Much hope for finding new physics phenomena at microscopic scale relies on the
observations obtained from High Energy Physics experiments, like the ones performed at …

Machine learning techniques are essential tools to compute efficient, yet accurate, force
fields for atomistic simulations. This approach has recently been extended to incorporate …

As the most important solvent, water has been at the center of interest since the advent of
computer simulations. While early molecular dynamics and Monte Carlo simulations had to …

The process of perceiving music involves the transference of environmental physics in the
air to anatomical and physiological interpretations of resonance in the body and …

Due to the increased concern about energy and environmental issues, significant attention
has been paid to the development of large-scale energy storage devices to facilitate the …

Narratives play a vital role in shaping public perceptions and policy on emerging
technologies like quantum technology (QT). However, little is known about the construction …

This work demonstrates a systematic implementation of hybrid quantum-classical
computational methods for investigating corrosion inhibition mechanisms on aluminum …

Abstract Machine learning techniques are essential tools to compute efficient, yet accurate,
force fields for atomistic simulations. This approach has recently been extended to …

This book chapter offers an extensive exploration of how quantum computing is being
applied within the realm of materials science. Chapter focus is specifically centered on its …

抄録 量子コンピュータのアプリケーションとして, 量子力学に支配される原子スケールの微視的な
振る舞いのシミュレーションが注目されており, 材料開発への応用が期待されている. 本稿では …