Complex Photonics

Fundamentals, Spin Glasses, and Optical Computing
Erscheinungsjahr 2026
ISBN: 978-1-107-11052-6
Verlag: Cambridge University Press

Buch, Englisch, 376 Seiten

Driven by advances in data science and machine learning, photonics has evolved rapidly in recent years and has transformed into a highly interdisciplinary field, connecting fundamental research with cutting-edge applications. Inspired by recent Nobel Prizes in Physics in 2021 and 2024, Conti highlights the interplay between photonics and spin glasses, a key concept for understanding the link between photon propagation and complex systems. Beginning with a study of black-body radiation, the book then revisits laser theory using techniques from non-equilibrium statistical mechanics. Through a step-by-step exploration of important photonic experiments, it bridges foundational concepts and advances in optical computing, with a focus on developing efficient hardware for classical and quantum artificial intelligence. This reveals the profound ties between complexity, photonics, and the future of AI technologies. The book will be a valuable resource for advanced undergraduate and graduate students and more practised researchers.

Autoren/Hrsg.

Conti, Claudio

Inhaltsverzeichnis

Part I. Light and Fluids: 1. From Max Planck to Machine Learning; 2. Elements of Linear Optics; 3. Green's Functions; 4. Rays; 5. Photon Fluid Transport; 6. Light Diffusion; 7. Diffusive Random Laser; Part II. Photonic Spin Glasses: 8. Spin Glass Theory and Replica Symmetry Breaking; 9. Modes and Fluctuations in Lasers; 10. The Photonic Spin Glass; 11. Photonic Spin Glass Theory; 12. Photonic Spin Glass Experiments; Part III. Optical Ising Machines: 13. Focusing in Random Media and Transmission Matrix; 14. The Spatial Ising Machine; 15. The Parametron and the Coherent Ising Machine.

Über Autor(innen)

Conti, Claudio
Claudio Conti is Professor of Physics at the Sapienza University of Rome and has published over 250 research articles on topics including complexity, photonic systems, and machine learning. He is the author of the book Quantum Machine Learning (2024).