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DGAmore is a Python toolbox that computes the multi-orbital, self-consistent ladder Dynamical Vertex Approximation and solves the Eliashberg equation for (strongly) correlated electron systems described by the multi-band Hubbard model. Starting from the one- and two-particle output of a dynamical mean-field theory (DMFT) calculation, it assembles the local vertex functions, solves the momentum-dependent ladder equations for the non-local self-energy and, optionally, extracts the leading superconducting eigenvalues and gap functions. It relies on vectorized numpy operations, parallelizes the heavy momentum-dependent work with mpi4py, and reads its DMFT input from HDF5 via h5py. It is partially based on DGApy.

For the implemented equations, see the author's Master's thesis (Chapters 3 and 4).

Documentation

Full documentation is hosted at dgamore.readthedocs.io.

Topic	Description
Installation	Environment setup, MPI dependencies, and installing the package.
Usage	Running the routine single-core, with MPI, and on a SLURM cluster.
Configuration	The YAML configuration file and its parameters.
Contributing	Reporting issues and submitting pull requests.
API reference	Module-by-module reference.
About	Background, citation, license, and contact.

Quick start

Install mpich and mpi4py (Python 3.12+ required), then install the package:

conda install -c conda-forge mpich mpi4py
git clone https://github.com/Julpe/DGAmore.git
cd DGAmore
pip install .

Configure a run by editing your configuration file, then execute the routine with -p to point at the directory holding it and -c to name it (defaults: the repository directory and dga_config.yaml):

mpiexec -np 8 DGAmore.py -p /configs/ -c my_config.yaml   # or: DGAmore.py for a single-core test run

See the installation and usage pages for the full instructions and an example SLURM submit script.

Contributing

Contributions are welcome. Please open an issue for bugs and feature requests, or submit a pull request. See CONTRIBUTING.md for details.

Citation and license

DGAmore is released under the MIT license. If you use it, please consider citing it together with the author's Master's thesis. For questions, get in touch by e-mail.