| Name | adapol JSON |
| Version |
0.1.0
JSON |
| download |
| home_page | None |
| Summary | Adaptive Pole Fitting for Quantum Many-Body Physics |
| upload_time | 2024-07-05 14:36:20 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | >=3.7 |
| license | None |
| keywords |
bath
fitting
hybridization
dmft
matsubara
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
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| coveralls test coverage |
No coveralls.
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# adapol: Adaptive Pole Fitting for Quantum Many-Body Physics
[`adapol`](https://github.com/Hertz4/Adapol) (pronounced "add a pole") is a python package for fitting Matsubara functions with the following form:
```math
G(\mathrm i \omega_k) = \sum_l \frac{V_lV_l^{\dagger}}{\mathrm i\omega_k - E_l}.
```
Current applications include
(1) hybridization fitting, (2) analytic continuation.
We also provide a [TRIQS](https://triqs.github.io/) interface if the Matsubara functions are stored in `triqs` Green's function container.
# Installation
`adapol` has `numpy` and `scipy` as its prerequisites. [`cvxpy`](https://www.cvxpy.org/) is also required for hybridization fitting of matrix-valued (instead of scalar-valued) Matsubara functions.
To install `adapol`, run
```terminal
pip install adapol
```
# Documentation
See the detailed [documentation](https://flatironinstitute.github.io/adapol/) for physical background, algorithms and user manual.
`Adapol` is a stand-alone package. For TRIQS users, we also provide a TRIQS interface. See [user manual](https://flatironinstitute.github.io/adapol/latest/python.html#triqs-interface) for details.
# Examples
In the `tutorial` page, we provide two examples [`discrete.ipynb`](https://flatironinstitute.github.io/adapol/latest/tutorials/discrete.html) and [`semicircle.ipynb`](https://flatironinstitute.github.io/adapol/latest/tutorials/semicircle.html), showcasing how to use `adapol` for both discrete spectrum and continuous spectrum.
In these notebooks, we also demonstrate how to use our code through the triqs interface.
# References
To cite this work, please include a reference to this GitHub repository, and
cite the following references:
1. Huang, Zhen, Emanuel Gull, and Lin Lin. "Robust analytic continuation of Green's functions via projection, pole estimation, and semidefinite relaxation." Physical Review B 107.7 (2023): 075151.
2. Mejuto-Zaera, Carlos, et al. "Efficient hybridization fitting for dynamical mean-field theory via semi-definite relaxation." Physical Review B 101.3 (2020): 035143.
3. Nakatsukasa, Yuji, Olivier Sète, and Lloyd N. Trefethen. "The AAA algorithm for rational approximation." SIAM Journal on Scientific Computing 40.3 (2018): A1494-A1522.
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"description": "# adapol: Adaptive Pole Fitting for Quantum Many-Body Physics\n[`adapol`](https://github.com/Hertz4/Adapol) (pronounced \"add a pole\") is a python package for fitting Matsubara functions with the following form:\n```math\nG(\\mathrm i \\omega_k) = \\sum_l \\frac{V_lV_l^{\\dagger}}{\\mathrm i\\omega_k - E_l}.\n```\n\nCurrent applications include\n(1) hybridization fitting, (2) analytic continuation.\n\nWe also provide a [TRIQS](https://triqs.github.io/) interface if the Matsubara functions are stored in `triqs` Green's function container.\n\n# Installation\n`adapol` has `numpy` and `scipy` as its prerequisites. [`cvxpy`](https://www.cvxpy.org/) is also required for hybridization fitting of matrix-valued (instead of scalar-valued) Matsubara functions.\n\nTo install `adapol`, run\n```terminal\npip install adapol\n```\n\n\n\n# Documentation\n\nSee the detailed [documentation](https://flatironinstitute.github.io/adapol/) for physical background, algorithms and user manual.\n\n`Adapol` is a stand-alone package. For TRIQS users, we also provide a TRIQS interface. See [user manual](https://flatironinstitute.github.io/adapol/latest/python.html#triqs-interface) for details.\n\n# Examples\nIn the `tutorial` page, we provide two examples [`discrete.ipynb`](https://flatironinstitute.github.io/adapol/latest/tutorials/discrete.html) and [`semicircle.ipynb`](https://flatironinstitute.github.io/adapol/latest/tutorials/semicircle.html), showcasing how to use `adapol` for both discrete spectrum and continuous spectrum.\n\nIn these notebooks, we also demonstrate how to use our code through the triqs interface.\n\n# References\nTo cite this work, please include a reference to this GitHub repository, and\ncite the following references:\n\n1. Huang, Zhen, Emanuel Gull, and Lin Lin. \"Robust analytic continuation of Green's functions via projection, pole estimation, and semidefinite relaxation.\" Physical Review B 107.7 (2023): 075151.\n2. Mejuto-Zaera, Carlos, et al. \"Efficient hybridization fitting for dynamical mean-field theory via semi-definite relaxation.\" Physical Review B 101.3 (2020): 035143.\n3. Nakatsukasa, Yuji, Olivier S\u00e8te, and Lloyd N. Trefethen. \"The AAA algorithm for rational approximation.\" SIAM Journal on Scientific Computing 40.3 (2018): A1494-A1522.\n",
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