_jll", "CompilerSupportLibraries_jll", "Fontconfig_jll", "FreeType2_jll", "Glib_jll", "JLLWrappers", "Libdl", "Pixman_jll", "Xorg_libXext_jll", "Xorg_libXrender_jll", "Zlib_jll", "libpng_jll"] +git-tree-sha1 = "1fa950ebc3e37eccd51c6a8fe1f92f7d86263522" uuid = "83423d85-b0ee-5818-9007-b63ccbeb887a" -version = "1.18.5+0" +version = "1.18.7+0" [[deps.ChainRulesCore]] deps = ["Compat", "LinearAlgebra"] -git-tree-sha1 = "e4c6a16e77171a5f5e25e9646617ab1c276c5607" +git-tree-sha1 = "12177ad6b3cad7fd50c8b3825ce24a99ad61c18f" uuid = "d360d2e6-b24c-11e9-a2a3-2a2ae2dbcce4" -version = "1.26.0" +version = "1.26.1" weakdeps = ["SparseArrays"] [deps.ChainRulesCore.extensions] @@ -185,9 +225,9 @@ version = "1.3.0+1" [[deps.ConcurrentUtilities]] deps = ["Serialization", "Sockets"] -git-tree-sha1 = "d9d26935a0bcffc87d2613ce14c527c99fc543fd" +git-tree-sha1 = "21d088c496ea22914fe80906eb5bce65755e5ec8" uuid = "f0e56b4a-5159-44fe-b623-3e5288b988bb" -version = "2.5.0" +version = "2.5.1" [[deps.Contour]] git-tree-sha1 = "439e35b0b36e2e5881738abc8857bd92ad6ff9a8" @@ -200,10 +240,10 @@ uuid = "9a962f9c-6df0-11e9-0e5d-c546b8b5ee8a" version = "1.16.0" [[deps.DataStructures]] -deps = ["InteractiveUtils", "OrderedCollections"] -git-tree-sha1 = "88d48e133e6d3dd68183309877eac74393daa7eb" +deps = ["OrderedCollections"] +git-tree-sha1 = "6fb53a69613a0b2b68a0d12671717d307ab8b24e" uuid = "864edb3b-99cc-5e75-8d2d-829cb0a9cfe8" -version = "0.17.20" +version = "0.19.5" [[deps.DataValueInterfaces]] git-tree-sha1 = "bfc1187b79289637fa0ef6d4436ebdfe6905cbd6" @@ -245,9 +285,9 @@ version = "1.11.0" [[deps.Distributions]] deps = ["AliasTables", "FillArrays", "LinearAlgebra", "PDMats", "Printf", "QuadGK", "Random", "SpecialFunctions", "Statistics", "StatsAPI", "StatsBase", "StatsFuns"] -git-tree-sha1 = "3bc002af51045ca3b47d2e1787d6ce02e68b943a" +git-tree-sha1 = "96f76dcd6cc75cf8eb49109123868499d413f526" uuid = "31c24e10-a181-5473-b8eb-7969acd0382f" -version = "0.25.122" +version = "0.25.126" [deps.Distributions.extensions] DistributionsChainRulesCoreExt = "ChainRulesCore" @@ -283,9 +323,9 @@ version = "0.1.11" [[deps.Expat_jll]] deps = ["Artifacts", "JLLWrappers", "Libdl"] -git-tree-sha1 = "27af30de8b5445644e8ffe3bcb0d72049c089cf1" +git-tree-sha1 = "c307cd83373868391f3ac30b41530bc5d5d05d08" uuid = "2e619515-83b5-522b-bb60-26c02a35a201" -version = "2.7.3+0" +version = "2.8.1+0" [[deps.FFMPEG]] deps = ["FFMPEG_jll"] @@ -294,22 +334,16 @@ uuid = "c87230d0-a227-11e9-1b43-d7ebe4e7570a" version = "0.4.5" [[deps.FFMPEG_jll]] -deps = ["Artifacts", "Bzip2_jll", "FreeType2_jll", "FriBidi_jll", "JLLWrappers", "LAME_jll", "Libdl", "Ogg_jll", "OpenSSL_jll", "Opus_jll", "PCRE2_jll", "Zlib_jll", "libaom_jll", "libass_jll", "libfdk_aac_jll", "libvorbis_jll", "x264_jll", "x265_jll"] -git-tree-sha1 = "ccc81ba5e42497f4e76553a5545665eed577a663" +deps = ["Artifacts", "Bzip2_jll", "FreeType2_jll", "FriBidi_jll", "JLLWrappers", "LAME_jll", "Libdl", "Ogg_jll", "OpenSSL_jll", "Opus_jll", "PCRE2_jll", "Zlib_jll", "libaom_jll", "libass_jll", "libfdk_aac_jll", "libva_jll", "libvorbis_jll", "x264_jll", "x265_jll"] +git-tree-sha1 = "cac41ca6b2d399adfc95e51240566f8a60a80806" uuid = "b22a6f82-2f65-5046-a5b2-351ab43fb4e5" -version = "8.0.0+0" +version = "8.1.0+0" -[[deps.FFTW]] -deps = ["AbstractFFTs", "FFTW_jll", "Libdl", "LinearAlgebra", "MKL_jll", "Preferences", "Reexport"] -git-tree-sha1 = "97f08406df914023af55ade2f843c39e99c5d969" -uuid = "7a1cc6ca-52ef-59f5-83cd-3a7055c09341" -version = "1.10.0" - -[[deps.FFTW_jll]] -deps = ["Artifacts", "JLLWrappers", "Libdl"] -git-tree-sha1 = "6d6219a004b8cf1e0b4dbe27a2860b8e04eba0be" -uuid = "f5851436-0d7a-5f13-b9de-f02708fd171a" -version = "3.3.11+0" +[[deps.FFTA]] +deps = ["AbstractFFTs", "DocStringExtensions", "LinearAlgebra", "MuladdMacro", "Primes", "Random", "Reexport"] +git-tree-sha1 = "65e55303b72f4a567a51b174dd2c47496efeb95a" +uuid = "b86e33f2-c0db-4aa1-a6e0-ab43e668529e" +version = "0.3.1" [[deps.FileWatching]] uuid = "7b1f6079-737a-58dc-b8bc-7a2ca5c1b5ee" @@ -317,21 +351,22 @@ version = "1.11.0" [[deps.FillArrays]] deps = ["LinearAlgebra"] -git-tree-sha1 = "173e4d8f14230a7523ae11b9a3fa9edb3e0efd78" +git-tree-sha1 = "2f979084d1e13948a3352cf64a25df6bd3b4dca3" uuid = "1a297f60-69ca-5386-bcde-b61e274b549b" -version = "1.14.0" -weakdeps = ["PDMats", "SparseArrays", "Statistics"] +version = "1.16.0" +weakdeps = ["PDMats", "SparseArrays", "StaticArrays", "Statistics"] [deps.FillArrays.extensions] FillArraysPDMatsExt = "PDMats" FillArraysSparseArraysExt = "SparseArrays" + FillArraysStaticArraysExt = "StaticArrays" FillArraysStatisticsExt = "Statistics" [[deps.FixedPointNumbers]] -deps = ["Statistics"] -git-tree-sha1 = "05882d6995ae5c12bb5f36dd2ed3f61c98cbb172" +deps = ["Random", "Statistics"] +git-tree-sha1 = "59af96b98217c6ef4ae0dfe065ac7c20831d1a84" uuid = "53c48c17-4a7d-5ca2-90c5-79b7896eea93" -version = "0.8.5" +version = "0.8.6" [[deps.Fontconfig_jll]] deps = ["Artifacts", "Bzip2_jll", "Expat_jll", "FreeType2_jll", "JLLWrappers", "Libdl", "Libuuid_jll", "Zlib_jll"] @@ -346,9 +381,9 @@ version = "1.3.7" [[deps.FreeType2_jll]] deps = ["Artifacts", "Bzip2_jll", "JLLWrappers", "Libdl", "Zlib_jll"] -git-tree-sha1 = "2c5512e11c791d1baed2049c5652441b28fc6a31" +git-tree-sha1 = "70329abc09b886fd2c5d94ad2d9527639c421e3e" uuid = "d7e528f0-a631-5988-bf34-fe36492bcfd7" -version = "2.13.4+0" +version = "2.14.3+1" [[deps.FriBidi_jll]] deps = ["Artifacts", "JLLWrappers", "Libdl"] @@ -358,21 +393,33 @@ version = "1.0.17+0" [[deps.GLFW_jll]] deps = ["Artifacts", "JLLWrappers", "Libdl", "Libglvnd_jll", "Xorg_libXcursor_jll", "Xorg_libXi_jll", "Xorg_libXinerama_jll", "Xorg_libXrandr_jll", "libdecor_jll", "xkbcommon_jll"] -git-tree-sha1 = "fcb0584ff34e25155876418979d4c8971243bb89" +git-tree-sha1 = "9e0fb9e54594c47f278d75063980e43066e26e20" uuid = "0656b61e-2033-5cc2-a64a-77c0f6c09b89" -version = "3.4.0+2" +version = "3.4.1+1" + +[[deps.GPUArraysCore]] +deps = ["Adapt"] +git-tree-sha1 = "83cf05ab16a73219e5f6bd1bdfa9848fa24ac627" +uuid = "46192b85-c4d5-4398-a991-12ede77f4527" +version = "0.2.0" [[deps.GR]] deps = ["Artifacts", "Base64", "DelimitedFiles", "Downloads", "GR_jll", "HTTP", "JSON", "Libdl", "LinearAlgebra", "Preferences", "Printf", "Qt6Wayland_jll", "Random", "Serialization", "Sockets", "TOML", "Tar", "Test", "p7zip_jll"] -git-tree-sha1 = "f52c27dd921390146624f3aab95f4e8614ad6531" +git-tree-sha1 = "f954322d5de03ec630d177cda203dcd92b6be399" uuid = "28b8d3ca-fb5f-59d9-8090-bfdbd6d07a71" -version = "0.73.18" +version = "0.73.26" + + [deps.GR.extensions] + IJuliaExt = "IJulia" + + [deps.GR.weakdeps] + IJulia = "7073ff75-c697-5162-941a-fcdaad2a7d2a" [[deps.GR_jll]] deps = ["Artifacts", "Bzip2_jll", "Cairo_jll", "FFMPEG_jll", "Fontconfig_jll", "FreeType2_jll", "GLFW_jll", "JLLWrappers", "JpegTurbo_jll", "Libdl", "Libtiff_jll", "Pixman_jll", "Qt6Base_jll", "Zlib_jll", "libpng_jll"] -git-tree-sha1 = "4b0406b866ea9fdbaf1148bc9c0b887e59f9af68" +git-tree-sha1 = "6fada551286ab6ea4ca1628cb2de9f166a2ec966" uuid = "d2c73de3-f751-5644-a686-071e5b155ba9" -version = "0.73.18+0" +version = "0.73.26+0" [[deps.GettextRuntime_jll]] deps = ["Artifacts", "CompilerSupportLibraries_jll", "JLLWrappers", "Libdl", "Libiconv_jll"] @@ -388,21 +435,25 @@ version = "9.55.1+0" [[deps.Glib_jll]] deps = ["Artifacts", "GettextRuntime_jll", "JLLWrappers", "Libdl", "Libffi_jll", "Libiconv_jll", "Libmount_jll", "PCRE2_jll", "Zlib_jll"] -git-tree-sha1 = "50c11ffab2a3d50192a228c313f05b5b5dc5acb2" +git-tree-sha1 = "24f6def62397474a297bfcec22384101609142ed" uuid = "7746bdde-850d-59dc-9ae8-88ece973131d" -version = "2.86.0+0" +version = "2.86.3+0" [[deps.Graphite2_jll]] deps = ["Artifacts", "JLLWrappers", "Libdl"] -git-tree-sha1 = "8a6dbda1fd736d60cc477d99f2e7a042acfa46e8" +git-tree-sha1 = "69ffb934a5c5b7e086a0b4fee3427db2556fba6e" uuid = "3b182d85-2403-5c21-9c21-1e1f0cc25472" -version = "1.3.15+0" +version = "1.3.16+0" [[deps.Graphs]] -deps = ["ArnoldiMethod", "DataStructures", "Distributed", "Inflate", "LinearAlgebra", "Random", "SharedArrays", "SimpleTraits", "SparseArrays", "Statistics"] -git-tree-sha1 = "7a98c6502f4632dbe9fb1973a4244eaa3324e84d" +deps = ["ArnoldiMethod", "DataStructures", "Inflate", "LinearAlgebra", "Random", "SimpleTraits", "SparseArrays", "Statistics"] +git-tree-sha1 = "7eb45fe833a5b7c51cf6d89c5a841d5967e44be3" uuid = "86223c79-3864-5bf0-83f7-82e725a168b6" -version = "1.13.1" +version = "1.14.0" +weakdeps = ["Distributed", "SharedArrays"] + + [deps.Graphs.extensions] + GraphsSharedArraysExt = "SharedArrays" [[deps.Grisu]] git-tree-sha1 = "53bb909d1151e57e2484c3d1b53e19552b887fb2" @@ -411,9 +462,9 @@ version = "1.0.2" [[deps.HTTP]] deps = ["Base64", "CodecZlib", "ConcurrentUtilities", "Dates", "ExceptionUnwrapping", "Logging", "LoggingExtras", "MbedTLS", "NetworkOptions", "OpenSSL", "PrecompileTools", "Random", "SimpleBufferStream", "Sockets", "URIs", "UUIDs"] -git-tree-sha1 = "5e6fe50ae7f23d171f44e311c2960294aaa0beb5" +git-tree-sha1 = "51059d23c8bb67911a2e6fd5130229113735fc7e" uuid = "cd3eb016-35fb-5094-929b-558a96fad6f3" -version = "1.10.19" +version = "1.11.0" [[deps.HarfBuzz_jll]] deps = ["Artifacts", "Cairo_jll", "Fontconfig_jll", "FreeType2_jll", "Glib_jll", "Graphite2_jll", "JLLWrappers", "Libdl", "Libffi_jll"] @@ -432,11 +483,10 @@ git-tree-sha1 = "d1b1b796e47d94588b3757fe84fbf65a5ec4a80d" uuid = "d25df0c9-e2be-5dd7-82c8-3ad0b3e990b9" version = "0.1.5" -[[deps.IntelOpenMP_jll]] -deps = ["Artifacts", "JLLWrappers", "LazyArtifacts", "Libdl"] -git-tree-sha1 = "ec1debd61c300961f98064cfb21287613ad7f303" -uuid = "1d5cc7b8-4909-519e-a0f8-d0f5ad9712d0" -version = "2025.2.0+0" +[[deps.IntegerMathUtils]] +git-tree-sha1 = "4c1acff2dc6b6967e7e750633c50bc3b8d83e617" +uuid = "18e54dd8-cb9d-406c-a71d-865a43cbb235" +version = "0.1.3" [[deps.InteractiveUtils]] deps = ["Markdown"] @@ -445,9 +495,9 @@ version = "1.11.0" [[deps.Interpolations]] deps = ["Adapt", "AxisAlgorithms", "ChainRulesCore", "LinearAlgebra", "OffsetArrays", "Random", "Ratios", "SharedArrays", "SparseArrays", "StaticArrays", "WoodburyMatrices"] -git-tree-sha1 = "65d505fa4c0d7072990d659ef3fc086eb6da8208" +git-tree-sha1 = "48922d06068130f87e43edef52382e6a94305ae6" uuid = "a98d9a8b-a2ab-59e6-89dd-64a1c18fca59" -version = "0.16.2" +version = "0.16.3" [deps.Interpolations.extensions] InterpolationsForwardDiffExt = "ForwardDiff" @@ -475,9 +525,9 @@ version = "0.1.11" [[deps.JLLWrappers]] deps = ["Artifacts", "Preferences"] -git-tree-sha1 = "0533e564aae234aff59ab625543145446d8b6ec2" +git-tree-sha1 = "7204148362dafe5fe6a273f855b8ccbe4df8173e" uuid = "692b3bcd-3c85-4b1f-b108-f13ce0eb3210" -version = "1.7.1" +version = "1.8.0" [[deps.JSON]] deps = ["Dates", "Mmap", "Parsers", "Unicode"] @@ -487,20 +537,36 @@ version = "0.21.4" [[deps.JpegTurbo_jll]] deps = ["Artifacts", "JLLWrappers", "Libdl"] -git-tree-sha1 = "4255f0032eafd6451d707a51d5f0248b8a165e4d" +git-tree-sha1 = "c0c9b76f3520863909825cbecdef58cd63de705a" uuid = "aacddb02-875f-59d6-b918-886e6ef4fbf8" -version = "3.1.3+0" +version = "3.1.5+0" [[deps.JuliaSyntaxHighlighting]] deps = ["StyledStrings"] uuid = "ac6e5ff7-fb65-4e79-a425-ec3bc9c03011" version = "1.12.0" +[[deps.KernelAbstractions]] +deps = ["Adapt", "Atomix", "InteractiveUtils", "MacroTools", "PrecompileTools", "Requires", "StaticArrays", "UUIDs"] +git-tree-sha1 = "f2e76d3ced51a2a9e185abc0b97494c7273f649f" +uuid = "63c18a36-062a-441e-b654-da1e3ab1ce7c" +version = "0.9.41" + + [deps.KernelAbstractions.extensions] + EnzymeExt = "EnzymeCore" + LinearAlgebraExt = "LinearAlgebra" + SparseArraysExt = "SparseArrays" + + [deps.KernelAbstractions.weakdeps] + EnzymeCore = "f151be2c-9106-41f4-ab19-57ee4f262869" + LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e" + SparseArrays = "2f01184e-e22b-5df5-ae63-d93ebab69eaf" + [[deps.KernelDensity]] -deps = ["Distributions", "DocStringExtensions", "FFTW", "Interpolations", "StatsBase"] -git-tree-sha1 = "ba51324b894edaf1df3ab16e2cc6bc3280a2f1a7" +deps = ["Distributions", "DocStringExtensions", "FFTA", "Interpolations", "StatsBase"] +git-tree-sha1 = "9eda8292dd3268b3b7ec9df21bbfac24e177ec52" uuid = "5ab0869b-81aa-558d-bb23-cbf5423bbe9b" -version = "0.6.10" +version = "0.6.12" [[deps.LAME_jll]] deps = ["Artifacts", "JLLWrappers", "Libdl"] @@ -510,9 +576,9 @@ version = "3.100.3+0" [[deps.LERC_jll]] deps = ["Artifacts", "JLLWrappers", "Libdl"] -git-tree-sha1 = "aaafe88dccbd957a8d82f7d05be9b69172e0cee3" +git-tree-sha1 = "17b94ecafcfa45e8360a4fc9ca6b583b049e4e37" uuid = "88015f11-f218-50d7-93a8-a6af411a945d" -version = "4.0.1+0" +version = "4.1.0+0" [[deps.LLVMOpenMP_jll]] deps = ["Artifacts", "JLLWrappers", "Libdl"] @@ -520,12 +586,6 @@ git-tree-sha1 = "eb62a3deb62fc6d8822c0c4bef73e4412419c5d8" uuid = "1d63c593-3942-5779-bab2-d838dc0a180e" version = "18.1.8+0" -[[deps.LZO_jll]] -deps = ["Artifacts", "JLLWrappers", "Libdl"] -git-tree-sha1 = "1c602b1127f4751facb671441ca72715cc95938a" -uuid = "dd4b983a-f0e5-5f8d-a1b7-129d4a5fb1ac" -version = "2.10.3+0" - [[deps.LaTeXStrings]] git-tree-sha1 = "dda21b8cbd6a6c40d9d02a73230f9d70fed6918c" uuid = "b964fa9f-0449-5b57-a5c2-d3ea65f4040f" @@ -549,11 +609,6 @@ version = "0.16.10" SymEngine = "123dc426-2d89-5057-bbad-38513e3affd8" tectonic_jll = "d7dd28d6-a5e6-559c-9131-7eb760cdacc5" -[[deps.LazyArtifacts]] -deps = ["Artifacts", "Pkg"] -uuid = "4af54fe1-eca0-43a8-85a7-787d91b784e3" -version = "1.11.0" - [[deps.LibCURL]] deps = ["LibCURL_jll", "MozillaCACerts_jll"] uuid = "b27032c2-a3e7-50c8-80cd-2d36dbcbfd21" @@ -603,9 +658,9 @@ version = "1.18.0+0" [[deps.Libmount_jll]] deps = ["Artifacts", "JLLWrappers", "Libdl"] -git-tree-sha1 = "3acf07f130a76f87c041cfb2ff7d7284ca67b072" +git-tree-sha1 = "cc3ad4faf30015a3e8094c9b5b7f19e85bdf2386" uuid = "4b2f31a3-9ecc-558c-b454-b3730dcb73e9" -version = "2.41.2+0" +version = "2.42.0+0" [[deps.Libtiff_jll]] deps = ["Artifacts", "JLLWrappers", "JpegTurbo_jll", "LERC_jll", "Libdl", "XZ_jll", "Zlib_jll", "Zstd_jll"] @@ -615,9 +670,9 @@ version = "4.7.2+0" [[deps.Libuuid_jll]] deps = ["Artifacts", "JLLWrappers", "Libdl"] -git-tree-sha1 = "2a7a12fc0a4e7fb773450d17975322aa77142106" +git-tree-sha1 = "d620582b1f0cbe2c72dd1d5bd195a9ce73370ab1" uuid = "38a345b3-de98-5d2b-a5d3-14cd9215e700" -version = "2.41.2+0" +version = "2.42.0+0" [[deps.LinearAlgebra]] deps = ["Libdl", "OpenBLAS_jll", "libblastrampoline_jll"] @@ -626,9 +681,9 @@ version = "1.12.0" [[deps.LogExpFunctions]] deps = ["DocStringExtensions", "IrrationalConstants", "LinearAlgebra"] -git-tree-sha1 = "13ca9e2586b89836fd20cccf56e57e2b9ae7f38f" +git-tree-sha1 = "bba2d9aa057d8f126415de240573e86a8f39d2a1" uuid = "2ab3a3ac-af41-5b50-aa03-7779005ae688" -version = "0.3.29" +version = "1.0.1" [deps.LogExpFunctions.extensions] LogExpFunctionsChainRulesCoreExt = "ChainRulesCore" @@ -650,12 +705,6 @@ git-tree-sha1 = "f00544d95982ea270145636c181ceda21c4e2575" uuid = "e6f89c97-d47a-5376-807f-9c37f3926c36" version = "1.2.0" -[[deps.MKL_jll]] -deps = ["Artifacts", "IntelOpenMP_jll", "JLLWrappers", "LazyArtifacts", "Libdl", "oneTBB_jll"] -git-tree-sha1 = "282cadc186e7b2ae0eeadbd7a4dffed4196ae2aa" -uuid = "856f044c-d86e-5d09-b602-aeab76dc8ba7" -version = "2025.2.0+0" - [[deps.MacroTools]] git-tree-sha1 = "1e0228a030642014fe5cfe68c2c0a818f9e3f522" uuid = "1914dd2f-81c6-5fcd-8719-6d5c9610ff09" @@ -668,15 +717,15 @@ version = "1.11.0" [[deps.MbedTLS]] deps = ["Dates", "MbedTLS_jll", "MozillaCACerts_jll", "NetworkOptions", "Random", "Sockets"] -git-tree-sha1 = "c067a280ddc25f196b5e7df3877c6b226d390aaf" +git-tree-sha1 = "8785729fa736197687541f7053f6d8ab7fc44f92" uuid = "739be429-bea8-5141-9913-cc70e7f3736d" -version = "1.1.9" +version = "1.1.10" [[deps.MbedTLS_jll]] deps = ["Artifacts", "JLLWrappers", "Libdl"] -git-tree-sha1 = "3cce3511ca2c6f87b19c34ffc623417ed2798cbd" +git-tree-sha1 = "ff69a2b1330bcb730b9ac1ab7dd680176f5896b8" uuid = "c8ffd9c3-330d-5841-b78e-0817d7145fa1" -version = "2.28.10+0" +version = "2.28.1010+0" [[deps.Measures]] git-tree-sha1 = "b513cedd20d9c914783d8ad83d08120702bf2c77" @@ -697,23 +746,28 @@ version = "1.11.0" uuid = "14a3606d-f60d-562e-9121-12d972cd8159" version = "2025.5.20" +[[deps.MuladdMacro]] +git-tree-sha1 = "cac9cc5499c25554cba55cd3c30543cff5ca4fab" +uuid = "46d2c3a1-f734-5fdb-9937-b9b9aeba4221" +version = "0.2.4" + [[deps.MultivariateStats]] deps = ["Arpack", "Distributions", "LinearAlgebra", "SparseArrays", "Statistics", "StatsAPI", "StatsBase"] -git-tree-sha1 = "816620e3aac93e5b5359e4fdaf23ca4525b00ddf" +git-tree-sha1 = "7c3ff68a904d0f7404e5d2f7f5bc667934d8d616" uuid = "6f286f6a-111f-5878-ab1e-185364afe411" -version = "0.10.3" +version = "0.10.4" [[deps.NaNMath]] deps = ["OpenLibm_jll"] -git-tree-sha1 = "9b8215b1ee9e78a293f99797cd31375471b2bcae" +git-tree-sha1 = "dbd2e8cd2c1c27f0b584f6661b4309609c5a685e" uuid = "77ba4419-2d1f-58cd-9bb1-8ffee604a2e3" -version = "1.1.3" +version = "1.1.4" [[deps.NearestNeighbors]] -deps = ["Distances", "StaticArrays"] -git-tree-sha1 = "ca7e18198a166a1f3eb92a3650d53d94ed8ca8a1" +deps = ["AbstractTrees", "Distances", "StaticArrays"] +git-tree-sha1 = "e2c3bba08dd6dedfe17a17889131b885b8c082f0" uuid = "b8a86587-4115-5ab1-83bc-aa920d37bbce" -version = "0.4.22" +version = "0.4.27" [[deps.NetworkOptions]] uuid = "ca575930-c2e3-43a9-ace4-1e988b2c1908" @@ -751,9 +805,9 @@ version = "0.8.7+0" [[deps.OpenSSL]] deps = ["BitFlags", "Dates", "MozillaCACerts_jll", "NetworkOptions", "OpenSSL_jll", "Sockets"] -git-tree-sha1 = "386b47442468acfb1add94bf2d85365dea10cbab" +git-tree-sha1 = "1d1aaa7d449b58415f97d2839c318b70ffb525a0" uuid = "4d8831e6-92b7-49fb-bdf8-b643e874388c" -version = "1.6.0" +version = "1.6.1" [[deps.OpenSSL_jll]] deps = ["Artifacts", "Libdl"] @@ -768,14 +822,14 @@ version = "0.5.6+0" [[deps.Opus_jll]] deps = ["Artifacts", "JLLWrappers", "Libdl"] -git-tree-sha1 = "c392fc5dd032381919e3b22dd32d6443760ce7ea" +git-tree-sha1 = "e2bb57a313a74b8104064b7efd01406c0a50d2ff" uuid = "91d4177d-7536-5919-b921-800302f37372" -version = "1.5.2+0" +version = "1.6.1+0" [[deps.OrderedCollections]] -git-tree-sha1 = "05868e21324cede2207c6f0f466b4bfef6d5e7ee" +git-tree-sha1 = "94ba93778373a53bfd5a0caaf7d809c445292ff4" uuid = "bac558e1-5e72-5ebc-8fee-abe8a469f55d" -version = "1.8.1" +version = "1.8.2" [[deps.PCRE2_jll]] deps = ["Artifacts", "Libdl"] @@ -784,9 +838,9 @@ version = "10.44.0+1" [[deps.PDMats]] deps = ["LinearAlgebra", "SparseArrays", "SuiteSparse"] -git-tree-sha1 = "d922b4d80d1e12c658da7785e754f4796cc1d60d" +git-tree-sha1 = "e4cff168707d441cd6bf3ff7e4832bdf34278e4a" uuid = "90014a1f-27ba-587c-ab20-58faa44d9150" -version = "0.11.36" +version = "0.11.37" weakdeps = ["StatsBase"] [deps.PDMats.extensions] @@ -794,9 +848,9 @@ weakdeps = ["StatsBase"] [[deps.Pango_jll]] deps = ["Artifacts", "Cairo_jll", "Fontconfig_jll", "FreeType2_jll", "FriBidi_jll", "Glib_jll", "HarfBuzz_jll", "JLLWrappers", "Libdl"] -git-tree-sha1 = "1f7f9bbd5f7a2e5a9f7d96e51c9754454ea7f60b" +git-tree-sha1 = "58e5ed5e386e156bd93e86b305ebd21ac63d2d04" uuid = "36c8627f-9965-5494-a995-c6b170f724f3" -version = "1.56.4+0" +version = "1.57.1+0" [[deps.ParserCombinator]] deps = ["AutoHashEquals", "Printf"] @@ -806,21 +860,27 @@ version = "2.2.1" [[deps.Parsers]] deps = ["Dates", "PrecompileTools", "UUIDs"] -git-tree-sha1 = "7d2f8f21da5db6a806faf7b9b292296da42b2810" +git-tree-sha1 = "468dbe2b510c876dc091b2c74ed52c7c34f48b9b" uuid = "69de0a69-1ddd-5017-9359-2bf0b02dc9f0" -version = "2.8.3" +version = "2.8.5" [[deps.PauliPropagation]] -deps = ["BitIntegers", "Bits", "JSON", "LinearAlgebra", "PlotGraphviz", "Random", "StatsBase", "Test", "UUIDs"] -git-tree-sha1 = "f97568ff3acf59bbcfb2b918febad483ca974fcb" +deps = ["AcceleratedKernels", "BitIntegers", "Bits", "JSON", "LinearAlgebra", "PlotGraphviz", "ProfileCanvas", "Random", "StatsBase", "Test", "UUIDs"] +git-tree-sha1 = "757b43af3c247d9fad953dd056d3df76fe6e6a08" uuid = "293282d5-3c99-4fb6-92d0-fd3280a19750" -version = "0.5.1" +version = "0.7.3" + + [deps.PauliPropagation.extensions] + PauliPropagationCUDA = "CUDA" + + [deps.PauliPropagation.weakdeps] + CUDA = "052768ef-5323-5732-b1bb-66c8b64840ba" [[deps.Pixman_jll]] deps = ["Artifacts", "CompilerSupportLibraries_jll", "JLLWrappers", "LLVMOpenMP_jll", "Libdl"] -git-tree-sha1 = "db76b1ecd5e9715f3d043cec13b2ec93ce015d53" +git-tree-sha1 = "e4a6721aa89e62e5d4217c0b21bd714263779dda" uuid = "30392449-352a-5448-841d-b1acce4e97dc" -version = "0.44.2+0" +version = "0.46.4+0" [[deps.Pkg]] deps = ["Artifacts", "Dates", "Downloads", "FileWatching", "LibGit2", "Libdl", "Logging", "Markdown", "Printf", "Random", "SHA", "TOML", "Tar", "UUIDs", "p7zip_jll"] @@ -845,15 +905,15 @@ version = "3.3.0" [[deps.PlotUtils]] deps = ["ColorSchemes", "Colors", "Dates", "PrecompileTools", "Printf", "Random", "Reexport", "StableRNGs", "Statistics"] -git-tree-sha1 = "3ca9a356cd2e113c420f2c13bea19f8d3fb1cb18" +git-tree-sha1 = "26ca162858917496748aad52bb5d3be4d26a228a" uuid = "995b91a9-d308-5afd-9ec6-746e21dbc043" -version = "1.4.3" +version = "1.4.4" [[deps.Plots]] deps = ["Base64", "Contour", "Dates", "Downloads", "FFMPEG", "FixedPointNumbers", "GR", "JLFzf", "JSON", "LaTeXStrings", "Latexify", "LinearAlgebra", "Measures", "NaNMath", "Pkg", "PlotThemes", "PlotUtils", "PrecompileTools", "Printf", "REPL", "Random", "RecipesBase", "RecipesPipeline", "Reexport", "RelocatableFolders", "Requires", "Scratch", "Showoff", "SparseArrays", "Statistics", "StatsBase", "TOML", "UUIDs", "UnicodeFun", "Unzip"] -git-tree-sha1 = "12ce661880f8e309569074a61d3767e5756a199f" +git-tree-sha1 = "cb20a4eacda080e517e4deb9cfb6c7c518131265" uuid = "91a5bcdd-55d7-5caf-9e0b-520d859cae80" -version = "1.41.1" +version = "1.41.6" [deps.Plots.extensions] FileIOExt = "FileIO" @@ -871,15 +931,21 @@ version = "1.41.1" [[deps.PrecompileTools]] deps = ["Preferences"] -git-tree-sha1 = "07a921781cab75691315adc645096ed5e370cb77" +git-tree-sha1 = "edbeefc7a4889f528644251bdb5fc9ab5348bc2c" uuid = "aea7be01-6a6a-4083-8856-8a6e6704d82a" -version = "1.3.3" +version = "1.3.4" [[deps.Preferences]] deps = ["TOML"] -git-tree-sha1 = "0f27480397253da18fe2c12a4ba4eb9eb208bf3d" +git-tree-sha1 = "8b770b60760d4451834fe79dd483e318eee709c4" uuid = "21216c6a-2e73-6563-6e65-726566657250" -version = "1.5.0" +version = "1.5.2" + +[[deps.Primes]] +deps = ["IntegerMathUtils"] +git-tree-sha1 = "25cdd1d20cd005b52fc12cb6be3f75faaf59bb9b" +uuid = "27ebfcd6-29c5-5fa9-bf4b-fb8fc14df3ae" +version = "0.5.7" [[deps.Printf]] deps = ["Unicode"] @@ -891,40 +957,52 @@ deps = ["StyledStrings"] uuid = "9abbd945-dff8-562f-b5e8-e1ebf5ef1b79" version = "1.11.0" +[[deps.ProfileCanvas]] +deps = ["Base64", "JSON", "Pkg", "Profile", "REPL"] +git-tree-sha1 = "990016fb1508b0726a70039f39569720d054c78d" +uuid = "efd6af41-a80b-495e-886c-e51b0c7d77a3" +version = "0.1.7" + [[deps.PtrArrays]] -git-tree-sha1 = "1d36ef11a9aaf1e8b74dacc6a731dd1de8fd493d" +git-tree-sha1 = "4fbbafbc6251b883f4d2705356f3641f3652a7fe" uuid = "43287f4e-b6f4-7ad1-bb20-aadabca52c3d" -version = "1.3.0" +version = "1.4.0" [[deps.Qt6Base_jll]] deps = ["Artifacts", "CompilerSupportLibraries_jll", "Fontconfig_jll", "Glib_jll", "JLLWrappers", "Libdl", "Libglvnd_jll", "OpenSSL_jll", "Vulkan_Loader_jll", "Xorg_libSM_jll", "Xorg_libXext_jll", "Xorg_libXrender_jll", "Xorg_libxcb_jll", "Xorg_xcb_util_cursor_jll", "Xorg_xcb_util_image_jll", "Xorg_xcb_util_keysyms_jll", "Xorg_xcb_util_renderutil_jll", "Xorg_xcb_util_wm_jll", "Zlib_jll", "libinput_jll", "xkbcommon_jll"] -git-tree-sha1 = "34f7e5d2861083ec7596af8b8c092531facf2192" +git-tree-sha1 = "144895f6166994730ee7ff8113b981fc360638f1" uuid = "c0090381-4147-56d7-9ebc-da0b1113ec56" -version = "6.8.2+2" +version = "6.10.2+2" [[deps.Qt6Declarative_jll]] -deps = ["Artifacts", "JLLWrappers", "Libdl", "Qt6Base_jll", "Qt6ShaderTools_jll"] -git-tree-sha1 = "da7adf145cce0d44e892626e647f9dcbe9cb3e10" +deps = ["Artifacts", "JLLWrappers", "Libdl", "Qt6Base_jll", "Qt6ShaderTools_jll", "Qt6Svg_jll"] +git-tree-sha1 = "d5b7dd0e226774cbd87e2790e34def09245c7eab" uuid = "629bc702-f1f5-5709-abd5-49b8460ea067" -version = "6.8.2+1" +version = "6.10.2+1" [[deps.Qt6ShaderTools_jll]] deps = ["Artifacts", "JLLWrappers", "Libdl", "Qt6Base_jll"] -git-tree-sha1 = "9eca9fc3fe515d619ce004c83c31ffd3f85c7ccf" +git-tree-sha1 = "4d85eedf69d875982c46643f6b4f66919d7e157b" uuid = "ce943373-25bb-56aa-8eca-768745ed7b5a" -version = "6.8.2+1" +version = "6.10.2+1" + +[[deps.Qt6Svg_jll]] +deps = ["Artifacts", "JLLWrappers", "Libdl", "Qt6Base_jll"] +git-tree-sha1 = "81587ff5ff25a4e1115ce191e36285ede0334c9d" +uuid = "6de9746b-f93d-5813-b365-ba18ad4a9cf3" +version = "6.10.2+0" [[deps.Qt6Wayland_jll]] deps = ["Artifacts", "JLLWrappers", "Libdl", "Qt6Base_jll", "Qt6Declarative_jll"] -git-tree-sha1 = "8f528b0851b5b7025032818eb5abbeb8a736f853" +git-tree-sha1 = "672c938b4b4e3e0169a07a5f227029d4905456f2" uuid = "e99dba38-086e-5de3-a5b1-6e4c66e897c3" -version = "6.8.2+2" +version = "6.10.2+1" [[deps.QuadGK]] deps = ["DataStructures", "LinearAlgebra"] -git-tree-sha1 = "9da16da70037ba9d701192e27befedefb91ec284" +git-tree-sha1 = "5e8e8b0ab68215d7a2b14b9921a946fee794749e" uuid = "1fd47b50-473d-5c70-9696-f719f8f3bcdc" -version = "2.11.2" +version = "2.11.3" [deps.QuadGK.extensions] QuadGKEnzymeExt = "Enzyme" @@ -1005,9 +1083,9 @@ version = "1.3.0" [[deps.SentinelArrays]] deps = ["Dates", "Random"] -git-tree-sha1 = "712fb0231ee6f9120e005ccd56297abbc053e7e0" +git-tree-sha1 = "084c47c7c5ce5cfecefa0a98dff69eb3646b5a80" uuid = "91c51154-3ec4-41a3-a24f-3f23e20d615c" -version = "1.4.8" +version = "1.4.10" [[deps.Serialization]] uuid = "9e88b42a-f829-5b0c-bbe9-9e923198166b" @@ -1036,15 +1114,15 @@ version = "1.2.0" [[deps.SimpleTraits]] deps = ["InteractiveUtils", "MacroTools"] -git-tree-sha1 = "be8eeac05ec97d379347584fa9fe2f5f76795bcb" +git-tree-sha1 = "7ddb0b49c109481b046972c0e4ab02b2127d6a75" uuid = "699a6c99-e7fa-54fc-8d76-47d257e15c1d" -version = "0.9.5" +version = "0.9.6" [[deps.SimpleWeightedGraphs]] deps = ["Graphs", "LinearAlgebra", "Markdown", "SparseArrays"] -git-tree-sha1 = "3e5f165e58b18204aed03158664c4982d691f454" +git-tree-sha1 = "749a2b719ec7f34f280c0d97ac3dab5c89818631" uuid = "47aef6b3-ad0c-573a-a1e2-d07658019622" -version = "1.5.0" +version = "1.5.1" [[deps.Sockets]] uuid = "6462fe0b-24de-5631-8697-dd941f90decc" @@ -1063,9 +1141,9 @@ version = "1.12.0" [[deps.SpecialFunctions]] deps = ["IrrationalConstants", "LogExpFunctions", "OpenLibm_jll", "OpenSpecFun_jll"] -git-tree-sha1 = "f2685b435df2613e25fc10ad8c26dddb8640f547" +git-tree-sha1 = "6547cbdd8ce32efba0d21c5a40fa96d1a3548f9f" uuid = "276daf66-3868-5448-9aa4-cd146d93841b" -version = "2.6.1" +version = "2.8.0" weakdeps = ["ChainRulesCore"] [deps.SpecialFunctions.extensions] @@ -1073,15 +1151,15 @@ weakdeps = ["ChainRulesCore"] [[deps.StableRNGs]] deps = ["Random"] -git-tree-sha1 = "95af145932c2ed859b63329952ce8d633719f091" +git-tree-sha1 = "4f96c596b8c8258cc7d3b19797854d368f243ddc" uuid = "860ef19b-820b-49d6-a774-d7a799459cd3" -version = "1.0.3" +version = "1.0.4" [[deps.StaticArrays]] deps = ["LinearAlgebra", "PrecompileTools", "Random", "StaticArraysCore"] -git-tree-sha1 = "b8693004b385c842357406e3af647701fe783f98" +git-tree-sha1 = "246a8bb2e6667f832eea063c3a56aef96429a3db" uuid = "90137ffa-7385-5640-81b9-e52037218182" -version = "1.9.15" +version = "1.9.18" weakdeps = ["ChainRulesCore", "Statistics"] [deps.StaticArrays.extensions] @@ -1105,21 +1183,21 @@ weakdeps = ["SparseArrays"] [[deps.StatsAPI]] deps = ["LinearAlgebra"] -git-tree-sha1 = "9d72a13a3f4dd3795a195ac5a44d7d6ff5f552ff" +git-tree-sha1 = "178ed29fd5b2a2cfc3bd31c13375ae925623ff36" uuid = "82ae8749-77ed-4fe6-ae5f-f523153014b0" -version = "1.7.1" +version = "1.8.0" [[deps.StatsBase]] -deps = ["AliasTables", "DataAPI", "DataStructures", "LinearAlgebra", "LogExpFunctions", "Missings", "Printf", "Random", "SortingAlgorithms", "SparseArrays", "Statistics", "StatsAPI"] -git-tree-sha1 = "a136f98cefaf3e2924a66bd75173d1c891ab7453" +deps = ["AliasTables", "DataAPI", "DataStructures", "IrrationalConstants", "LinearAlgebra", "LogExpFunctions", "Missings", "Printf", "Random", "SortingAlgorithms", "SparseArrays", "Statistics", "StatsAPI"] +git-tree-sha1 = "c6f18e5a52a176a383f6f6c635e0f81feed1d6d4" uuid = "2913bbd2-ae8a-5f71-8c99-4fb6c76f3a91" -version = "0.34.7" +version = "0.34.11" [[deps.StatsFuns]] deps = ["HypergeometricFunctions", "IrrationalConstants", "LogExpFunctions", "Reexport", "Rmath", "SpecialFunctions"] -git-tree-sha1 = "91f091a8716a6bb38417a6e6f274602a19aaa685" +git-tree-sha1 = "3f4e1d24289cd974e089c617b1472311a2b1feab" uuid = "4c63d2b9-4356-54db-8cca-17b64c39e42c" -version = "1.5.2" +version = "2.1.0" [deps.StatsFuns.extensions] StatsFunsChainRulesCoreExt = "ChainRulesCore" @@ -1212,6 +1290,17 @@ git-tree-sha1 = "53915e50200959667e78a92a418594b428dffddf" uuid = "1cfade01-22cf-5700-b092-accc4b62d6e1" version = "0.4.1" +[[deps.UnsafeAtomics]] +git-tree-sha1 = "0f30765c32d66d58e41f4cb5624d4fc8a82ec13b" +uuid = "013be700-e6cd-48c3-b4a1-df204f14c38f" +version = "0.3.1" + + [deps.UnsafeAtomics.extensions] + UnsafeAtomicsLLVM = ["LLVM"] + + [deps.UnsafeAtomics.weakdeps] + LLVM = "929cbde3-209d-540e-8aea-75f648917ca0" + [[deps.Unzip]] git-tree-sha1 = "ca0969166a028236229f63514992fc073799bb78" uuid = "41fe7b60-77ed-43a1-b4f0-825fd5a5650d" @@ -1237,15 +1326,15 @@ version = "0.6.7" [[deps.WoodburyMatrices]] deps = ["LinearAlgebra", "SparseArrays"] -git-tree-sha1 = "c1a7aa6219628fcd757dede0ca95e245c5cd9511" +git-tree-sha1 = "248a7031b3da79a127f14e5dc5f417e26f9f6db7" uuid = "efce3f68-66dc-5838-9240-27a6d6f5f9b6" -version = "1.0.0" +version = "1.1.0" [[deps.XZ_jll]] deps = ["Artifacts", "JLLWrappers", "Libdl"] -git-tree-sha1 = "fee71455b0aaa3440dfdd54a9a36ccef829be7d4" +git-tree-sha1 = "b29c22e245d092b8b4e8d3c09ad7baa586d9f573" uuid = "ffd25f8a-64ca-5728-b0f7-c24cf3aae800" -version = "5.8.1+0" +version = "5.8.3+0" [[deps.Xorg_libICE_jll]] deps = ["Artifacts", "JLLWrappers", "Libdl"] @@ -1261,9 +1350,9 @@ version = "1.2.6+0" [[deps.Xorg_libX11_jll]] deps = ["Artifacts", "JLLWrappers", "Libdl", "Xorg_libxcb_jll", "Xorg_xtrans_jll"] -git-tree-sha1 = "b5899b25d17bf1889d25906fb9deed5da0c15b3b" +git-tree-sha1 = "808090ede1d41644447dd5cbafced4731c56bd2f" uuid = "4f6342f7-b3d2-589e-9d20-edeb45f2b2bc" -version = "1.8.12+0" +version = "1.8.13+0" [[deps.Xorg_libXau_jll]] deps = ["Artifacts", "JLLWrappers", "Libdl"] @@ -1285,9 +1374,9 @@ version = "1.1.6+0" [[deps.Xorg_libXext_jll]] deps = ["Artifacts", "JLLWrappers", "Libdl", "Xorg_libX11_jll"] -git-tree-sha1 = "a4c0ee07ad36bf8bbce1c3bb52d21fb1e0b987fb" +git-tree-sha1 = "1a4a26870bf1e5d26cd585e38038d399d7e65706" uuid = "1082639a-0dae-5f34-9b06-72781eeb8cb3" -version = "1.3.7+0" +version = "1.3.8+0" [[deps.Xorg_libXfixes_jll]] deps = ["Artifacts", "JLLWrappers", "Libdl", "Xorg_libX11_jll"] @@ -1303,15 +1392,15 @@ version = "1.8.3+0" [[deps.Xorg_libXinerama_jll]] deps = ["Artifacts", "JLLWrappers", "Libdl", "Xorg_libXext_jll"] -git-tree-sha1 = "a5bc75478d323358a90dc36766f3c99ba7feb024" +git-tree-sha1 = "0ba01bc7396896a4ace8aab67db31403c71628f4" uuid = "d1454406-59df-5ea1-beac-c340f2130bc3" -version = "1.1.6+0" +version = "1.1.7+0" [[deps.Xorg_libXrandr_jll]] deps = ["Artifacts", "JLLWrappers", "Libdl", "Xorg_libXext_jll", "Xorg_libXrender_jll"] -git-tree-sha1 = "aff463c82a773cb86061bce8d53a0d976854923e" +git-tree-sha1 = "6c174ef70c96c76f4c3f4d3cfbe09d018bcd1b53" uuid = "ec84b674-ba8e-5d96-8ba1-2a689ba10484" -version = "1.5.5+0" +version = "1.5.6+0" [[deps.Xorg_libXrender_jll]] deps = ["Artifacts", "JLLWrappers", "Libdl", "Xorg_libX11_jll"] @@ -1319,6 +1408,12 @@ git-tree-sha1 = "7ed9347888fac59a618302ee38216dd0379c480d" uuid = "ea2f1a96-1ddc-540d-b46f-429655e07cfa" version = "0.9.12+0" +[[deps.Xorg_libpciaccess_jll]] +deps = ["Artifacts", "JLLWrappers", "Libdl", "Zlib_jll"] +git-tree-sha1 = "58972370b81423fc546c56a60ed1a009450177c3" +uuid = "a65dc6b1-eb27-53a1-bb3e-dea574b5389e" +version = "0.19.0+0" + [[deps.Xorg_libxcb_jll]] deps = ["Artifacts", "JLLWrappers", "Libdl", "Xorg_libXau_jll", "Xorg_libXdmcp_jll"] git-tree-sha1 = "bfcaf7ec088eaba362093393fe11aa141fa15422" @@ -1327,9 +1422,9 @@ version = "1.17.1+0" [[deps.Xorg_libxkbfile_jll]] deps = ["Artifacts", "JLLWrappers", "Libdl", "Xorg_libX11_jll"] -git-tree-sha1 = "e3150c7400c41e207012b41659591f083f3ef795" +git-tree-sha1 = "ed756a03e95fff88d8f738ebc2849431bdd4fd1a" uuid = "cc61e674-0454-545c-8b26-ed2c68acab7a" -version = "1.1.3+0" +version = "1.2.0+0" [[deps.Xorg_xcb_util_cursor_jll]] deps = ["Artifacts", "JLLWrappers", "Libdl", "Xorg_xcb_util_image_jll", "Xorg_xcb_util_jll", "Xorg_xcb_util_renderutil_jll"] @@ -1375,9 +1470,9 @@ version = "1.4.7+0" [[deps.Xorg_xkeyboard_config_jll]] deps = ["Artifacts", "JLLWrappers", "Libdl", "Xorg_xkbcomp_jll"] -git-tree-sha1 = "00af7ebdc563c9217ecc67776d1bbf037dbcebf4" +git-tree-sha1 = "ed349d26affcacafbc7fc2941ace1fb98f71e715" uuid = "33bec58e-1273-512f-9401-5d533626f822" -version = "2.44.0+0" +version = "2.47.0+1" [[deps.Xorg_xtrans_jll]] deps = ["Artifacts", "JLLWrappers", "Libdl"] @@ -1410,9 +1505,9 @@ version = "0.61.1+0" [[deps.libaom_jll]] deps = ["Artifacts", "JLLWrappers", "Libdl"] -git-tree-sha1 = "371cc681c00a3ccc3fbc5c0fb91f58ba9bec1ecf" +git-tree-sha1 = "850b06095ee71f0135d644ffd8a52850699581ed" uuid = "a4ae2306-e953-59d6-aa16-d00cac43593b" -version = "3.13.1+0" +version = "3.13.3+0" [[deps.libass_jll]] deps = ["Artifacts", "Bzip2_jll", "FreeType2_jll", "FriBidi_jll", "HarfBuzz_jll", "JLLWrappers", "Libdl", "Zlib_jll"] @@ -1431,6 +1526,12 @@ git-tree-sha1 = "9bf7903af251d2050b467f76bdbe57ce541f7f4f" uuid = "1183f4f0-6f2a-5f1a-908b-139f9cdfea6f" version = "0.2.2+0" +[[deps.libdrm_jll]] +deps = ["Artifacts", "JLLWrappers", "Libdl", "Xorg_libpciaccess_jll"] +git-tree-sha1 = "63aac0bcb0b582e11bad965cef4a689905456c03" +uuid = "8e53e030-5e6c-5a89-a30b-be5b7263a166" +version = "2.4.125+1" + [[deps.libevdev_jll]] deps = ["Artifacts", "JLLWrappers", "Libdl"] git-tree-sha1 = "56d643b57b188d30cccc25e331d416d3d358e557" @@ -1451,9 +1552,15 @@ version = "1.28.1+0" [[deps.libpng_jll]] deps = ["Artifacts", "JLLWrappers", "Libdl", "Zlib_jll"] -git-tree-sha1 = "07b6a107d926093898e82b3b1db657ebe33134ec" +git-tree-sha1 = "e51150d5ab85cee6fc36726850f0e627ad2e4aba" uuid = "b53b4c65-9356-5827-b1ea-8c7a1a84506f" -version = "1.6.50+0" +version = "1.6.58+0" + +[[deps.libva_jll]] +deps = ["Artifacts", "JLLWrappers", "Libdl", "Xorg_libX11_jll", "Xorg_libXext_jll", "Xorg_libXfixes_jll", "libdrm_jll"] +git-tree-sha1 = "7dbf96baae3310fe2fa0df0ccbb3c6288d5816c9" +uuid = "9a156e7d-b971-5f62-b2c9-67348b8fb97c" +version = "2.23.0+0" [[deps.libvorbis_jll]] deps = ["Artifacts", "JLLWrappers", "Libdl", "Ogg_jll"] @@ -1472,12 +1579,6 @@ deps = ["Artifacts", "Libdl"] uuid = "8e850ede-7688-5339-a07c-302acd2aaf8d" version = "1.64.0+1" -[[deps.oneTBB_jll]] -deps = ["Artifacts", "JLLWrappers", "LazyArtifacts", "Libdl"] -git-tree-sha1 = "1350188a69a6e46f799d3945beef36435ed7262f" -uuid = "1317d2d5-d96f-522e-a858-c73665f53c3e" -version = "2022.0.0+1" - [[deps.p7zip_jll]] deps = ["Artifacts", "Libdl"] uuid = "3f19e933-33d8-53b3-aaab-bd5110c3b7a0" @@ -1497,6 +1598,6 @@ version = "4.1.0+0" [[deps.xkbcommon_jll]] deps = ["Artifacts", "JLLWrappers", "Libdl", "Xorg_libxcb_jll", "Xorg_xkeyboard_config_jll"] -git-tree-sha1 = "fbf139bce07a534df0e699dbb5f5cc9346f95cc1" +git-tree-sha1 = "a1fc6507a40bf504527d0d4067d718f8e179b2b8" uuid = "d8fb68d0-12a3-5cfd-a85a-d49703b185fd" -version = "1.9.2+0" +version = "1.13.0+0" diff --git a/julia-benchmarks/benches/gates.jl b/julia-benchmarks/benches/gates.jl index 511444f72..20868a36e 100644 --- a/julia-benchmarks/benches/gates.jl +++ b/julia-benchmarks/benches/gates.jl @@ -49,13 +49,13 @@ function benchmark_suite() cnot = CliffordGate(:CNOT, [1, 2]) cz = CliffordGate(:CZ, [1, 2]) - rx = PauliRotation([:X], [1], 0.5) - ry = PauliRotation([:Y], [1], 0.5) - rz = PauliRotation([:Z], [1], 0.5) + rx = PauliRotation([:X], [2], 0.5) + ry = PauliRotation([:Y], [2], 0.5) + rz = PauliRotation([:Z], [2], 0.5) - rxx = PauliRotation([:X, :X], [1, 2], 0.5) - ryy = PauliRotation([:Y, :Y], [1, 2], 0.5) - rzz = PauliRotation([:Z, :Z], [1, 2], 0.5) + rxx = PauliRotation([:X, :X], [2, 3], 0.5) + ryy = PauliRotation([:Y, :Y], [2, 3], 0.5) + rzz = PauliRotation([:Z, :Z], [2, 3], 0.5) # collect the gate applications into the benchmark group group["x"] = @benchmarkable propagate!($x, state; min_abs_coeff = 1e-10) setup = (state = copy($initial_state); cache_state = copy($tmp_state)) diff --git a/julia-benchmarks/benches/random-circuit.jl b/julia-benchmarks/benches/random-circuit.jl index bf09eb63c..4ba50e76e 100644 --- a/julia-benchmarks/benches/random-circuit.jl +++ b/julia-benchmarks/benches/random-circuit.jl @@ -24,7 +24,10 @@ end function random_circuit(n, depth) circuit = Gate[] - # NOTE: inverse order since it propagation is done with reverse(circuit) + # NOTE: inverse order since propagation is done with reverse(circuit). + # The leading layer! is pushed first so it is applied last, matching the + # trailing layer in the Rust benchmark (layer, entangle per step, then layer). + layer!(circuit, n) for _ in 1:depth entangle!(circuit, n) layer!(circuit, n) @@ -35,8 +38,9 @@ end function run_circuit(circuit, state) - propagate!(circuit, state) - overlapwithzero(state) + # min_abs_coeff=0 disables truncation and no overlapwithzero, matching the + # Rust benchmark which never truncates and times propagation only. + propagate!(circuit, state; min_abs_coeff=0) end function run_benchmark(n, depth) diff --git a/julia-benchmarks/benches/trotter.jl b/julia-benchmarks/benches/trotter.jl index 0849311df..04afcf2bf 100644 --- a/julia-benchmarks/benches/trotter.jl +++ b/julia-benchmarks/benches/trotter.jl @@ -31,7 +31,9 @@ function trotter_circuit(n, total_time, dt, interaction_strength, external_field end - return circuit + # built in Schrödinger/forward order above; reverse so propagate!'s internal + # Heisenberg reverse() applies it forward, matching the Rust/Python benches. + return reverse(circuit) end function run_benchmark() diff --git a/julia-benchmarks/benches/truncation-weight.jl b/julia-benchmarks/benches/truncation-weight.jl new file mode 100644 index 000000000..a92f6ff5c --- /dev/null +++ b/julia-benchmarks/benches/truncation-weight.jl @@ -0,0 +1,122 @@ +# SPDX-FileCopyrightText: 2026 The PPVM Authors +# SPDX-License-Identifier: Apache-2.0 +# +# Mirror of crates/ppvm-runtime/benches/truncation-weight.rs. +# Measures PauliPropagation.jl's truncate! over the same parameter grid: +# - 3 term-weight profiles (3, 50, 120) +# - 4 weight cutoffs (10, 100, 1000, Inf) +# - 1000 terms on 128 qubits +# +# PP.jl's truncate! always builds a single closure combining min_abs_coeff +# and max_weight checks, then walks the dictionary once. To approximate the +# Rust "single-strategy" benches we set the other threshold to a sentinel +# value that never trips. + +using PauliPropagation +using BenchmarkTools + +const N_QUBITS = 128 +const N_TERMS = 1_000 +const COEFF_EPS = 1e-12 + +const PROFILES = [ + ("w3", 3), + ("w50", 50), + ("w120", 120), +] + +const CUTOFFS = [ + ("10", 10.0), + ("100", 100.0), + ("1000", 1000.0), + ("inf", Inf), +] + +const PAULI_SYMS = [:X, :Y, :Z] + +# Build N_TERMS PauliStrings each with exactly target_weight non-identity +# slots (clamped to N_QUBITS), spread by stride. Pauli choices depend on k +# so terms are mostly distinct. Matches make_terms() in the Rust mirror. +function make_psum(target_weight) + weight = min(target_weight, N_QUBITS) + stride = max(div(N_QUBITS, max(weight, 1)), 1) + psum = PauliSum(N_QUBITS) + for k in 0:(N_TERMS - 1) + positions = Int[] + symbols = Symbol[] + for w in 0:(weight - 1) + push!(positions, mod(k + w * stride, N_QUBITS) + 1) # 1-indexed + push!(symbols, PAULI_SYMS[mod(k * 31 + w, 3) + 1]) + end + coeff = 1.0 / (k + 1) + add!(psum, PauliString(N_QUBITS, symbols, positions, coeff)) + end + return psum +end + +function bench_max_weight_alone() + println("\n=== max-weight-only (min_abs_coeff = 0, never trips) ===") + results = Dict{String, Any}() + for (profile, weight) in PROFILES + psum = make_psum(weight) + println("[$profile] psum has $(length(psum)) terms") + for (cutoff_name, cutoff) in CUTOFFS + id = "$profile/cut-$cutoff_name" + t = @benchmark PauliPropagation.truncate!(state; + min_abs_coeff = 0.0, max_weight = $cutoff) setup = (state = deepcopy($psum)) samples=200 + results[id] = t + println(" $id: median = $(median(t).time) ns") + end + end + return results +end + +function bench_coeff_threshold_alone() + println("\n=== coeff-threshold-only (max_weight = Inf, never trips) ===") + results = Dict{String, Any}() + for (profile, weight) in PROFILES + psum = make_psum(weight) + id = profile + t = @benchmark PauliPropagation.truncate!(state; + min_abs_coeff = $COEFF_EPS, max_weight = Inf) setup = (state = deepcopy($psum)) samples=200 + results[id] = t + println(" $id: median = $(median(t).time) ns") + end + return results +end + +function bench_combined() + println("\n=== combined (both checks active, matches Rust CombinedStrategy) ===") + results = Dict{String, Any}() + for (profile, weight) in PROFILES + psum = make_psum(weight) + for (cutoff_name, cutoff) in CUTOFFS + id = "$profile/cut-$cutoff_name" + t = @benchmark PauliPropagation.truncate!