4 papers
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…
Black-box optimization using factorization and Ising machines
Ryo Tamura, Yuya Seki, Yuki Minamoto +4
Black-box optimization (BBO) is used in materials design, drug discovery, and hyperparameter tuning in machine learning. The world is experiencing several of these problems. In thi…
Energy symmetry and interlayer wave function ratio of tunneling electrons in partially overlapped graphene
Ryo Tamura
While the exponential decay of tunneling probability with barrier thickness is well known, the accompanying oscillations with thickness have been comparatively less explored. Using…
CRYSIM: Prediction of Symmetric Structures of Large Crystals with GPU-based Ising Machines
Chen Liang, Diptesh Das, Jiang Guo +3
Solving black-box optimization problems with Ising machines is increasingly common in materials science. However, their application to crystal structure prediction (CSP) is still i…