Proceedings of the 35th IUPAP Conference on Computational Physics

CCP2024, July 7-12, Thessaloniki, Greece
Erscheinungsjahr 2026
ISBN: 978-3-032-21972-5
Verlag: Springer Nature Switzerland AG

Buch, Englisch, 368 Seiten, Format (B × H): 155 mm x 235 mm

Reihe: Springer Proceedings in Physics

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.

Zielgruppe

Research

Autoren/Hrsg.

Argyrakis, Panos

Fachgebiete

• Naturwissenschaften Physik Physik Allgemein Theoretische Physik, Mathematische Physik, Computerphysik
• Naturwissenschaften Physik Angewandte Physik Astrophysik
• Naturwissenschaften Physik Quantenphysik
• Interdisziplinäres Wissenschaften Wissenschaften: Forschung und Information Kybernetik, Systemtheorie, Komplexe Systeme
• Naturwissenschaften Physik Thermodynamik Festkörperphysik, Kondensierte Materie

Inhaltsverzeichnis

Hadron Structure Studies within Lattice QCD.- Hadron Interactions in Lattice QCD: Non-Perturbative Studies on Interactions Between Composite Particles.- Equilibrium of a Brownian Particle with Coordinate-Dependent Diffusion: Understanding the Ito Process.- Calculating Collisions in Atomic and Molecular Physics.- Resonant Migration of the Injected Excitation in Donor–Biomolecular Chain Structure.- Representation of Typical Droplet Shapes in 2D Latent Space.- Computational Physics in Strong Gravity: A Tool for Gravitational-Wave Astronomy.- First-Principles Study of Multiple Lithium and Sodium Oxides Effects on 12-borophene Cathode.- Structural, Electronic, and Electron Transport Property of Nickel-doped Porphyrin Two-Terminal Device with Graphene Electrodes.- Deep Learning Detection of New Gravitational Wave Events with AresGW.- Block Sparsity in Physics with State-of-the-art Algorithm Design and Simulation Analysis.- Detection of Regular Rotational Activity During Cardiac Arrhythmia Using the Helmholtz Decomposition for Directed Graphs.- Tensions on Small Scales: Too Many Galaxy-Galaxy Strong Lenses Observed in Galaxy Clusters?.- Application of Quasi Static Approximation Technique to Nonlinear Wakefield Excitation Beam Driven Plasma Acceleration Scheme.- Complex Network Analysis of Global Trade in Strategic Sectors: Fuels, Pharmaceuticals, and Technology Products (2003–2022): Completing the Cross-Sectoral View of Geopolitical Influence.- Economic Cycles, Thermodynamic Uncertainty Relations, and Inflationary Bounds.- Accelerating HiRep Lattice Simulations on CPU-based Computer Clusters.- Estimation of Semimajor Axis of Exoplanet Orbit Using Machine Learning Techniques.- Solving the Forced Korteweg-de Vries Equation Using a Pseudospectral Method in AMReX.- Lightweight Super Resolution Architecture for Reconstruction of Turbulent Micropolar Open Channel Flow Data.- Singular Spectrum Analysis of Time-Series Data from Time-Dependent Density-Functional Theory in Real-Time.

Über Autor(innen)

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.