(state; + min_abs_coeff = $COEFF_EPS, max_weight = $cutoff) setup = (state = deepcopy($psum)) samples=200 + results[id] = t + println(" $id: median = $(median(t).time) ns") + end + end + return results +end + +function bench_clone_baseline() + println("\n=== clone (deepcopy) baseline ===") + results = Dict{String, Any}() + for (profile, weight) in PROFILES + psum = make_psum(weight) + t = @benchmark deepcopy($psum) samples=200 + results[profile] = t + println(" $profile: median = $(median(t).time) ns") + end + return results +end + +println("Using $(Threads.nthreads()) threads") +println("N_QUBITS = $N_QUBITS, N_TERMS = $N_TERMS") + +bench_max_weight_alone() +bench_coeff_threshold_alone() +bench_combined() +bench_clone_baseline() diff --git a/julia-benchmarks/xy_ladder_msd.jl b/julia-benchmarks/xy_ladder_msd.jl new file mode 100644 index 000000000..87fd0042e --- /dev/null +++ b/julia-benchmarks/xy_ladder_msd.jl @@ -0,0 +1,99 @@ +#!/usr/bin/env julia +# Goal (1): PauliPropagation.jl benchmark — MSD of the 2-leg XY ladder under +# real-space 2nd-order (Strang) Trotter, NO symmetry merging. Mirrors the ppvm +# run in main_realspace_ladder.py (same bonds, Strang structure, localized Z +# seed, |coeff| truncation) so the MSD curves overlay and the runtime/memory +# can be compared head-to-head. +# +# Usage: julia -t 10 xy_ladder_msd.jl [L] [dt] [nsteps] [min_abs_coeff] [max_weight] [out.csv] +# defaults: L=41 dt=0.02 nsteps=100 min_abs_coeff=1e-6 max_weight=0(=off) out=data/g1_pp.csv +# +# Output: CSV with columns t,msd (one row per step). Wall time is reported +# by the NERSC `/usr/bin/time -v` wrapper; we also print it. +# +# Verified locally (PauliPropagation.jl, Julia 1.12) against ppvm at L=5, +# dt=0.02: MSD(t) curves agree to ~1e-9. If the NERSC PauliPropagation version +# differs and the API names (PauliSum / PauliString / PauliRotation / +# propagate / getcoeff) or the `theta` angle convention change, re-run the +# small-L cross-check against main_realspace_ladder.py and adjust. +using PauliPropagation +using Printf + +arg(i, d) = length(ARGS) >= i ? ARGS[i] : d +L = parse(Int, arg(1, "41")) +dt = parse(Float64, arg(2, "0.02")) +nsteps = parse(Int, arg(3, "100")) +mincoeff = parse(Float64, arg(4, "1e-6")) +maxweight = parse(Int, arg(5, "0")) # 0 => no weight cap +outfile = arg(6, "data/g1_pp.csv") + +nlegs = 2 +nq = nlegs * L +j0 = div(L, 2) +site(j, a) = j + a * L + 1 # j∈0:L-1, a∈0:1 -> 1-indexed qubit +chain_coord(q) = (q - 1) % L # chain position of qubit q + +# Brick-wall bond layering (matches ppvm): vertex-disjoint layers so adjacent +# gates within a sweep commute. Degree-3 ladder -> up to 4 layers: even leg- +# bonds, odd leg-bonds, the wrap seam (odd ring isn't 2-edge-colourable), rungs. +legbond(j, a) = (site(j, a), site(mod(j + 1, L), a)) +bonds = Tuple{Int,Int}[] +for a in 0:1, j in 0:2:L-2; push!(bonds, legbond(j, a)); end # even leg bonds +for a in 0:1, j in 1:2:L-2; push!(bonds, legbond(j, a)); end # odd leg bonds +for a in 0:1; push!(bonds, legbond(L - 1, a)); end # wrap seam +for j in 0:L-1; push!(bonds, (site(j, 0), site(j, 1))); end # rungs + +# Second-order (O(dt^3)) per-bond Strang: forward sweep over the bonds then a +# reversed sweep, each bond rxx then ryy. rxx and ryy commute on a bond, so the +# reversed bond order makes the step a palindrome -> O(dt^3). Truncation MATCHES +# ppvm: rxx never drops (min_abs_coeff=0; it creates the hopping intermediate), +# ryy drops at |coeff| 0 ? + propagate([PauliRotation([:Y, :Y], [a, b])], ps, [theta]; min_abs_coeff = D, max_weight = maxweight) : + propagate([PauliRotation([:Y, :Y], [a, b])], ps, [theta]; min_abs_coeff = D) + end + return ps +end + +# localized seed observable O(0) = 0.5 Z_{(j0,0)} + 0.5 Z_{(j0,1)} (Σ a_q = 1) +psum = PauliSum(nq) +add!(psum, PauliString(nq, :Z, site(j0, 0), 0.5)) +add!(psum, PauliString(nq, :Z, site(j0, 1), 0.5)) + +# single-Z target strings for the profile readout +ztargets = [PauliString(nq, :Z, q, 1.0) for q in 1:nq] +# min-image chain displacement from j0, per qubit +dj = [let d = mod(chain_coord(q) - j0, L); d > div(L, 2) ? d - L : d end for q in 1:nq] + +function msd(ps) + num = 0.0; den = 0.0 + for q in 1:nq + c = getcoeff(ps, ztargets[q]) # coefficient of Z_q in the sum + num += dj[q]^2 * c + den += c + end + return num / den +end + +ts = Float64[] +ms = Float64[] +push!(ts, 0.0); push!(ms, msd(psum)) +t0 = time() +for s in 1:nsteps + global psum = trotter_step!(psum, mincoeff) + push!(ts, s * dt); push!(ms, msd(psum)) +end +wall = time() - t0 + +mkpath(dirname(outfile)) +open(outfile, "w") do io + println(io, "t,msd") + for (t, m) in zip(ts, ms); @printf(io, "%.10g,%.10g\n", t, m); end +end +@printf("done -> %s (L=%d, nq=%d, %d steps, wall %.1fs, MSD(T)=%.6g, basis=%d)\n", + outfile, L, nq, nsteps, wall, ms[end], length(psum)) diff --git a/ppvm-python/demo/lindblad_adaptive.py b/ppvm-python/demo/lindblad_adaptive.py new file mode 100644 index 000000000..45c0ab6db --- /dev/null +++ b/ppvm-python/demo/lindblad_adaptive.py @@ -0,0 +1,313 @@ +# --- +# jupyter: +# jupytext: +# cell_metadata_filter: -all +# text_representation: +# extension: .py +# format_name: percent +# format_version: '1.3' +# jupytext_version: 1.19.1 +# kernelspec: +# display_name: ppvm (3.12.12) +# language: python +# name: python3 +# --- + +# SPDX-FileCopyrightText: 2026 The PPVM Authors +# SPDX-License-Identifier: Apache-2.0 + +# %% [markdown] +# # Adaptive Pauli-Lindbladian time evolution +# +# Direct Heisenberg-picture evolution of a transport observable on a growing +# Pauli-string basis, without Trotterisation. Composes the three +# `ppvm.Lindbladian` primitives — `leakage`, `generator`, and the matrix +# exponential — into a predictor-corrector integrator on an all-to-all XY +# model (Kac-normalised $1/r^\alpha$ couplings) with single-site Z dephasing. +# +# The observable is kept as a finite sum over Pauli strings (the *basis*), +# and each step: +# +# 1. measures the leakage $(\mathbf 1 - P_B)\,\mathcal L^\dagger(\mathcal O)$ +# out of the current basis $B$; +# 2. adds the leakage strings above `add_tol` to $B$; +# 3. advances the coefficient vector by $\exp(dt\,M)$, where +# $M = P_B \mathcal L^\dagger P_B$ is the Lindbladian restricted to $B$; +# 4. prunes coefficients below `drop_tol`; the protected set (the target +# observable's own support) is never dropped. +# +# The matrix exponential is exact in `dt` within the basis, so there is no +# Trotter splitting error; the only approximation is the finite basis, +# monitored by the cumulative discarded weight. +# +# With `predictor_corrector=True`, the predicted state is fed back as a +# second leakage probe — enriching $B$ with the strings the predictor flows +# into before re-running the step from the pre-step state. This lifts the +# per-step adaptive-integration error from $\mathcal O(dt^2)$ to $\mathcal O(dt^3)$. +# +# The observable is the single-Z Fourier mode +# $\mathcal O_k = \sum_j \cos(k x_j) Z_j$; its decay +# $C_k(t)/C_k(0)$ is the (infinite-temperature) spin transport coefficient. + +# %% +import matplotlib.pyplot as plt +import numpy as np +import scipy.sparse as sp +from scipy.sparse.linalg import expm_multiply + +from ppvm import Lindbladian + +# %% [markdown] +# ## Parameters + +# %% +L = 8 +alpha = 3.0 +gamma = 0.1 +dt = 0.05 +steps = 20 +kmax = 3 +add_tol = 1e-8 +drop_tol = 1e-10 +max_pauli_weight = L +max_basis = 0 # 0 = no cap +predictor_corrector = True + +times = np.arange(steps + 1) * dt +k_indices = np.arange(1, kmax + 1) +k_modes = 2 * np.pi * k_indices / L +x = np.arange(L) - L // 2 + + +# %% [markdown] +# ## Model +# +# All-to-all XY Hamiltonian $H = \sum_{a drop_tol: + rows.append(zterm_codes(j)) + coeffs.append(c) + basis_arr = np.array(rows, dtype=np.uint8) + coeff = np.array(coeffs, dtype=float) + index = {row.tobytes(): i for i, row in enumerate(basis_arr)} + protected_keys = set(index) + return basis_arr, coeff, index, protected_keys + + +def add_leakage_to_basis(basis_arr, probe_coeff, extend_coeffs, protected_arr, index): + """Compute leakage from `probe_coeff`, add above-threshold strings to + `basis_arr`, and pad each vector in `extend_coeffs` with zeros for the + new rows. Returns ``(basis_arr, [extended...], index, rate_below)`` where + `rate_below` is the l2 norm of the leakage too small to add.""" + leak_basis, leak_coeffs = L_op.leakage_arr(basis_arr, probe_coeff, protected_arr) + if not len(leak_coeffs): + return basis_arr, list(extend_coeffs), index, 0.0 + weights = weights_of(leak_basis) + add_mask = (np.abs(leak_coeffs) > add_tol) & (weights <= max_pauli_weight) + rate_below = float(np.linalg.norm(leak_coeffs[~add_mask])) + if not add_mask.any(): + return basis_arr, list(extend_coeffs), index, rate_below + cand = leak_basis[add_mask] + cand = cand[np.argsort(np.abs(leak_coeffs[add_mask]))[::-1]] + cand = cand[np.array([row.tobytes() not in index for row in cand])] + if max_basis: + cand = cand[: max(max_basis - len(basis_arr), 0)] + if not len(cand): + return basis_arr, list(extend_coeffs), index, rate_below + n0 = len(basis_arr) + basis_arr = np.vstack([basis_arr, cand]) + extended = [np.r_[c, np.zeros(len(cand))] for c in extend_coeffs] + for i, row in enumerate(cand): + index[row.tobytes()] = n0 + i + return basis_arr, extended, index, rate_below + + +def prune_and_cap(basis_arr, coeff, protected_keys): + """Drop below-`drop_tol` coefficients; if `max_basis` is set, cap by + keeping protected rows + largest-magnitude others.""" + keep = np.array( + [(row.tobytes() in protected_keys) or (abs(v) >= drop_tol) + for row, v in zip(basis_arr, coeff)] + ) + basis_arr = basis_arr[keep] + coeff = coeff[keep] + keys = [row.tobytes() for row in basis_arr] + index = {kk: i for i, kk in enumerate(keys)} + protected_keys = {pk for pk in protected_keys if pk in index} + if max_basis and len(basis_arr) > max_basis: + slots = max(max_basis - len(protected_keys), 0) + is_protected = np.array([kk in protected_keys for kk in keys]) + order = sorted(np.where(~is_protected)[0].tolist(), + key=lambda i: abs(coeff[i]), reverse=True) + keep2 = is_protected.copy() + keep2[order[:slots]] = True + basis_arr = basis_arr[keep2] + coeff = coeff[keep2] + keys = [row.tobytes() for row in basis_arr] + index = {kk: i for i, kk in enumerate(keys)} + protected_keys = {pk for pk in protected_keys if pk in index} + return basis_arr, coeff, index, protected_keys + + +# %% [markdown] +# ## Run one $k$-mode +# +# Returns per-step $C_k(t)$, basis size, max weight, and cumulative discarded +# weight (trapezoidal a-posteriori error estimate normalised by +# $\|\mathcal O_k\|$). + +# %% +def run_mode(kk): + basis_arr, coeff, index, protected_keys = init_mode(kk) + # `basis_arr` rebinds to a new ndarray on every vstack/slice; nothing + # mutates the initial array in place, so the target/protected views can + # simply alias it without a copy. + target_arr = basis_arr + target_coeff = coeff + protected_arr = basis_arr + norm0 = float(np.dot(coeff, coeff)) + norm_target = np.sqrt(norm0) + + ck = np.empty(steps + 1) + n_basis_t = np.empty(steps + 1, dtype=np.int64) + max_w_t = np.empty(steps + 1, dtype=np.int64) + discarded_cum = np.zeros(steps + 1) + + for nt in range(steps + 1): + # Overlap with the (fixed) initial target. + c_t = sum(coeff[index[trow.tobytes()]] * tc + for trow, tc in zip(target_arr, target_coeff) + if trow.tobytes() in index) + ck[nt] = c_t / norm0 + n_basis_t[nt] = len(basis_arr) + max_w_t[nt] = int(weights_of(basis_arr).max()) + if nt == steps: + break + + # Predictor: enrich basis with leakage from current state, then + # advance by exp(dt · M). + basis_arr, [coeff], index, rate_before = add_leakage_to_basis( + basis_arr, coeff, [coeff], protected_arr, index + ) + coeff_pre = coeff.copy() + coeff = expm_multiply(dt * generator_sparse(L_op, basis_arr), coeff) + + if predictor_corrector: + # Probe leakage with the predicted state; extend the pre-step + # vector with zeros for the new rows and re-run on the enlarged + # basis. Lifts O(dt²) -> O(dt³). + basis_arr, [coeff_pre], index, _ = add_leakage_to_basis( + basis_arr, coeff, [coeff_pre], protected_arr, index + ) + coeff = expm_multiply(dt * generator_sparse(L_op, basis_arr), coeff_pre) + + # Post-step leakage rate, for the trapezoidal error estimate. + norm2_pre_prune = float(np.dot(coeff, coeff)) + _, leak_after = L_op.leakage_arr(basis_arr, coeff, protected_arr) + rate_after = float(np.linalg.norm(leak_after)) if len(leak_after) else 0.0 + + basis_arr, coeff, index, protected_keys = prune_and_cap( + basis_arr, coeff, protected_keys + ) + # Pruning only removes entries, so the discarded l2 weight is + # sqrt(‖c‖²_pre − ‖c‖²_post). + dropped_w = np.sqrt(max(norm2_pre_prune - float(np.dot(coeff, coeff)), 0.0)) + d_total = 0.5 * dt * (rate_before + rate_after) + dropped_w + discarded_cum[nt + 1] = discarded_cum[nt] + d_total / norm_target + + return ck, n_basis_t, max_w_t, discarded_cum + + +# %% [markdown] +# ## Run all $k$-modes and plot + +# %% +Ck = np.empty((steps + 1, kmax)) +n_basis = np.empty((steps + 1, kmax), dtype=np.int64) +max_weight = np.empty((steps + 1, kmax), dtype=np.int64) +discarded_cum = np.empty((steps + 1, kmax)) +for m, kk in enumerate(k_modes): + Ck[:, m], n_basis[:, m], max_weight[:, m], discarded_cum[:, m] = run_mode(kk) + +# %% +fig, ax = plt.subplots() +for m in range(kmax): + ax.plot(times, Ck[:, m], "o-", ms=3, label=rf"$k = 2\pi\cdot{k_indices[m]}/L$") +ax.set_xlabel("$t$") +ax.set_ylabel(r"$C_k(t)/C_k(0)$") +ax.set_title(f"Adaptive Lindbladian evolution L={L} γ={gamma} α={alpha}") +ax.legend() +plt.tight_layout() +plt.show() + +# %% +fig, ax = plt.subplots(1, 2, figsize=(10, 4)) +for m in range(kmax): + ax[0].plot(times, n_basis[:, m], "o-", ms=3, label=rf"$k_{k_indices[m]}$") + ax[1].semilogy(times, discarded_cum[:, m] + 1e-16, "o-", ms=3, + label=rf"$k_{k_indices[m]}$") +ax[0].set(xlabel="$t$", ylabel="|basis|", title="Basis-size