$\texttt{TRIQS}/\texttt{SOM}$: Implementation of the Stochastic Optimization Method for Analytic Continuation

TL;DR

The paper introduces TRIQS/SOM, an open-source software package implementing the Stochastic Optimization Method for analytic continuation, providing a flexible, high-quality alternative to Maximum Entropy methods in condensed matter physics.

Contribution

It offers a new open-source implementation of the Stochastic Optimization Method compatible with TRIQS, supporting various analytic continuation problems in condensed matter physics.

Findings

Efficient implementation of the SOM algorithm in TRIQS/SOM.

Supports multiple representations of response functions including imaginary time, Matsubara frequencies, and Legendre basis.

Provides a user-friendly Python interface for integration with existing computational tools.

Abstract

We present the $\texttt{TRIQS}/\texttt{SOM}$ analytic continuation package, an efficient implementation of the Stochastic Optimization Method proposed by A. Mishchenko et al [Phys. Rev. B $\textbf{62}$, 6317 (2000)]. $\texttt{TRIQS}/\texttt{SOM}$ strives to provide a high quality open source (distributed under the GNU General Public License version 3) alternative to the more widely adopted Maximum Entropy continuation programs. It supports a variety of analytic continuation problems encountered in the field of computational condensed matter physics. Those problems can be formulated in terms of response functions of imaginary time, Matsubara frequencies or in the Legendre polynomial basis representation. The application is based on the $\texttt{TRIQS}$ C++/Python framework, which allows for easy interoperability with $\texttt{TRIQS}$-based quantum impurity solvers, electronic band structure codes and visualization tools. Similar to other $\texttt{TRIQS}$ packages, it comes with a convenient Python interface.