Deep Learning in Physics: Applications in Quantum Mechanics and High-Energy Physics

by Medhat ullah

Deep Learning in Applications in Quantum Mechanics and High-Energy Physics is a concise, modern guide that bridges cutting-edge AI techniques with the most advanced areas of theoretical physics. This book explores how neural networks, deep architectures, and generative models are transforming quantum systems research, particle-collision analysis, and the search for new physics beyond the Standard Model. Designed for both learners and researchers, it walks through essential concepts with clarity—showing how deep learning accelerates simulations, predicts quantum states, detects rare particle events, and uncovers hidden structures in massive datasets. Whether you're building quantum-aware neural networks, studying LHC data, or simply curious about the intersection of physics and AI, this book gives you a practical, intuitive, and forward-looking roadmap into one of the fastest-growing fields in science.

39 pages, Kindle Edition

Published November 17, 2025