AI for Physics

Written in accessible language without mathematical formulas, this short book provides an overview of the wide and varied applications of artificial intelligence (AI) across the spectrum of physical sciences. Focusing in particular on AI's ability to extract patterns from data, known as machine learning (ML), the book includes a chapter on important machine learning algorithms and their respective applications in physics. It then explores the use of ML across a number of important sub-fields in more detail, ranging from particle, molecular and condensed matter physics, to astrophysics, cosmology and the theory of everything. The book covers such applications as the search for new particles and the detection of gravitational waves from the merging of black holes, and concludes by discussing what the future may hold.

這本短書以易懂的語言撰寫，不使用數學公式，提供了人工智慧（AI）在物理科學領域中廣泛且多樣化應用的概述。特別聚焦於AI從數據中提取模式的能力，即機器學習（ML），書中包含了一章關於重要的機器學習算法及其在物理學中的應用。接著更詳細地探討了ML在一些重要的子領域中的應用，包括粒子、分子和凝聚態物理學，以及天體物理學、宇宙學和萬物理論。本書涵蓋了尋找新粒子和檢測黑洞合併產生的引力波等應用，最後討論了未來可能的發展。

Volker Knecht, Germany, Editor at International Journal of Molecular Sciences, Science Writer as Freelancer. Diploma in Physics at University of Kaiserslautern, PhD in Theoretical Physics at University of Göttingen, PhD project at MPI Göttingen, postdoc at University of Groningen, group leader and PI at MPI Potsdam and University of Freiburg. Research at the interface between physics, chemistry, biology, and computer science for 17 years.

Volker Knecht，德國人，是《國際分子科學期刊》的編輯，也是自由撰稿人的科學作家。他在凱撒斯勞滕大學獲得物理學學士學位，在哥廷根大學獲得理論物理學博士學位，並在哥廷根的MPI進行博士後研究，之後在格羅寧根大學擔任博士後研究員，並在波茨坦的MPI和弗賴堡大學擔任研究小組組長和PI。他在物理學、化學、生物學和計算機科學的交叉領域進行研究已有17年。