This book comprises a selection of lectures presented at the IUPAP Conference on Computational Physics (CCP2024), held in July 2024 in Thessaloniki, Greece. The meeting highlighted recent research advances across a broad spectrum of physics, with particular emphasis on studies employing computational and simulation-based methodologies. The increasing accessibility of High-Performance Computing (HPC) resources has enabled researchers to address some of the most challenging problems in the field through optimized parallel programming frameworks, including MPI and OpenMP, as well as GPU-accelerated computing. Such approaches have become standard practice in many of the research topics represented in this book.

A prominent feature of the conference was the integration of emerging methodologies based on Artificial Intelligence (AI) and Machine Learning (ML). Contributions demonstrated that these techniques can significantly enhance computational efficiency while maintaining high levels of accuracy. Numerical simulations play a central role in many of the included works, particularly in studies of complex systems employing network theory, advanced HPC strategies, and AI-augmented computational frameworks, as presented by leading researchers in their respective areas.

This book is intended for researchers, practitioners, and graduate students across all areas of Physics, who seek to apply state-of-the-art computational techniques, numerical modeling, computer simulations, and data-driven methods. The individual chapters may also serve as instructional material for graduate-level courses in computational physics, numerical methods, and high-performance computing.

Panos Argyrakis has been a professor at the University of Thessaloniki in Greece. He has studied at the University of Illinois (BS) and the University of Michigan (Ph.D.) in the USA. His field is the Computational Sciences, with a background in Statistical Physics. He has worked extensively in mathematical models of phase transitions in lattices and other condensed matter systems, focusing in disordered systems, low-dimensional systems, and fractals. The key question that he has been concerned with is how is diffusion affected by the inhomogeneity in such systems resulting in a variety of different regimes, e.g., sub-diffusion, super-diffusion, trapping states, crystal growth diffusion models, etc., that are characterized by different critical exponents. Applications of such theories extend to the dynamics of signal transmission in the brain, diffusion of drugs delivered in the gastrointestinal tube, reaction-controlled versus diffusion-controlled chemical reactions, surface catalysis, and many more.