growth") +ax[1].set(xlabel="$t$", ylabel=r"cum. discarded / $||O_k||$", + title="A-posteriori error estimate") +for a in ax: + a.legend() +plt.tight_layout() +plt.show() diff --git a/ppvm-python/demo/lindblad_pc_scaling.py b/ppvm-python/demo/lindblad_pc_scaling.py new file mode 100644 index 000000000..f7c56c34b --- /dev/null +++ b/ppvm-python/demo/lindblad_pc_scaling.py @@ -0,0 +1,185 @@ +# --- +# jupyter: +# jupytext: +# cell_metadata_filter: -all +# text_representation: +# extension: .py +# format_name: percent +# format_version: '1.3' +# jupytext_version: 1.19.1 +# kernelspec: +# display_name: ppvm (3.12.12) +# language: python +# name: python3 +# --- + +# SPDX-FileCopyrightText: 2026 The PPVM Authors +# SPDX-License-Identifier: Apache-2.0 + +# %% [markdown] +# # `pc_step` parallel scaling +# +# End-to-end wall-time scaling of the pure-Rust predictor-corrector step +# (`ppvm.Lindbladian.pc_step`) with rayon thread count. The entire `pc_step` +# body — both leakage calls, the generator build, and both matrix +# exponentials — runs inside a rayon pool of the requested size: +# +# * leakage and generator parallelise over basis elements; +# * the matrix exponential parallelises over SpMV rows. +# +# So the speedup numbers reflect overall PC throughput, not just SpMV. + +# %% +from statistics import median +import time + +import matplotlib.pyplot as plt +import numpy as np + +from ppvm import Lindbladian + + +# %% [markdown] +# ## Parameters + +# %% +L = 51 +J = 1.0 +gamma = 1.0 +alpha = 1.0 +dt = 0.05 +n_steps = 20 +tau_add = 1e-8 +max_cores = 4 +warmup_steps = 4 +model = "long-range" # "nn" or "long-range" + + +# %% [markdown] +# ## Model +# +# All-to-all XY with $1/r^\alpha$ couplings (Kac-normalised) and per-site Z +# dephasing. Long-range activates every bond every step, giving a basis +# size that meaningfully exercises parallel scaling. + +# %% +def build_nn_xy_dephasing(L, J, gamma): + h_terms = [] + for i in range(L - 1): + a, b = i, i + 1 + xs = ["I"] * L + xs[a] = xs[b] = "X" + ys = ["I"] * L + ys[a] = ys[b] = "Y" + h_terms += [("".join(xs), J), ("".join(ys), J)] + jump_terms = [("I" * j + "Z" + "I" * (L - j - 1), gamma) for j in range(L)] + return h_terms, jump_terms + + +def build_long_range_xy_dephasing(L, J, alpha, gamma): + pairs = [ + (a, b, 1.0 / min(b - a, L - b + a) ** alpha) + for a in range(L) + for b in range(a + 1, L) + ] + kac = sum(j for _, _, j in pairs) / L + pairs = [(a, b, j / kac) for a, b, j in pairs] + h_terms = [] + for a, b, j in pairs: + for q in "XY": + term = ["I"] * L + term[a] = term[b] = q + h_terms.append(("".join(term), J * j)) + jump_terms = [("I" * j + "Z" + "I" * (L - j - 1), gamma) for j in range(L)] + return h_terms, jump_terms + + +if model == "nn": + h_terms, jump_terms = build_nn_xy_dephasing(L, J, gamma) +else: + h_terms, jump_terms = build_long_range_xy_dephasing(L, J, alpha, gamma) +L_op = Lindbladian(L, h_terms, jump_terms) + + +# %% [markdown] +# ## Timing harness +# +# Each call to `run_pc_steps` runs `n_steps` consecutive PC steps from +# $Z_{L/2}$, returning the per-step wall times and the final basis size. +# The `num_threads` kwarg pins this call to a freshly-built rayon pool of +# that size, isolating thread-count effects from JIT cache state. + +# %% +def run_pc_steps(L_op, L, site0, dt, n_steps, tau_add, num_threads): + z_strings = ["I" * j + "Z" + "I" * (L - j - 1) for j in range(L)] + basis = [z_strings[site0]] + coeffs = np.array([1.0]) + protected = [z_strings[site0]] + times = [] + for _ in range(n_steps): + t0 = time.perf_counter() + basis, coeffs = L_op.pc_step( + basis, + coeffs, + dt, + tau_add, + protected=protected, + num_threads=num_threads, + ) + times.append(time.perf_counter() - t0) + return times, len(basis) + + +# %% [markdown] +# ## Warmup +# +# Each thread count pre-builds its rayon pool and amortises one-time setup +# before the real timing pass. + +# %% +site0 = L // 2 +for n in range(1, max_cores + 1): + run_pc_steps(L_op, L, site0, dt, warmup_steps, tau_add, n) + + +# %% [markdown] +# ## Scaling sweep + +# %% +results = [] +for n in range(1, max_cores + 1): + times, basis_size = run_pc_steps(L_op, L, site0, dt, n_steps, tau_add, n) + first = times[0] * 1000.0 + steady = median(times[1:]) * 1000.0 + results.append({"threads": n, "first_ms": first, "steady_ms": steady, + "basis": basis_size}) + +baseline = results[0]["steady_ms"] +print(f"{'threads':>8s} {'first-step (ms)':>16s} {'steady (ms)':>12s} " + f"{'speedup':>9s} {'|basis|':>8s}") +for r in results: + speedup = baseline / r["steady_ms"] + print(f"{r['threads']:>8d} {r['first_ms']:>16.1f} {r['steady_ms']:>12.2f} " + f"{speedup:>8.2f}x {r['basis']:>8d}") + + +# %% [markdown] +# ## Plot +# +# Steady-state speedup vs thread count, with the linear-scaling reference. + +# %% +threads = np.array([r["threads"] for r in results]) +steady_ms = np.array([r["steady_ms"] for r in results]) +speedup = steady_ms[0] / steady_ms + +fig, ax = plt.subplots() +ax.plot(threads, speedup, "o-", label="measured") +ax.plot(threads, threads, "k--", alpha=0.4, label="linear") +ax.set_xlabel("threads") +ax.set_ylabel("speedup (vs 1 thread)") +ax.set_title(f"pc_step parallel scaling L={L} model={model} " + f"|basis|={results[-1]['basis']}") +ax.legend() +plt.tight_layout() +plt.show() diff --git a/ppvm-python/demo/stim.py b/ppvm-python/demo/stim_demo.py similarity index 100% rename from ppvm-python/demo/stim.py rename to ppvm-python/demo/stim_demo.py diff --git a/ppvm-python/demo/trotter_ladder.py b/ppvm-python/demo/trotter_ladder.py new file mode 100644 index 000000000..46da81ed3 --- /dev/null +++ b/ppvm-python/demo/trotter_ladder.py @@ -0,0 +1,73 @@ +"""Pedagogical example: Trotter evolution of the XY two-leg ladder with ppvm. + +We track an observable in the Heisenberg picture as a `PauliSum` (a weighted +sum of Pauli strings). Seeding with a localized Z at the centre rung and +applying second-order Trotter steps of the XX+YY ladder Hamiltonian, we read off +the spin profile a_q(t) = each step and reduce it to a +mean-squared displacement (MSD) along the chain — the signature of spin +transport. Truncating tiny coefficients (`min_abs_coeff`) is what keeps the +growing operator tractable. + + python trotter_ladder.py +""" +import numpy as np +from ppvm import PauliSum + +# ── parameters ─────────────────────────────────────────────────────────── +L = 10 # rungs; N = 2L qubits (two legs) +dt = 0.05 # Trotter step +steps = 20 +min_abs_coeff = 1e-4 # drop Pauli terms smaller than this (accuracy knob) + +import sys # optional override for benchmarking: python trotter_ladder.py L dt steps min_abs_coeff +if len(sys.argv) == 5: + L, dt, steps, min_abs_coeff = int(sys.argv[1]), float(sys.argv[2]), int(sys.argv[3]), float(sys.argv[4]) + +N = 2 * L +j0 = L // 2 # seed at the centre rung +site = lambda j, a: j + a * L # qubit index of rung j on leg a (0 or 1) + +# Brick-wall bond layering: group bonds into vertex-disjoint layers so adjacent +# gates within a sweep commute (no within-sweep propagation). The ladder is +# degree-3, so it takes up to 4 layers -- even leg-bonds, odd leg-bonds, the +# wrap-around seam (an odd ring is not 2-edge-colourable), and the rungs. +leg = lambda j, a: (site(j, a), site((j + 1) % L, a)) +bonds = ([leg(j, a) for a in (0, 1) for j in range(0, L - 1, 2)] # even leg bonds + + [leg(j, a) for a in (0, 1) for j in range(1, L - 1, 2)] # odd leg bonds + + [leg(L - 1, a) for a in (0, 1)] # wrap seam + + [(site(j, 0), site(j, 1)) for j in range(L)]) # rungs + +# Observable O(0) = (Z_{j0,0} + Z_{j0,1}) / 2. Σ_q a_q = is conserved. +o = PauliSum.new(N, [(f"Z{site(j0, 0)}", 0.5), (f"Z{site(j0, 1)}", 0.5)], + min_abs_coeff=min_abs_coeff, max_pauli_weight=N) +z_targets = [PauliSum.new(N, f"Z{q}") for q in range(N)] # for the profile readout + + +def trotter_step(): + """One second-order Strang step (O(dt^3)): a forward sweep over the bonds + then a reversed sweep, each bond evolved by rxx(dt) then ryy(dt). rxx and ryy + commute on a bond, so the reversed bond order makes the step a palindrome -> + O(dt^3). rxx is applied WITHOUT truncation and ryy WITH it, on purpose: rxx + turns Z_a into cos(.)Z_a + sin(.)Y_aX_b -- the hopping intermediate -- which + the very next ryy on the SAME bond rotates into Z_b. Dropping terms only + after that pair (never the bare intermediate) keeps the Z-hopping flux + intact, so total Z stays conserved even under aggressive truncation.""" + for a, b in bonds: + o.rxx(a, b, dt, truncate=False); o.ryy(a, b, dt) + for a, b in reversed(bonds): + o.rxx(a, b, dt, truncate=False); o.ryy(a, b, dt) + + +def msd(): + """MSD along the chain: Σ_q (Δj_q)^2 a_q / Σ_q a_q, with a_q = , + Δj the min-image chain displacement from j0 (both legs summed via q % L).""" + a = np.array([o.overlap(z) for z in z_targets]) + dj = ((np.arange(N) % L) - j0 + L // 2) % L - L // 2 + return float((dj**2 * a).sum() / a.sum()) + + +print(" t MSD n_terms") +for n in range(steps + 1): + print(f"{n*dt:5.2f} {msd():8.4f} {len(o):7d}") + if n < steps: + trotter_step() diff --git a/ppvm-python/pyproject.toml b/ppvm-python/pyproject.toml index ee6a96369..e6636d1df 100644 --- a/ppvm-python/pyproject.toml +++ b/ppvm-python/pyproject.toml @@ -10,6 +10,7 @@ requires-python = ">=3.10" dependencies = [ "bloqade-circuit>=0.14.1", "kirin>=0.0.15", + "numpy>=1.26", "ppvm-python-native", ] @@ -44,10 +45,21 @@ extra-paths = ["../crates/ppvm-python-native"] [tool.ty.src] exclude = ["docs/"] +[tool.pytest.ini_options] +# Benchmarks (test/benchmarks/) only time when explicitly enabled via +# --benchmark-enable; otherwise they run once as smoke tests. +addopts = "--benchmark-disable" + [dependency-groups] dev = [ "numpy>=2.2.6", "pytest>=9.0.2", + "pytest-benchmark>=5.2.3", +] +# Optional: only the `demo/` scripts use it (`expm_multiply` for the reference +# matrix exponential). Runtime ppvm and the test suite have no scipy dep. +demo = [ + "scipy>=1.13", ] doc = [ "griffe-inherited-docstrings>=1.1.1", diff --git a/ppvm-python/src/ppvm/__init__.py b/ppvm-python/src/ppvm/__init__.py index f28072849..57beb9420 100644 --- a/ppvm-python/src/ppvm/__init__.py +++ b/ppvm-python/src/ppvm/__init__.py @@ -6,6 +6,9 @@ from .generalized_tableau import GeneralizedTableau as GeneralizedTableau from .generalized_tableau import MeasurementResult as MeasurementResult from .generalized_tableau import sample_stim as sample_stim +from .lindblad import Lindbladian as Lindbladian +from .lindblad import sigma_minus as sigma_minus +from .lindblad import sigma_plus as sigma_plus from .paulisum import LossyPauliSum as LossyPauliSum from .paulisum import PauliSum as PauliSum from .squin_interpreter.device import ( diff --git a/ppvm-python/src/ppvm/lindblad.py b/ppvm-python/src/ppvm/lindblad.py new file mode 100644 index 000000000..231499341 --- /dev/null +++ b/ppvm-python/src/ppvm/lindblad.py @@ -0,0 +1,401 @@ +# SPDX-FileCopyrightText: 2026 The PPVM Authors +# SPDX-License-Identifier: Apache-2.0 + +"""Direct Pauli-Lindbladian time evolution on an adaptive Pauli-string basis. + +Given a Hermitian Pauli Hamiltonian H = Σ c_i P_i and jump operators +L_k = Σ_a λ_{k,a} P_{k,a} (each a complex linear combination of Pauli +strings) with rates γ_k ≥ 0, this module exposes three primitives needed +for adaptive Heisenberg-picture evolution: + +- ``action(p)`` / ``action_arr(p)``: L*(p) for one Pauli string p +- ``leakage(basis, coeffs)`` / ``leakage_arr(...)``: off-basis component of + L*(Σ c_j p_j), driving basis expansion +- ``generator(basis)``: COO triples ``(rows, cols, vals)`` for the generator + matrix M such that L* restricted to ``basis`` is ``M @ coeffs``. Users + wanting a sparse matrix can wrap them — e.g. + ``scipy.sparse.coo_matrix((vals, (rows, cols)), shape=(N, N)).tocsc()`` + +The ``*_arr`` variants pass Pauli strings as ``(N, n_qubits)`` ``uint8`` +arrays of Pauli codes (``0=I, 1=X, 2=Z, 3=Y``) and skip string +construction entirely — at ~10^5 basis rows per evolution step, per-row +``str.join`` dominates wall time. + +Each jump term can be either: + +- a single Hermitian Pauli (`("ZZII", γ)`), routed to a fast diagonal path, + or +- a complex Pauli sum (`([("XIII", 0.5+0j), ("YIII", 0+0.5j)], γ)`) to + describe e.g. amplitude-damping (`σ⁻`) and excitation (`σ⁺`) operators. + +For the general case the shim evaluates +``γ ( L† p L − ½ {L†L, p} )`` directly; the L†L Pauli expansion is +precomputed once at construction. +""" + +from __future__ import annotations + +from collections.abc import Iterable, Sequence +from typing import Union + +import numpy as np +from ppvm_python_native import LindbladSpec as _LindbladSpec + +_PAULI_CODE = {"I": 0, "X": 1, "Z": 2, "Y": 3} +# Lookup table mapping code -> ASCII byte for vectorised string output. +_CODE_TO_ASCII = np.array([ord("I"), ord("X"), ord("Z"), ord("Y")], dtype=np.uint8) + +# A jump operator is either a Hermitian Pauli (single string) or a complex +# linear combination of Pauli strings. +PauliLincomb = Iterable[tuple[str, complex]] +JumpSpec = Union[tuple[str, float], tuple[PauliLincomb, float]] + + +def _string_to_codes(s: str, n_qubits: int) -> np.ndarray: + """Encode a Pauli string ``"IXYZ..."`` as a length-``n_qubits`` uint8 array. + + Underscores in the input are ignored, matching the Rust parser + (``parse_pauli_string`` in `ppvm-lindblad`) so users can write + ``"X_Y_Z"`` for readability. + """ + s_clean = s.replace("_", "") + if len(s_clean) != n_qubits: + raise ValueError( + f"Pauli string {s!r} has length {len(s_clean)} (after stripping '_') " + f"!