Adapol: adaptive pole fitting for quantum many-body physics
Adapol (pronouced “add a pole”) is a python package for fitting Matsubara functions with pole expansions.
Current applications include bath fitting and analytic continuation. The name Adapol
is short for adaptive pole fitting.
Getting started
To use Adapol, first install it using pip:
$ pip install adapol
Learn how to use it in the Documentation.
For updates and latest versions, see Github.
References
To cite this work, please include a reference to this GitHub repository, and cite the following references:
Zhen Huang, 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.
Carlos Mejuto-Zaera, et al. “Efficient hybridization fitting for dynamical mean-field theory via semi-definite relaxation.” Physical Review B 101.3 (2020): 035143.
Yuji Nakatsukasa, Olivier Sète, and Lloyd N. Trefethen. “The AAA algorithm for rational approximation.” SIAM Journal on Scientific Computing 40.3 (2018): A1494-A1522.