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2DMAT

2DMAT is a framework designed to apply search algorithms to forward problem solvers to find optimal solutions. Users can define the forward problem solvers themselves, and as a standard solver, there is software available for analyzing experimental data aimed at two-dimensional material structure analysis. The implemented search algorithms include the Nelder-Mead method, grid-based search, Bayesian optimization, replica exchange Monte Carlo, and population annealing Monte Carlo methods.

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Official site	https://www.pasums.issp.u-tokyo.ac.jp/2dmat/
Openness	★★★
Manual	https://www.pasums.issp.u-tokyo.ac.jp/2dmat/doc/manual
Download	https://github.com/issp-center-dev/2DMAT/releases
License	GPL v3
Core Developers	Yuichi Motoyama (The Institute for Solid State Physics, The University of Tokyo) Kazuyoshi Yoshimi (The Institute for Solid State Physics, The University of Tokyo) Harumichi Iwamoto (Department of Applied Mathematics and Physics, Tottori University) Takeo Hoshi (Department of Applied Mathematics and Physics, Tottori University)
Availability	Windows, MacOS, Linux
Related Papers	paper on 2DMAT: Y. Motoyama et al., “Data-analysis software framework 2DMAT and<\span> its application to experimental measurements for two-dimensional material structures”, Comp. Phys. Comm., 280, 108465 (2022).
Related Sites	MateriApps: https://ma.issp.u-tokyo.ac.jp/en/app/4999