This book presents a unified approach to a rich and rapidly evolving research domain at the interface between statistical physics, theoretical computer science/discrete mathematics, and coding/information theory. It is accessible to graduate students and researchers without a specific training in any of these fields. The selected topics include spin glasses, error correcting codes, satisfiability, and are central to each field. The approach focuses on large random instances and adopts a common probabilistic formulation in terms of graphical models. It presents message passing algorithms like belief propagation and survey propagation, and their use in decoding and constraint satisfaction solving. It also explains analysis techniques like density evolution and the cavity method, and uses them to study phase transitions.
發表於2024-12-19
Information, Physics, and Computation 2024 pdf epub mobi 電子書 下載
圖書標籤: 物理 統計 復雜係統 計算 信息論 信息 算法 物理學
有些難度
評分有些難度
評分Noted to study the idea models in physics.
評分有些難度
評分有些難度
Information, Physics, and Computation 2024 pdf epub mobi 電子書 下載