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Matrix Collection in Material Science

Collection of sparse Hamiltonian matrices that appears in material science, such as electronic structure and quantum lattice models. Several data sets contain eigenvalues and eigenvectors, as well as the matrix data.

Robust analytic continuation using sparse modeling approach imposed by semi-positive definiteness for multi-orbital systems

A dataset of the spectral functions and the corresponding Green's functions for multiple orbital electron systems used for numerical demonstrations of analytic continuation methods

Monte Carlo database on quantum spin models

Collection of Monte Carlo simulation results on quantum spin models. Currently includes S=1/2 and S=1 antiferromagnetic Heisenberg model in 1 and 2 dimensions.

Moller Gallery

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.

Data set for Noise reduction of coherent diffraction image data using deep learning method

Single-shot imaging with femtosecond X-ray lasers is a powerful measurement technique that can achieve both high spatial and temporal resolution. However, its accuracy has been severely limited by the difficulty of applying conventional background processing. In this data repository, sample codes, training dataset and learned model for deep learning method which was used to validate noise reduction techniques are provided.

Electronic band structure change with structural transition of buckled Au₂X monolayers induced by strain

This study investigates the structural transitions of η ↔ θ and the changes in electronic band structures of Au₂X (X=S, Se, Te, Si, Ge) and Au₄SSe induced by strain.
This database provides the input files and the results of the DFT calculations by OpenMX.

Dataset for Ab initio study of TMTTF$_2$PF$_6$ under pressure: implications to the unified phase diagram

This data repository provides a comprehensive dataset related to the theoretical study of TMTTF$2$PF$6$ crystal structures at high pressures (0-8 GPa) analyzed by single crystal X-ray diffraction and diamond anvil cells. This repository provides the data, including input and output data for ab initio calculations by Quantum ESPRESSO, downfolding by RESPACK, calculating Fermi surface and irreducible susceptibilities by H-wave,and many-variable variational Monte Carlo calculation by mVMC.

GeO2_glass_NNP

Project URL：https://isspns-gitlab.issp.u-tokyo.ac.jp/skasamatsu/GeO2_glass_NNP
Update Date：2024-11-06 18:38:37

spmac_multi

Project URL：https://isspns-gitlab.issp.u-tokyo.ac.jp/y-motoyama/spmac_multi
Update Date：2024-09-04 17:45:44

Monte Carlo database on quantum spin models

Project URL：https://isspns-gitlab.issp.u-tokyo.ac.jp/kawashima/monte-carlo-database-on-quantum-spin-models
Update Date：2024-06-20 13:37:40

moller-gallery

Project URL：https://isspns-gitlab.issp.u-tokyo.ac.jp/htp-tools-dev/moller-gallery
Update Date：2024-06-10 16:27:30

buckled-Au2X

Project URL：https://isspns-gitlab.issp.u-tokyo.ac.jp/masahiro.fukuda/buckled-Au2X
Update Date：2024-06-05 17:32:26