2DMAT Gallery
| About |
2DMAT is a framework for applying a search algorithm to a direct problem solver to find the optimal solution. As the standard direct problem solver, the experimental data analysis software for two-dimensional material structure analysis is prepared. The direct problem solver gives the deviation between the experimental data and the calculated data obtained under the given parameters such as atomic positions as a loss function used in the inverse problem. The optimal parameters are estimated by minimizing the loss function using a search algorithm. For further use, the original direct problem solver or the search algorithm can be defined by users. In the version 2.0, for solving a direct problem, 2DMAT offers the wrapper of the solver for the total-reflection high-energy positron diffraction (TRHEPD) experiment, sxrd, and leed. As algorithms, it offers the Nelder-Mead method, the grid search method, the Bayesian optimization method, the replica exchange Monte Carlo method, and the population annealing Monte Carlo method. This repository provides the sample data including input and output data for 2DMAT. |
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| URL | https://isspns-gitlab.issp.u-tokyo.ac.jp/2dmat-dev/2dmat-gallery |
| DOI | |
| Authors | Takeo Hoshi , Kazuyoshi Yoshimi , Yuichi Motoyama |
| License | Documents: CC BY 4.0, Codes: GNU General Public License v3.0 or later |
| Category | Machine learning , Others |
| References | |
| Related software | 2DMAT |
| Contact ※Please replace __at__ with @. |
2dmat-dev__at__issp.u-tokyo.ac.jp |
| Note |