= n_qubits {n_qubits}" + ) + try: + return np.array([_PAULI_CODE[c] for c in s_clean], dtype=np.uint8) + except KeyError as exc: + bad = exc.args[0] + raise ValueError( + f"Pauli string {s!r} contains invalid character {bad!r}; " + f"expected one of 'I', 'X', 'Y', 'Z' (and '_' is allowed as a separator)" + ) from None + + +def _codes_to_string(codes: np.ndarray) -> str: + """Decode one length-``n_qubits`` row of Pauli codes back to a string.""" + return _CODE_TO_ASCII[codes].tobytes().decode("ascii") + + +def _basis_to_codes(basis: Sequence[str], n_qubits: int) -> np.ndarray: + """Stack a sequence of Pauli strings into an ``(N, n_qubits)`` uint8 array.""" + arr = np.zeros((len(basis), n_qubits), dtype=np.uint8) + for i, s in enumerate(basis): + arr[i] = _string_to_codes(s, n_qubits) + return arr + + +def _codes_to_basis(arr: np.ndarray) -> list[str]: + """Inverse of :func:`_basis_to_codes`. One call into C per row.""" + bytes_per_row = _CODE_TO_ASCII[arr].tobytes() + n = arr.shape[1] + return [bytes_per_row[i * n : (i + 1) * n].decode("ascii") for i in range(arr.shape[0])] + + +def sigma_plus(site: int, n_qubits: int) -> list[tuple[str, complex]]: + """``σ⁺_q = (X_q + i Y_q) / 2``. Use as a Lindblad jump for excitation.""" + if not 0 <= site < n_qubits: + raise ValueError(f"site {site} out of range for n_qubits={n_qubits}") + x_str = "I" * site + "X" + "I" * (n_qubits - site - 1) + y_str = "I" * site + "Y" + "I" * (n_qubits - site - 1) + return [(x_str, 0.5 + 0.0j), (y_str, 0.0 + 0.5j)] + + +def sigma_minus(site: int, n_qubits: int) -> list[tuple[str, complex]]: + """``σ⁻_q = (X_q − i Y_q) / 2``. Use as a Lindblad jump for amplitude damping.""" + if not 0 <= site < n_qubits: + raise ValueError(f"site {site} out of range for n_qubits={n_qubits}") + x_str = "I" * site + "X" + "I" * (n_qubits - site - 1) + y_str = "I" * site + "Y" + "I" * (n_qubits - site - 1) + return [(x_str, 0.5 + 0.0j), (y_str, 0.0 - 0.5j)] + + +def _normalize_jump(jump_op: object) -> list[tuple[str, float, float]]: + """Convert a user-supplied jump operator to ``[(pauli_str, re, im), ...]``. + + Accepts either a single Pauli string (treated as a Hermitian-Pauli jump + with coefficient 1) or an iterable of ``(pauli_str, complex_coeff)`` + pairs. + """ + if isinstance(jump_op, str): + return [(jump_op, 1.0, 0.0)] + out: list[tuple[str, float, float]] = [] + for term in jump_op: + s, c = term + cc = complex(c) + out.append((str(s), float(cc.real), float(cc.imag))) + if not out: + raise ValueError("jump operator lincomb must contain at least one Pauli term") + return out + + +class Lindbladian: + """Pre-compiled adjoint Pauli-Lindbladian acting on Pauli strings. + + Parameters + ---------- + n_qubits: + Number of qubits. + h_terms: + Iterable of ``(pauli_string, coefficient)`` pairs for the + Hermitian Hamiltonian ``H = Σ c_i P_i``. Each ``pauli_string`` is + a length-``n_qubits`` ``str`` over ``"IXYZ"``. + jump_terms: + Iterable of ``(jump_op, rate)`` pairs. ``jump_op`` is either a + Pauli string ``"XYZI..."`` (treated as a Hermitian-Pauli jump + with coefficient 1, hitting the fast path) or an iterable of + ``(pauli_string, complex_coeff)`` pairs for a general complex + Pauli linear combination such as :func:`sigma_plus` or + :func:`sigma_minus`. ``rate`` is the non-negative GKSL rate + ``γ_k``. + + Examples + -------- + Dephasing (Hermitian Pauli): + + >>> Lindbladian(2, [("XX", 1.0)], [("ZI", 0.3), ("IZ", 0.3)]) + + Amplitude damping on site 0 (non-Hermitian): + + >>> jumps = [(sigma_minus(0, 2), 0.5)] + >>> Lindbladian(2, [("XX", 1.0)], jumps) + """ + + def __init__( + self, + n_qubits: int, + h_terms: Iterable[tuple[str, float]], + jump_terms: Iterable[tuple[object, float]] = (), + ): + self.n_qubits = int(n_qubits) + h_strs: list[str] = [] + h_coeffs: list[float] = [] + for s, c in h_terms: + h_strs.append(s) + h_coeffs.append(float(c)) + j_lincombs: list[list[tuple[str, float, float]]] = [] + j_rates: list[float] = [] + for jump_op, rate in jump_terms: + j_lincombs.append(_normalize_jump(jump_op)) + j_rates.append(float(rate)) + self._spec = _LindbladSpec(self.n_qubits, h_strs, h_coeffs, j_lincombs, j_rates) + + @property + def num_h_terms(self) -> int: + return self._spec.num_h_terms + + @property + def num_jump_terms(self) -> int: + return self._spec.num_jump_terms + + # ── Pure-ndarray hot path ── + + def action_arr(self, p: np.ndarray) -> tuple[np.ndarray, np.ndarray]: + """Apply ``L*`` to a single Pauli string given as uint8 codes. + + Returns ``(out_basis, out_coeffs)``: a ``(M, n_qubits)`` uint8 + array and a length-``M`` float64 array. + """ + return self._spec.action(np.ascontiguousarray(p, dtype=np.uint8)) + + def leakage_arr( + self, + basis_arr: np.ndarray, + coeffs: np.ndarray, + protected_arr: np.ndarray | None = None, + ) -> tuple[np.ndarray, np.ndarray]: + """Off-basis component of ``L*( Σ_j coeffs[j] basis[j] )``. + + ``basis_arr``: ``(N, n_qubits)`` uint8. ``coeffs``: length-N float64. + ``protected_arr``: optional ``(K, n_qubits)`` uint8 of Pauli strings + that must NEVER appear in the leakage output. + + Returns ``(out_basis, out_coeffs)`` packed the same way as + :meth:`action_arr`. + """ + n = self.n_qubits + if protected_arr is None: + protected_arr = np.zeros((0, n), dtype=np.uint8) + return self._spec.leakage( + np.ascontiguousarray(basis_arr, dtype=np.uint8), + np.ascontiguousarray(coeffs, dtype=np.float64), + np.ascontiguousarray(protected_arr, dtype=np.uint8), + ) + + def pc_step_arr( + self, + basis_arr: np.ndarray, + coeffs: np.ndarray, + dt: float, + tau_add: float | None = None, + drop_tol: float = 0.0, + K: float = 5.0, + protected_arr: np.ndarray | None = None, + num_threads: int | None = None, + ) -> tuple[np.ndarray, np.ndarray]: + """One predictor-corrector adaptive step. + + All work — leakage expansion, matrix-exponential step, second-hop + re-expansion, corrector — runs in Rust; SciPy is not required. + The matrix-exponential action is computed matrix-free via the external + ``quspin-expm`` crate (Al-Mohy & Higham scaling-and-squaring). + + Tolerances. ``drop_tol`` prunes basis entries whose absolute + coefficient is below this threshold after the corrector (unless + the word is ``protected``). ``tau_add`` is the leakage-rate + threshold for adding new strings. The default policy ties them via + ``tau_add = K * drop_tol / dt`` (with ``K = 5``): the LR-XY + γ=1, L=51 Pareto study showed K≈5 lies on the front, with + ``drop_tol`` the natural accuracy knob. Pass ``tau_add`` explicitly + to override. + + ``num_threads``, when set, pins this call to a freshly-built rayon + pool of that size — useful for benchmarking parallel scaling. + + Returns ``(new_basis_arr, new_coeffs)``; the basis may have grown + (or shrunk, if ``drop_tol`` pruned entries). + """ + if tau_add is None: + if drop_tol <= 0.0: + raise ValueError( + "must provide tau_add explicitly, or drop_tol > 0 " + "(tau_add defaults to K * drop_tol / dt)" + ) + tau_add = K * drop_tol / dt + n = self.n_qubits + if protected_arr is None: + protected_arr = np.zeros((0, n), dtype=np.uint8) + return self._spec.pc_step( + np.ascontiguousarray(basis_arr, dtype=np.uint8), + np.ascontiguousarray(coeffs, dtype=np.float64), + float(dt), + float(tau_add), + float(drop_tol), + np.ascontiguousarray(protected_arr, dtype=np.uint8), + None if num_threads is None else int(num_threads), + ) + + def rk4_step_arr( + self, + basis_arr: np.ndarray, + coeffs: np.ndarray, + dt: float, + drop_tol: float = 0.0, + protected_arr: np.ndarray | None = None, + num_threads: int | None = None, + ) -> tuple[np.ndarray, np.ndarray]: + """One classical fourth-order Runge-Kutta step on ``L*``. + + Matrix-free: no CSR build, no Krylov subspace, no predictor- + corrector basis enrichment. Four action evaluations per step; + the basis grows naturally as new strings emerge from each + commutator. After the step, drops any string with + ``|coeff| < drop_tol`` unless it appears in ``protected_arr``. + + Per-step local truncation error is ``O(dt^5)``. + **Stability** requires ``dt ≤ 2.78 / ‖L*‖``. Violating the bound + is silent — the trajectory still norm-conserves, but individual + Pauli coefficients diverge to oscillating ±large values; local + observables (e.g. MSD) blow up. Verify against a stable reference + before trusting tight-``drop_tol`` results at large ``dt``. + + For stiff problems where that bound is restrictive, prefer + :meth:`pc_step_arr`, which integrates ``exp(dt·L*)`` via Krylov + and is unconditionally stable. + """ + n = self.n_qubits + if protected_arr is None: + protected_arr = np.zeros((0, n), dtype=np.uint8) + return self._spec.rk4_step( + np.ascontiguousarray(basis_arr, dtype=np.uint8), + np.ascontiguousarray(coeffs, dtype=np.float64), + float(dt), + float(drop_tol), + np.ascontiguousarray(protected_arr, dtype=np.uint8), + None if num_threads is None else int(num_threads), + ) + + def pc_step( + self, + basis: Sequence[str], + coeffs: np.ndarray, + dt: float, + tau_add: float | None = None, + drop_tol: float = 0.0, + K: float = 5.0, + protected: Sequence[str] | None = None, + num_threads: int | None = None, + ) -> tuple[list[str], np.ndarray]: + """String-keyed variant of :meth:`pc_step_arr`.""" + n = self.n_qubits + basis_arr = _basis_to_codes(basis, n) + protected_arr = ( + _basis_to_codes(list(protected), n) if protected else np.zeros((0, n), dtype=np.uint8) + ) + new_basis_arr, new_coeffs = self.pc_step_arr( + basis_arr, + coeffs, + dt, + tau_add, + drop_tol, + K, + protected_arr, + num_threads, + ) + return _codes_to_basis(new_basis_arr), new_coeffs + + def generator_arr( + self, basis_arr: np.ndarray + ) -> tuple[np.ndarray, np.ndarray, np.ndarray]: + """Generator matrix as COO triples ``(rows, cols, vals)``. + + Basis given as uint8 codes. To get a SciPy sparse matrix: + + >>> import scipy.sparse as sp + >>> rows, cols, vals = L_op.generator_arr(basis_arr) + >>> M = sp.coo_matrix( + ... (vals, (rows, cols)), shape=(len(basis_arr), len(basis_arr)) + ... ).tocsc() + """ + return self._spec.generator(np.ascontiguousarray(basis_arr, dtype=np.uint8)) + + # ── String-keyed convenience API (slower; for tests / display) ── + + def action(self, p: str) -> dict[str, float]: + """Apply ``L*`` to a single Pauli string ``p`` (string-keyed dict).""" + codes = _string_to_codes(p, self.n_qubits) + out_basis, out_coeffs = self._spec.action(codes) + keys = _codes_to_basis(out_basis) + return {k: float(v) for k, v in zip(keys, out_coeffs) if v != 0.0} + + def leakage( + self, + basis: Sequence[str], + coeffs: np.ndarray, + protected: Sequence[str] | None = None, + ) -> dict[str, float]: + """Off-basis leakage as a ``dict[str, float]`` (slower API).""" + n = self.n_qubits + basis_arr = _basis_to_codes(basis, n) + protected_arr = ( + _basis_to_codes(list(protected), n) if protected else np.zeros((0, n), dtype=np.uint8) + ) + out_basis, out_coeffs = self._spec.leakage( + basis_arr, + np.ascontiguousarray(coeffs, dtype=np.float64), + protected_arr, + ) + keys = _codes_to_basis(out_basis) + return {k: float(v) for k, v in zip(keys, out_coeffs) if v != 0.0} + + def generator( + self, basis: Sequence[str] + ) -> tuple[np.ndarray, np.ndarray, np.ndarray]: + """Generator matrix as COO triples ``(rows, cols, vals)``, + basis given as strings. See :meth:`generator_arr` for the conversion + to a SciPy sparse matrix.""" + n = self.n_qubits + basis_arr = _basis_to_codes(basis, n) + return self.generator_arr(basis_arr) diff --git a/ppvm-python/test/benchmarks/test_trotter.py b/ppvm-python/test/benchmarks/test_trotter.py new file mode 100644 index 000000000..9034a7db4 --- /dev/null +++ b/ppvm-python/test/benchmarks/test_trotter.py @@ -0,0 +1,68 @@ +"""pytest-benchmark mirror of crates/ppvm-runtime/benches/trotter.rs. + +Same circuit, parameters, truncation and initial observable as the Rust +trotter benchmark, run through the Python ``PauliSum``. Python hard-picks the +IndexMap + FxHash storage variant, so this corresponds to exactly the +``ByteF64FxIndexMap`` Rust config -- a single backend, by design. + +Run the timed benchmark with: + + uv run pytest test/benchmarks/test_trotter.py --benchmark-enable + +Without ``--benchmark-enable`` it runs once as a smoke test (see ``addopts`` in +pyproject.toml). +""" + +import copy + +import pytest + +from ppvm import PauliSum + +# parameters (match trotter.rs) +N_QUBITS = 12 +H = 1.0 +DT = 0.1 / H +TIME = 1.0 / H +J = 1.0 / 8.0 * H +MIN_ABS_COEFF = 1e-6 +# pauli_error([p/4]*3) damps each X/Y/Z coeff by (1-p): the depolarizing +# channel for p = 1e-4, matching DepolarizingNoise(1e-4) in PP.jl. +NOISE = [1e-4 / 4.0] * 3 + +ROUNDS = 200 + + +def build_state(): + # initial observable: sum_i Z_i + terms = [f"Z{i}" for i in range(N_QUBITS)] + return PauliSum.new(N_QUBITS, terms, min_abs_coeff=MIN_ABS_COEFF) + + +def trotter(state): + steps = int(TIME / DT) + theta_zz = DT * J + theta_x = DT * H + # gates default to truncate=True, i.e. truncate after every gate + # application, to stay consistent with the Rust benchmark / PP.jl. + for _ in range(steps): + for i in range(N_QUBITS): + state.rx(i, theta_x) + state.pauli_error(i, NOISE) + for i in range(N_QUBITS - 1): + state.rzz(i, i + 1, theta_zz) + state.pauli_error(i, NOISE) + state.pauli_error(i + 1, NOISE) + + +@pytest.mark.benchmark(group="trotter") +def test_trotter(benchmark): + state = build_state() + # clone a fresh state each round (not timed), mirroring Rust's + # iter_batched_ref(|| state.clone(), ...). + benchmark.pedantic( + trotter, + setup=lambda: ((copy.copy(state),), {}), + iterations=1, + rounds=ROUNDS, + ) diff --git a/ppvm-python/test/lindblad/__init__.py b/ppvm-python/test/lindblad/__init__.py new file mode 100644 index 000000000..e69de29bb diff --git a/ppvm-python/test/lindblad/_helpers.py b/ppvm-python/test/lindblad/_helpers.py new file mode 100644 index 000000000..444e7c856 --- /dev/null +++ b/ppvm-python/test/lindblad/_helpers.py @@ -0,0 +1,346 @@ +# SPDX-FileCopyrightText: 2026 The PPVM Authors +# SPDX-License-Identifier: Apache-2.0 +"""Shared helpers for the Lindbladian shim tests. + +Two reference kernels live here: + +- :func:`_reference_action` builds `L*(p)` for **Hermitian-Pauli** jumps via + the single-qubit Pauli multiplication table (cheap; only depends on `p`'s + weight). +- :func:`_dense_action` builds `L*(p)` for **arbitrary jump operators** by + constructing the full 2^L × 2^L dense Liouvillian. Only viable for L ≤ 3, + but it makes no assumption about the shape of the jumps. + +The bilinear NN-XY + Z-dephasing reference :func:`_bilinear_nn_xy_z_dephasing_obc` +gives an exact closed-form answer that the predictor-corrector tests converge +toward as dt → 0. +""" + +from __future__ import annotations + +import numpy as np + +# --- Pauli multiplication table for the Hermitian-Pauli reference ----------- +I, X, Y, Z = range(4) # noqa: E741 (I is standard Pauli notation here) +MUL = { + (I, I): (1, I), (I, X): (1, X), (I, Y): (1, Y), (I, Z): (1, Z), + (X, I): (1, X), (X, X): (1, I), (X, Y): (1j, Z), (X, Z): (-1j, Y), + (Y, I): (1, Y), (Y, X): (-1j, Z), (Y, Y): (1, I), (Y, Z): (1j, X), + (Z, I): (1, Z), (Z, X): (1j, Y), (Z, Y): (-1j, X), (Z, Z): (1, I), +} +CODE = {I: "I", X: "X", Y: "Y", Z: "Z"} +ICODE = {"I": I, "X": X, "Y": Y, "Z": Z} + + +def _str_to_tuple(s): + return tuple(ICODE[ch] for ch in s) + + +def _tuple_to_str(t): + return "".join(CODE[ch] for ch in t) + + +def _mul_pauli(p, q): + """Return ``(phase, p·q)`` for two Pauli strings given as code tuples.""" + phase = 1 + r = list(p) + for i, (pi, qi) in enumerate(zip(p, q)): + ph, rr = MUL[(pi, qi)] + phase *= ph + r[i] = rr + return phase, tuple(r) + + +def _reference_action(p_str, h_terms, jump_terms): + """``L*(p) = i[H, p] + sum_k gamma_k (L_k p L_k - p)``, term by term.""" + p = _str_to_tuple(p_str) + out: dict = {} + for h_str, coeff_h in h_terms: + h = _str_to_tuple(h_str) + ph_pp, pp = _mul_pauli(h, p) + ph_pq, _ = _mul_pauli(p, h) + # i[H, p] = i (Hp - pH) = i (ph_pp - ph_pq) r ; real for Hermitian H, p. + coeff = (1j * coeff_h * (ph_pp - ph_pq)).real + if coeff: + out[pp] = out.get(pp, 0.0) + coeff + for j_str, gamma in jump_terms: + j = _str_to_tuple(j_str) + ph_pp, _ = _mul_pauli(j, p) + # Hermitian Pauli L, p: Lp has imaginary phase iff they anti-commute, + # and then L p L = -p, contributing -2 gamma p. + if abs(ph_pp.imag) > 0.5: + out[p] = out.get(p, 0.0) + (-2.0 * gamma) + return {kk: v for kk, v in out.items() if v} + + +def _to_str_dict(d): + return {_tuple_to_str(kk): v for kk, v in d.items()} + + +# --- model builders --------------------------------------------------------- + + +def xy_dephasing(L, alpha, gamma): + """Long-range XY model with PBC + Z dephasing.""" + pairs = [ + (a, b, 1.0 / min(b - a, L - b + a) ** alpha) for a in range(L) for b in range(a + 1, L) + ] + kac = sum(j for _, _, j in pairs) / L + pairs = [(a, b, j / kac) for a, b, j in pairs] + h_terms = [] + for a, b, j in pairs: + for q in "XY": + term = ["I"] * L + term[a] = term[b] = q + h_terms.append(("".join(term), j)) + jump_terms = [("I" * i + "Z" + "I" * (L - i - 1), gamma) for i in range(L)] + return h_terms, jump_terms + + +def tfim_xdeph(L, J, h, gamma): + """TFIM (ZZ + transverse X) with X dephasing.""" + h_terms = [] + for i in range(L - 1): + term = ["I"] * L + term[i] = term[i + 1] = "Z" + h_terms.append(("".join(term), J)) + for i in range(L): + term = ["I"] * L + term[i] = "X" + h_terms.append(("".join(term), h)) + jump_terms = [("I" * i + "X" + "I" * (L - i - 1), gamma) for i in range(L)] + return h_terms, jump_terms + + +def nn_xy_z_dephasing_obc(L, J, gamma): + """Nearest-neighbour XY (OBC) + per-site Z dephasing.""" + h_terms = [] + for i in range(L - 1): + a, b = i, i + 1 + xs = ["I"] * L + xs[a] = xs[b] = "X" + ys = ["I"] * L + ys[a] = ys[b] = "Y" + h_terms += [("".join(xs), J), ("".join(ys), J)] + jump_terms = [("I" * j + "Z" + "I" * (L - j - 1), gamma) for j in range(L)] + return h_terms, jump_terms + + +def random_pauli_str(rng, L): + chars = ["I"] * L + positions = rng.choice(L, size=int(rng.integers(1, L + 1)), replace=False) + for q in positions: + chars[q] = rng.choice(["X", "Y", "Z"]) + return "".join(chars) + + +def assert_action_matches(L_op, h_terms, jump_terms, strings): + """Compare `L_op.action(p)` against :func:`_reference_action` for each `p`.""" + for p in strings: + got = L_op.action(p) + want = _to_str_dict(_reference_action(p, h_terms, jump_terms)) + for kk in set(got) | set(want): + assert abs(got.get(kk, 0.0) - want.get(kk, 0.0)) < 1e-12, ( + f"action mismatch at p={p!r} k={kk!r}: " + f"shim={got.get(kk, 0.0)} ref={want.get(kk, 0.0)}" + ) + + +# --- dense Liouvillian reference (for non-Hermitian jumps) ------------------ + +_DENSE_PAULI = { + "I": np.eye(2, dtype=complex), + "X": np.array([[0, 1], [1, 0]], dtype=complex), + "Y": np.array([[0, -1j], [1j, 0]], dtype=complex), + "Z": np.array([[1, 0], [0, -1]], dtype=complex), +} +SIGMA_MINUS_MAT = np.array([[0, 0], [1, 0]], dtype=complex) +SIGMA_PLUS_MAT = np.array([[0, 1], [0, 0]], dtype=complex) + + +def pauli_mat(s): + """Dense matrix for Pauli string ``s`` (leftmost char = leftmost factor).""" + M = np.array([[1.0]], dtype=complex) + for c in s: + M = np.kron(M, _DENSE_PAULI[c]) + return M + + +def all_strings(L): + if L == 0: + return [""] + sub = all_strings(L - 1) + return [c + s for c in "IXYZ" for s in sub] + + +def dense_action(H, jumps, p_str, L): + """`L*(p)` computed densely, returned as a real Pauli-coefficient dict.""" + p_mat = pauli_mat(p_str) + # macOS Accelerate emits spurious divide warnings on exact zeros. + with np.errstate(divide="ignore", invalid="ignore", over="ignore"): + out_mat = 1j * (H @ p_mat - p_mat @ H) + for Lop, gamma in jumps: + Ld = Lop.conj().T + out_mat += gamma * ( + Ld @ p_mat @ Lop - 0.5 * (Ld @ Lop @ p_mat + p_mat @ Ld @ Lop) + ) + d = 2**L + out = {} + for q_str in all_strings(L): + coef = np.trace(pauli_mat(q_str) @ out_mat) / d + assert abs(coef.imag) < 1e-9, f"non-real coefficient for {q_str}: {coef}" + if abs(coef.real) > 1e-12: + out[q_str] = coef.real + return out + + +def embed_op(op_1q, site, L): + """Embed a single-qubit dense operator at ``site`` of an L-qubit register.""" + eye = _DENSE_PAULI["I"] + M = np.array([[1.0]], dtype=complex) + for j in range(L): + M = np.kron(M, op_1q if j == site else eye) + return M + + +# --- closed bilinear evolution for NN-XY + Z-dephasing (OBC) ---------------- + + +def bilinear_nn_xy_z_dephasing_obc(L, J, gamma, times, site0): + """Closed bilinear evolution of `C_j(t)` for the NN XY + Z-dephasing model + with open boundary conditions. + + `F_{mn}(t) = 2^{-L} Tr[B_{mn}(t) Z_i]` evolves as + `∂_t F_{mn} = i·2J·(F_{m+1,n}+F_{m-1,n}-F_{m,n+1}-F_{m,n-1}) - 4γ(1-δ_{mn})F_{mn}` + on the L×L lattice; OBC means edge terms (m=0 or m=L-1, etc.) drop. + Z_j = I - 2 n_j gives C_j = -2 F_{jj}. + """ + dim = L * L + + def idx(m, n): + return m * L + n + + gen = np.zeros((dim, dim), dtype=complex) + for m in range(L): + for n in range(L): + row = idx(m, n) + if m + 1 < L: + gen[row, idx(m + 1, n)] += 1j * 2 * J + if m - 1 >= 0: + gen[row, idx(m - 1, n)] += 1j * 2 * J + if n + 1 < L: + gen[row, idx(m, n + 1)] += -1j * 2 * J + if n - 1 >= 0: + gen[row, idx(m, n - 1)] += -1j * 2 * J + if m != n: + gen[row, row] += -4 * gamma + + evals, evecs = np.linalg.eig(gen) + evecs_inv = np.linalg.inv(evecs) + f0 = np.zeros(dim, dtype=complex) + f0[idx(site0, site0)] = -0.5 + coeffs = evecs_inv @ f0 + + corr = np.empty((len(times), L)) + diag = [idx(j, j) for j in range(L)] + for nt, t in enumerate(times): + ft = evecs @ (np.exp(evals * t) * coeffs) + corr[nt] = np.real(-2 * ft[diag]) + return corr + + +# --- numpy-only matrix exponential reference -------------------------------- + + +def coo_to_dense(triples, n_basis): + """Build a dense ``(n_basis, n_basis)`` array from COO triples.""" + rows, cols, vals = triples + M = np.zeros((n_basis, n_basis), dtype=float) + M[rows, cols] = vals + return M + + +def expm_mv_dense(M, v): + """``exp(M) @ v`` via numpy eigendecomposition. Independent of the Rust + Al-Mohy & Higham implementation; small bases only. + + The Lindbladian is generally diagonalizable, so + ``M = V diag(λ) V^{-1}`` and ``exp(M) v = V (exp(λ) ⊙ (V^{-1} v))``. + """ + evals, evecs = np.linalg.eig(M) + rhs = np.linalg.solve(evecs, v.astype(complex)) + return np.real(evecs @ (np.exp(evals) * rhs)) + + +# --- adaptive PC evolution reference (used by test_adaptive_pc.py) ---------- + + +def _generator_dense(L_op, basis): + """`L_op.generator(basis)` returns COO triples; convert to dense.""" + return coo_to_dense(L_op.generator(basis), len(basis)) + + +def adaptive_z_correlator(L_op, L, site0, dt, n_steps, tau_add): + """Adaptive Heisenberg-picture evolution of Z_{site0} on a growing basis. + + First-hop only: each step adds the strings from `L_op.leakage(...)`, + then matrix-exponentiates the (small, dense) restricted generator via + numpy eigendecomposition. Local truncation is O(dt²) per step. + """ + z_strings = ["I" * j + "Z" + "I" * (L - j - 1) for j in range(L)] + basis = [z_strings[site0]] + coeffs = np.array([1.0]) + protected = [z_strings[site0]] + + corr = np.zeros((n_steps + 1, L)) + corr[0, site0] = 1.0 + + for step in range(n_steps): + leak = L_op.leakage(basis, coeffs, protected=protected) + new = [k for k, v in leak.items() if abs(v) > tau_add] + if new: + basis = basis + new + coeffs = np.concatenate([coeffs, np.zeros(len(new))]) + M = _generator_dense(L_op, basis) + coeffs = expm_mv_dense(dt * M, coeffs) + index = {s: i for i, s in enumerate(basis)} + for j in range(L): + if z_strings[j] in index: + corr[step + 1, j] = coeffs[index[z_strings[j]]] + return corr + + +def adaptive_z_correlator_pc(L_op, L, site0, dt, n_steps, tau_add): + """Same as :func:`adaptive_z_correlator` but with predictor-corrector + basis expansion: predict, then add the second-hop leakage strings before + redoing the step. Lifts the per-step truncation from O(dt²) to O(dt³). + """ + z_strings = ["I" * j + "Z" + "I" * (L - j - 1) for j in range(L)] + basis = [z_strings[site0]] + coeffs = np.array([1.0]) + protected = [z_strings[site0]] + + corr = np.zeros((n_steps + 1, L)) + corr[0, site0] = 1.0 + + for step in range(n_steps): + leak = L_op.leakage(basis, coeffs, protected=protected) + new = [k for k, v in leak.items() if abs(v) > tau_add] + if new: + basis = basis + new + coeffs = np.concatenate([coeffs, np.zeros(len(new))]) + coeffs_pre = coeffs.copy() + M = _generator_dense(L_op, basis) + coeffs_predict = expm_mv_dense(dt * M, coeffs) + leak2 = L_op.leakage(basis, coeffs_predict, protected=protected) + new2 = [k for k, v in leak2.items() if abs(v) > tau_add] + if new2: + basis = basis + new2 + coeffs_pre = np.concatenate([coeffs_pre, np.zeros(len(new2))]) + M = _generator_dense(L_op, basis) + coeffs = expm_mv_dense(dt * M, coeffs_pre) + index = {s: i for i, s in enumerate(basis)} + for j in range(L): + if z_strings[j] in index: + corr[step + 1, j] = coeffs[index[z_strings[j]]] + return corr diff --git a/ppvm-python/test/lindblad/test_action_generator.py b/ppvm-python/test/lindblad/test_action_generator.py new file mode 100644 index 000000000..b888dffb3 --- /dev/null +++ b/ppvm-python/test/lindblad/test_action_generator.py @@ -0,0 +1,108 @@ +# SPDX-FileCopyrightText: 2026 The PPVM Authors +# SPDX-License-Identifier: Apache-2.0 +"""Cross-checks for :meth:`Lindbladian.action` / :meth:`Lindbladian.generator` +/ :meth:`Lindbladian.leakage` against the Hermitian-Pauli reference built from +the single-qubit Pauli multiplication table. +""" + +from __future__ import annotations + +import numpy as np +import pytest + +from ppvm import Lindbladian + +from ._helpers import ( + _reference_action, + _tuple_to_str, + assert_action_matches, + coo_to_dense, + expm_mv_dense, + random_pauli_str, + tfim_xdeph, + xy_dephasing, +) + + +def test_action_xy_dephasing(): + L = 8 + h_terms, jump_terms = xy_dephasing(L, alpha=1.0, gamma=0.3) + L_op = Lindbladian(L, h_terms, jump_terms) + rng = np.random.default_rng(42) + strings = ["I" * L] + strings += ["I" * i + "Z" + "I" * (L - i - 1) for i in range(L)] + strings += [random_pauli_str(rng, L) for _ in range(20)] + assert_action_matches(L_op, h_terms, jump_terms, strings) + + +def test_action_tfim_xdephasing(): + L = 6 + h_terms, jump_terms = tfim_xdeph(L, J=0.7, h=0.4, gamma=0.2) + L_op = Lindbladian(L, h_terms, jump_terms) + rng = np.random.default_rng(7) + strings = [random_pauli_str(rng, L) for _ in range(30)] + assert_action_matches(L_op, h_terms, jump_terms, strings) + + +def test_generator_leakage_and_expm(): + L = 5 + dt = 0.1 + h_terms, jump_terms = xy_dephasing(L, alpha=1.0, gamma=0.4) + L_op = Lindbladian(L, h_terms, jump_terms) + basis = ["I" * i + "Z" + "I" * (L - i - 1) for i in range(L)] + basis += ["YIYII", "IYIYI", "ZZIII"] + coeffs = np.array([0.5, -0.3, 0.2, 0.4, -0.1, 0.6, 0.2, 0.1]) + + M_shim = coo_to_dense(L_op.generator(basis), len(basis)) + M_ref = np.zeros((len(basis), len(basis))) + index = {p: i for i, p in enumerate(basis)} + for col, p in enumerate(basis): + for r_tuple, v in _reference_action(p, h_terms, jump_terms).items(): + r = _tuple_to_str(r_tuple) + if r in index: + M_ref[index[r], col] += v + assert np.max(np.abs(M_shim - M_ref)) < 1e-12 + + shim_leak = L_op.leakage(basis, coeffs) + ref_leak: dict = {} + for p, cf in zip(basis, coeffs): + for r_tuple, v in _reference_action(p, h_terms, jump_terms).items(): + r = _tuple_to_str(r_tuple) + if r not in index: + ref_leak[r] = ref_leak.get(r, 0.0) + v * cf + ref_leak = {kk: v for kk, v in ref_leak.items() if v} + for kk in set(shim_leak) | set(ref_leak): + assert