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

2 Aug 2018  ·  Igor Krivenko, Malte Harland ·

We present the $\texttt{SOM}$ analytic continuation package, an efficient implementation of the Stochastic Optimization Method proposed by A. Mishchenko $\textit{et al}$. $\texttt{SOM}$ 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.

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Computational Physics