Category: Others

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.

Moller is a program to support high-throughput computations, provided as a part of the HTP-tools package. The use of machine learning for predicting material properties and designing substances, known as materials informatics, has gained considerable attention in recent years. The accuracy of machine learning depends heavily on the preparation of appropriate training data. Therefore, the development of tools and environments for the rapid generation of training data is expected to contribute significantly to the advancement of research in materials informatics. Moller generates batch job scripts for supercomputers and clusters, allowing parallel execution of programs under a series of computational conditions, such as parameter parallelism. This repository provides sample inputs and outputs that illustrate the use of Moller.

We propose a multi-impurity method for the bond-weighted tensor renormalization group (BWTRG) to compute the higher-order moment of physical quantities in a two-dimensional system. The replacement of the bond weight with an impurity matrix in a bond-weighted triad tensor network represents a physical quantity such as the magnetization and the energy. We demonstrate that the accuracy of the proposed method is much higher than the conventional tensor renormalization group for the Ising model and the five-state Potts model. Furthermore, we perform the finite-size scaling analysis and observe that the dimensionless quantity characterizing the structure of the fixed point tensor satisfies the same scaling relation in the critical region as the Binder parameter. The estimated critical temperature dependence on the bond dimension indicates that the exponent relating the correlation length to the bond dimension varies continuously with respect to the BWTRG hyperparameter. We find that BWTRG with the optimal hyperparameter is more efficient in terms of computational time than alternative approaches based on the matrix product state in estimating the critical temperature.

Open Data Analysis Tool for Science and Engineering (ODAT-SE) is a framework for applying a search algorithm to a direct problem solver to find the optimal solution. It has been developed by the name 2DMAT, and since version 3.0, it is organized as an open platform for data analysis by modularizing direct problem solvers and search algorithms. This repository is a collection of examples for ODAT-SE.

We study a non-monotonic behavior of the Binder parameter, which appears in discrete spin systems. We show that the Binder parameters of the Potts model are non-monotonic for q = 3 and 4, while they are monotonic for the Ising case (q = 2). Using the Fortuin–Kasteleyn graph representation, we find that the improved estimator of the Binder parameter consists of two terms with values only in the high- and low-temperature regions. The non-monotonic behavior is found to originate from the low-temperature term. With the appropriately defined order parameter, we can reduce the influence of the low-temperature term and, as a result, the non-monotonic behavior can also be reduced. We propose new definitions for the order parameter, which reduces or eliminates the non-monotonic behavior of the Binder parameter in a system for which the improved estimator of the Binder parameter is unknown.

Aging behavior of the scale free network with various parameters. This repository contains all the raw data related to the following paper. "Structural Changes and Percolation Transition in Networks after Aging Processes", R. Sekikawa and H. Watanabe

The behavior of dimensionless quantities defined as ratios of partition functions is analyzed to investigate phase transitions and critical phenomena. At criticality, the universal values of these ratios can be predicted from conformal field theory (CFT) through the modular-invariant partition functions on a torus. We perform numerical calculations using the bond-weighted tensor renormalization group for three two-dimensional models belonging to different universality classes: the Ising model, the three-state Potts model, and the four-state Potts model. The partition-function ratios obey the same finite-size scaling form as the Binder parameter, and their critical values agree well with the universal values predicted by CFT. In the four-state Potts model, we observe logarithmic corrections in the system-size dependence of these ratios.

Data underlying the paper “Building a Research-Software Catalogue with a Coding Agent: From Hackathon Prototype to Public Deployment.” Part 1 contains the 1 September 2026 catalogue snapshot (68 public repository records), derived data for Figure 4, provenance metadata, and validation scripts. Part 2 contains the MateriApps data used in Section 4: metadata for 336 applications, 6,230 documentation pages crawled by 3 August 2026, a 49,485-passage vector index, and retrieval-evaluation outputs. Original data and evaluation outputs are licensed under CC BY 4.0. Copyright in third-party documentation remains with its respective owners.

Data of Monte Carlo Simulations of Active Potts Models