abs(shim_leak.get(kk, 0.0) - ref_leak.get(kk, 0.0)) < 1e-12 + + c_shim = expm_mv_dense(dt * M_shim, coeffs) + c_ref = expm_mv_dense(dt * M_ref, coeffs) + assert np.allclose(c_shim, c_ref, atol=1e-13) + + +def test_generator_rejects_duplicate_basis(): + """Duplicate basis rows would silently overwrite each other in the + row-index map and produce an incorrect sparse generator. The user-facing + entry point must reject them with a clear ValueError instead. + """ + L = 4 + h_terms, jump_terms = xy_dephasing(L, alpha=1.0, gamma=0.3) + L_op = Lindbladian(L, h_terms, jump_terms) + basis = ["ZIII", "IZII", "ZIII"] # duplicate at rows 0 and 2 + with pytest.raises(ValueError, match=r"duplicate Pauli word at row 0 and row 2"): + L_op.generator(basis) + # pc_step also builds the row index and must reject duplicates. + with pytest.raises(ValueError, match=r"duplicate Pauli word"): + L_op.pc_step(basis, np.ones(len(basis)), 0.01, 1e-10) + + +def test_protected_strings_suppressed(): + L = 4 + h_terms, jump_terms = xy_dephasing(L, alpha=1.0, gamma=0.0) + L_op = Lindbladian(L, h_terms, jump_terms) + basis = ["ZIII"] + coeffs = np.array([1.0]) + leak = L_op.leakage(basis, coeffs) + assert leak, "expected some leakage" + protected_key = next(iter(leak)) + leak2 = L_op.leakage(basis, coeffs, protected=[protected_key]) + assert protected_key not in leak2 diff --git a/ppvm-python/test/lindblad/test_adaptive_pc.py b/ppvm-python/test/lindblad/test_adaptive_pc.py new file mode 100644 index 000000000..83578d979 --- /dev/null +++ b/ppvm-python/test/lindblad/test_adaptive_pc.py @@ -0,0 +1,106 @@ +# SPDX-FileCopyrightText: 2026 The PPVM Authors +# SPDX-License-Identifier: Apache-2.0 +"""End-to-end convergence of the adaptive predictor-corrector evolution +(numpy eigendecomposition reference) against the closed bilinear NN-XY + +Z-dephasing solution. + +For NN interactions the JW bilinears stay closed under the adjoint +Lindbladian, so the spin correlator obeys a tractable L²×L² ODE +(:func:`bilinear_nn_xy_z_dephasing_obc`). OBC keeps this exact; PBC would +introduce a parity-twist that only matches up to 1/L corrections. +""" + +from __future__ import annotations + +from itertools import pairwise + +import numpy as np + +from ppvm import Lindbladian + +from ._helpers import ( + adaptive_z_correlator, + adaptive_z_correlator_pc, + bilinear_nn_xy_z_dephasing_obc, + nn_xy_z_dephasing_obc, +) + + +def test_adaptive_converges_to_nn_xy_z_dephasing_bilinear(): + """Halving dt drives the adaptive shim toward the closed bilinear solution. + + Single-hop has local truncation O(dt²) per step → global error O(T·dt). + """ + L = 4 + J = 1.0 + gamma = 1.0 + site0 = L // 2 + T = 0.05 + tau_add = 1e-12 # tight enough that integrator (T·dt) dominates + + h_terms, jump_terms = nn_xy_z_dephasing_obc(L, J, gamma) + L_op = Lindbladian(L, h_terms, jump_terms) + + errors = [] + final_corr = None + for dt in (0.01, 0.005, 0.0025): + n_steps = round(T / dt) + times = np.arange(n_steps + 1) * dt + exact = bilinear_nn_xy_z_dephasing_obc(L, J, gamma, times, site0) + shim = adaptive_z_correlator(L_op, L, site0, dt, n_steps, tau_add) + # Endpoint comparison only — independent of which step counts we use. + errors.append(float(np.max(np.abs(shim[-1] - exact[-1])))) + if dt == 0.0025: + final_corr = (shim[-1], exact[-1]) + + # Halving dt should roughly halve the error; allow 2× slack. + assert errors[1] < 0.8 * errors[0], f"dt-halving did not help: {errors}" + assert errors[2] < 0.8 * errors[1], f"dt-halving did not help: {errors}" + + # Integrator floor at dt = 0.0025 is ~T·dt = 1.25e-4; expect <1e-3. + assert errors[-1] < 1e-3, ( + f"shim vs bilinear at smallest dt: max abs error = {errors[-1]:.3g}; " + f"shim={final_corr[0]}, exact={final_corr[1]}" + ) + + +def test_predictor_corrector_lifts_dt_scaling_to_cubic(): + """The predictor-corrector basis expansion lifts the single-hop scheme's + local O(dt²) truncation to O(dt³). PC error is also strictly smaller at + every dt we test. + """ + L = 4 + J = 1.0 + gamma = 1.0 + site0 = L // 2 + T = 0.05 + tau_add = 1e-12 + + h_terms, jump_terms = nn_xy_z_dephasing_obc(L, J, gamma) + L_op = Lindbladian(L, h_terms, jump_terms) + + err_single = [] + err_pc = [] + for dt in (0.01, 0.005, 0.0025): + n_steps = round(T / dt) + times = np.arange(n_steps + 1) * dt + exact = bilinear_nn_xy_z_dephasing_obc(L, J, gamma, times, site0) + single = adaptive_z_correlator(L_op, L, site0, dt, n_steps, tau_add) + pc = adaptive_z_correlator_pc(L_op, L, site0, dt, n_steps, tau_add) + err_single.append(float(np.max(np.abs(single[-1] - exact[-1])))) + err_pc.append(float(np.max(np.abs(pc[-1] - exact[-1])))) + + # PC strictly more accurate than single-hop at every dt (by ~100× in this + # regime). Threshold loose enough to absorb expm_multiply tolerance noise. + for s, p, dt in zip(err_single, err_pc, (0.01, 0.005, 0.0025)): + assert p < s / 50, ( + f"PC ({p:.3e}) not meaningfully better than single-hop ({s:.3e}) at dt={dt}" + ) + + # dt-scaling one order steeper: halving dt should drop the error ~8× + # (dt³ vs single-hop's ~4×). Require >5× per halving with safety margin. + for prev, curr in pairwise(err_pc): + assert curr < prev / 5, f"PC dt-halving ratio < 5: errors {err_pc}" + + # Smallest-dt PC error should sit at FP noise of the bilinear reference. + assert err_pc[-1] < 1e-7, f"PC at smallest dt: error = {err_pc[-1]:.3e}" diff --git a/ppvm-python/test/lindblad/test_non_hermitian_jumps.py b/ppvm-python/test/lindblad/test_non_hermitian_jumps.py new file mode 100644 index 000000000..e0170a567 --- /dev/null +++ b/ppvm-python/test/lindblad/test_non_hermitian_jumps.py @@ -0,0 +1,106 @@ +# SPDX-FileCopyrightText: 2026 The PPVM Authors +# SPDX-License-Identifier: Apache-2.0 +"""Non-Hermitian dissipators: cross-check :meth:`Lindbladian.action` / +:meth:`Lindbladian.generator` / :meth:`Lindbladian.leakage` against the dense +2^L × 2^L Liouvillian reference. Only viable for L ≤ 3. +""" + +from __future__ import annotations + +import numpy as np + +from ppvm import Lindbladian, sigma_minus, sigma_plus + +from ._helpers import ( + SIGMA_MINUS_MAT, + SIGMA_PLUS_MAT, + all_strings, + coo_to_dense, + dense_action, + embed_op, + pauli_mat, + random_pauli_str, +) + + +def test_amplitude_damping_action(): + L = 3 + gamma = 0.5 + h_terms = [("XXI", 1.0), ("IXX", 0.7), ("ZIZ", 0.3)] + jump_terms = [(sigma_minus(i, L), gamma) for i in range(L)] + L_op = Lindbladian(L, h_terms, jump_terms) + + H = sum(c * pauli_mat(s) for s, c in h_terms) + jumps_dense = [(embed_op(SIGMA_MINUS_MAT, i, L), gamma) for i in range(L)] + + rng = np.random.default_rng(11) + strings = ["III", "ZII", "IZI", "IIZ", "XYZ", "YYZ"] + strings += [random_pauli_str(rng, L) for _ in range(10)] + + for p in strings: + got = L_op.action(p) + want = dense_action(H, jumps_dense, p, L) + for k in set(got) | set(want): + diff = abs(got.get(k, 0.0) - want.get(k, 0.0)) + assert diff < 1e-10, ( + f"sigma_minus action mismatch at p={p!r} k={k!r}: " + f"shim={got.get(k, 0.0)} ref={want.get(k, 0.0)} diff={diff}" + ) + + +def test_thermal_excitation_damping_action(): + """σ⁺ + σ⁻ jumps together (thermal bath at finite temperature).""" + L = 2 + h_terms = [("XX", 1.0), ("ZI", 0.2), ("IZ", 0.1)] + jump_terms = [(sigma_minus(i, L), 0.4) for i in range(L)] + [ + (sigma_plus(i, L), 0.1) for i in range(L) + ] + L_op = Lindbladian(L, h_terms, jump_terms) + + H = sum(c * pauli_mat(s) for s, c in h_terms) + jumps_dense = [(embed_op(SIGMA_MINUS_MAT, i, L), 0.4) for i in range(L)] + [ + (embed_op(SIGMA_PLUS_MAT, i, L), 0.1) for i in range(L) + ] + + for p in all_strings(L): + got = L_op.action(p) + want = dense_action(H, jumps_dense, p, L) + for k in set(got) | set(want): + diff = abs(got.get(k, 0.0) - want.get(k, 0.0)) + assert diff < 1e-10, ( + f"sigma_plus/sigma_minus action mismatch at p={p!r} k={k!r}: " + f"shim={got.get(k, 0.0)} ref={want.get(k, 0.0)}" + ) + + +def test_amplitude_damping_generator_and_leakage(): + L = 3 + gamma = 0.3 + h_terms = [("XXI", 0.5), ("IXX", 0.5), ("ZII", 0.2), ("IZI", 0.2), ("IIZ", 0.2)] + jump_terms = [(sigma_minus(0, L), gamma), (sigma_minus(2, L), gamma)] + L_op = Lindbladian(L, h_terms, jump_terms) + + basis = ["III", "ZII", "IZI", "IIZ", "ZZI", "IZZ"] + coeffs = np.array([0.1, 0.5, -0.3, 0.4, 0.2, -0.1]) + + H = sum(c * pauli_mat(s) for s, c in h_terms) + jumps_dense = [(embed_op(SIGMA_MINUS_MAT, i, L), gamma) for i in (0, 2)] + + M_shim = coo_to_dense(L_op.generator(basis), len(basis)) + M_ref = np.zeros((len(basis), len(basis))) + idx = {p: i for i, p in enumerate(basis)} + leak_ref: dict = {} + for col, p in enumerate(basis): + action_p = dense_action(H, jumps_dense, p, L) + for q, v in action_p.items(): + if q in idx: + M_ref[idx[q], col] += v + else: + leak_ref[q] = leak_ref.get(q, 0.0) + v * coeffs[col] + assert np.max(np.abs(M_shim - M_ref)) < 1e-10 + + leak_shim = L_op.leakage(basis, coeffs) + leak_ref = {k: v for k, v in leak_ref.items() if abs(v) > 1e-14} + for k in set(leak_shim) | set(leak_ref): + diff = abs(leak_shim.get(k, 0.0) - leak_ref.get(k, 0.0)) + assert diff < 1e-10, f"leakage mismatch at k={k!r}: diff={diff}" diff --git a/ppvm-python/test/lindblad/test_pc_step_rust.py b/ppvm-python/test/lindblad/test_pc_step_rust.py new file mode 100644 index 000000000..6332f1959 --- /dev/null +++ b/ppvm-python/test/lindblad/test_pc_step_rust.py @@ -0,0 +1,118 @@ +# SPDX-FileCopyrightText: 2026 The PPVM Authors +# SPDX-License-Identifier: Apache-2.0 +"""Pure-Rust :meth:`Lindbladian.pc_step` (Al-Mohy & Higham expm + parallel +SpMV): agrees with the numpy-eigendecomp PC reference at FP precision and +shows the same cubic dt-scaling against the bilinear reference. Plus a +sanity check that a length-1 real lincomb routes to the Hermitian fast path. +""" + +from __future__ import annotations + +from itertools import pairwise + +import numpy as np + +from ppvm import Lindbladian + +from ._helpers import ( + adaptive_z_correlator_pc, + bilinear_nn_xy_z_dephasing_obc, + nn_xy_z_dephasing_obc, + random_pauli_str, + xy_dephasing, +) + + +def _adaptive_z_correlator_pc_rust(L_op, L, site0, dt, n_steps, tau_add): + """Same as :func:`_helpers.adaptive_z_correlator_pc` but the per-step PC + work (leakage expansion, predictor expm, second-hop expansion, corrector + expm) all runs in Rust through :meth:`Lindbladian.pc_step`.""" + z_strings = ["I" * j + "Z" + "I" * (L - j - 1) for j in range(L)] + basis = [z_strings[site0]] + coeffs = np.array([1.0]) + protected = [z_strings[site0]] + + corr = np.zeros((n_steps + 1, L)) + corr[0, site0] = 1.0 + + for step in range(n_steps): + basis, coeffs = L_op.pc_step(basis, coeffs, dt, tau_add, protected=protected) + index = {s: i for i, s in enumerate(basis)} + for j in range(L): + if z_strings[j] in index: + corr[step + 1, j] = coeffs[index[z_strings[j]]] + return corr + + +def test_pc_step_rust_matches_python_pc(): + """The pure-Rust PC step agrees with the numpy-eigendecomp PC reference + at FP precision. + + Pins the Rust matrix exponential (Al-Mohy & Higham) against an + independent reference (numpy ``eig``) under the exact same + basis-expansion schedule.""" + L = 4 + J = 1.0 + gamma = 1.0 + site0 = L // 2 + dt = 0.01 + n_steps = 5 + tau_add = 1e-12 + + h_terms, jump_terms = nn_xy_z_dephasing_obc(L, J, gamma) + L_op = Lindbladian(L, h_terms, jump_terms) + + rust = _adaptive_z_correlator_pc_rust(L_op, L, site0, dt, n_steps, tau_add) + py_ref = adaptive_z_correlator_pc(L_op, L, site0, dt, n_steps, tau_add) + + diff = float(np.max(np.abs(rust - py_ref))) + assert diff < 1e-10, f"Rust PC differs from numpy-eigendecomp PC by {diff:.3e}" + + +def test_pc_step_rust_dt_scaling_is_cubic(): + """End-to-end: the Rust-only PC step matches the bilinear reference with + cubic dt-scaling, confirming the Rust matrix exponential is not the + accuracy bottleneck.""" + L = 4 + J = 1.0 + gamma = 1.0 + site0 = L // 2 + T = 0.05 + tau_add = 1e-12 + + h_terms, jump_terms = nn_xy_z_dephasing_obc(L, J, gamma) + L_op = Lindbladian(L, h_terms, jump_terms) + + err = [] + for dt in (0.01, 0.005, 0.0025): + n_steps = round(T / dt) + times = np.arange(n_steps + 1) * dt + exact = bilinear_nn_xy_z_dephasing_obc(L, J, gamma, times, site0) + rust = _adaptive_z_correlator_pc_rust(L_op, L, site0, dt, n_steps, tau_add) + err.append(float(np.max(np.abs(rust[-1] - exact[-1])))) + + # Halving dt should drop the error by ≥5× (cubic gives 8×). + for prev, curr in pairwise(err): + assert curr < prev / 5, f"Rust PC dt-halving ratio < 5: errors {err}" + assert err[-1] < 1e-7, f"Rust PC tight-dt error too large: {err[-1]:.3e}" + + +def test_lincomb_single_term_matches_hermitian_fast_path(): + """A length-1 real lincomb should route to the Hermitian fast path and + produce numerically identical results to passing the string directly.""" + L = 4 + h_terms, jump_simple = xy_dephasing(L, alpha=1.0, gamma=0.3) + L_simple = Lindbladian(L, h_terms, jump_simple) + # Same operator, expressed as a length-1 complex lincomb. + jump_lincomb = [([(s, 1.0 + 0.0j)], g) for s, g in jump_simple] + L_lincomb = Lindbladian(L, h_terms, jump_lincomb) + + rng = np.random.default_rng(99) + for _ in range(5): + p = random_pauli_str(rng, L) + got_a = L_simple.action(p) + got_b = L_lincomb.action(p) + for k in set(got_a) | set(got_b): + assert got_a.get(k, 0.0) == got_b.get(k, 0.0), ( + f"lincomb fast path mismatch at p={p!r}: {got_a} vs {got_b}" + ) diff --git a/ppvm-python/uv.lock b/ppvm-python/uv.lock index 7fd0de56a..3878b0a48 100644 --- a/ppvm-python/uv.lock +++ b/ppvm-python/uv.lock @@ -15,37 +15,18 @@ resolution-markers = [ "python_full_version < '3.11'", ] -[[package]] -name = "aiobotocore" -version = "3.7.0" -source = 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