geometric-intelligence · johmathe · May 7, 2026 · May 7, 2026 · May 7, 2026 · May 7, 2026
diff --git a/.cursorrules b/.cursorrules
diff --git a/.github/workflows/tests.yml b/.github/workflows/tests.yml
@@ -41,4 +41,4 @@ jobs:
         uses: codecov/codecov-action@v5
         with:
           token: ${{ secrets.CODECOV_TOKEN }}
-          slug: geometric-intelligence/bispectrum
+          slug: anonymous/bispectrum
diff --git a/DESIGN.md b/DESIGN.md
diff --git a/README.md b/README.md
@@ -1,10 +1,45 @@
 # bispectrum
 
-[![Tests](https://github.com/geometric-intelligence/bispectrum/actions/workflows/tests.yml/badge.svg)](https://github.com/geometric-intelligence/bispectrum/actions/workflows/tests.yml)
-[![Pre-commit](https://github.com/geometric-intelligence/bispectrum/actions/workflows/pre-commit.yml/badge.svg)](https://github.com/geometric-intelligence/bispectrum/actions/workflows/pre-commit.yml)
-[![codecov](https://codecov.io/github/geometric-intelligence/bispectrum/graph/badge.svg?token=J6GGY4VK1E)](https://codecov.io/github/geometric-intelligence/bispectrum)
+An open-source, fully unit-tested PyTorch library that implements *selective* G-bispectra for seven group actions as differentiable `torch.nn.Module`s, ready to plug into ML pipelines and deep learning architectures.
 
-Bispectrum analysis for machine learning.
+The G-bispectrum is a principled *complete* invariant of a signal — it retains all information up to the group action. Selectivity reduces cost from O(|G|²) to O(|G|) for finite groups, and from O(L³) to Θ(L²) coefficients for SO(3) on S².
+
+## Supported Groups
+
+| Module | Group / Domain | Output mode | Complexity (selective) |
+|--------|---------------|-------------|----------------------|
+| `CnonCn` | C_n on C_n | selective + full | O(n) |
+| `SO2onS1` | SO(2) on S¹ | selective + full | O(n) |
+| `TorusOnTorus` | T^d | selective + full | O(n) |
+| `DnonDn` | D_n on D_n | selective | O(n) |
+| `SO2onDisk` | SO(2) on disk | selective | O(L) |
+| `SO3onS2` | SO(3) on S² | selective + full | Θ(L²) |
+| `OctaonOcta` | chiral octahedral O (24 elements) | selective | 172 coefficients |
+
+`SO2onS1` is the continuous-n limit of `CnonCn` and shares its implementation.
+
+## API
+
+Every module exposes a uniform interface:
+
+- **`forward(f)`** — selective (default) or full bispectral invariants
+- **`fourier(f)`** — group Fourier coefficients
+- **`invert(beta)`** — signal reconstruction up to group-action indeterminacy (where available)
+
+Modules default to O(|G|) selective coefficients; pass `selective=False` for the full O(|G|²) set. CG matrices, DFT kernels, and Bessel roots are precomputed as non-learnable buffers. Dependencies: PyTorch, NumPy, and `torch_harmonics` (for `SO3onS2`).
+
+## Benchmarks
+
+Median wall-clock on a single NVIDIA H100 80 GB GPU (batch=16, `torch.utils.benchmark`):
+
+| Module | Group | \|G\| / L_max | Coefs (sel.) | Coefs (full) | Fwd sel. (ms) | Fwd full (ms) |
+|--------|-------|-----------|------------|-------------|--------------|----------------|
+| `CnonCn` | C_128 | 128 | 128 | 8,256 | 0.14 | 8.53 |
+| `TorusOnTorus` | C_32 × C_32 | 1,024 | 1,024 | 524,800 | 0.07 | 0.31 |
+| `DnonDn` | D_32 | 64 | 245 | — | 0.57 | — |
+| `SO2onDisk` | SO(2) | L=16 | 105 | — | 0.22 | — |
+| `SO3onS2` | SO(3) | L=16 | 430 | — | 0.48 | — |
+| `OctaonOcta` | O | 24 | 172 | — | 0.68 | — |
 
 ## Installation
 
@@ -21,8 +56,6 @@ uv pip install bispectrum
 ### Development
 
 ```bash
-git clone https://github.com/geometric-intelligence/bispectrum.git
-cd bispectrum
 uv pip install -e ".[dev]"
 pre-commit install
 ```
@@ -81,8 +114,6 @@ beta = bsp(f)                 # shape (4, 172), complex64
 f_rec = bsp.invert(beta)      # reconstructed up to group action
 ```
 
-See [DESIGN.md](DESIGN.md) for the full API and all supported groups.
-
 ## License
 
 MIT
diff --git a/benchmarks/figures/bench1_coefficient_count.pdf b/benchmarks/figures/bench1_coefficient_count.pdf
diff --git a/benchmarks/figures/bench1_coefficient_count.png b/benchmarks/figures/bench1_coefficient_count.png
diff --git a/benchmarks/figures/bench2_forward_cpu.pdf b/benchmarks/figures/bench2_forward_cpu.pdf
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diff --git a/benchmarks/figures/bench2_forward_gpu.pdf b/benchmarks/figures/bench2_forward_gpu.pdf
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diff --git a/benchmarks/figures/bench3_inversion_cpu.pdf b/benchmarks/figures/bench3_inversion_cpu.pdf
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diff --git a/benchmarks/figures/table_benchmarks.tex b/benchmarks/figures/table_benchmarks.tex
diff --git a/benchmarks/inversion_results/inversion_convergence.pdf b/benchmarks/inversion_results/inversion_convergence.pdf
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diff --git a/benchmarks/inversion_results/inversion_errors.pdf b/benchmarks/inversion_results/inversion_errors.pdf
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diff --git a/benchmarks/inversion_results/inversion_stats.tex b/benchmarks/inversion_results/inversion_stats.tex
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diff --git a/docs/beamer_slides.pdf b/docs/beamer_slides.pdf