Proceedings of the 34th IUPAP Conference on Computational Physics: CCP2023, August 4-8, Kobe, Japan

Singapore : Springer Singapore, 2026.

Under the general editorship: Y. Okamoto

This volume presents the Proceedings of the 34th IUPAP Conference on Computational Physics (CCP2023), held in Kobe, Japan on August 4–8, 2023. It offers a collection of peer-reviewed articles that highlight recent developments in computational and simulation research across various areas of physics. Key topics include the use of data science, quantum computing, and machine learning in physics, providing readers with useful perspectives on these emerging approaches. The articles, contributed by researchers in the field, discuss how computational methods are broadening our understanding of physical phenomena and what kinds of future collaborations may develop from ongoing work. This volume serves as a helpful resource for those interested in the current state and possible future directions of computational physics. Suitable for graduate students, researchers, scholars, and practitioners, this volume provides free and unrestricted access to its contents. This is an open access book.

Keywords: statistical physics, Computational biophysics, computational physics, Atomic physics, Lattice Gauge Theory, machine learning, computational astrophysics, data driven science in physics, Computational Plasma Physics, Computational Physics in Condensed Matters, Softmatter Physics, Computational Chemical Physics