6 papers
Revisiting spin Hamiltonian parameters in a Kitaev material via Bayesian optimization of magnetization curves
Takahiro Misawa, Ryo Tamura, Kazuyoshi Yoshimi +1
Determining the spin Hamiltonian of a magnetic compound is crucial for understanding its magnetic properties. A standard approach is to derive model parameters from c…
Update of PHYSBO: Improving Usability and Portability of Bayesian Optimization for Physics and Materials Research
Yuichi Motoyama, Kazuyoshi Yoshimi, Tatsumi Aoyama +3
Bayesian optimization (BO) is widely used to accelerate physics and materials research, where objective function evaluations are computationally or experimentally expensive. While…
Semi-automated estimation of hydrogenic initial states for localized Wannier functions
Tatsuki Oikawa, Kota Ido, Takahiro Misawa +2
We present a semi-automated method for obtaining an initial estimate of Wannier functions, designed to facilitate the construction of Wannier functions for describing low-energy ef…
Exploring utilization of generative AI for research and education in data-driven materials science
Takahiro Misawa, Ai Koizumi, Ryo Tamura +1
Generative AI has recently had a profound impact on various fields, including daily life, research, and education. To explore its efficient utilization in data-driven materials sci…
Project For Advancement of Software Usability in Materials Science
Kazuyoshi Yoshimi, Yuichi Motoyama, Tatsumi Aoyama +2
The Institute for Solid State Physics (ISSP) at The University of Tokyo has been carrying out a software development project named ``the Project for Advancement of Software Usabili…
TeNeS-v2: Enhancement for Real-Time and Finite Temperature Simulations of Quantum Many-Body Systems
Yuichi Motoyama, Tsuyoshi Okubo, Kazuyoshi Yoshimi +4
Quantum many-body systems are challenging targets for computational physics due to their large degrees of freedom. The tensor networks, particularly Tensor Product States (TPS) and…