Anders Malthe-Sørenssen – författare

This book – specifically developed as a novel textbook on elementary classical mechanics – shows how analytical and numerical methods can be seamlessly integrated to solve physics problems. This approach allows students to solve more advanced and applied problems at an earlier stage and equips them to deal with real-world examples well beyond the typical special cases treated in standard textbooks.Another advantage of this approach is that students are brought closer to the way physics is actually discovered and applied, as they are introduced right from the start to a more exploratory way of understanding phenomena and of developing their physical concepts.While not a requirement, it is advantageous for the reader to have some prior knowledge of scientific programming with a scripting-type language. This edition of the book uses Matlab, and a chapter devoted to the basics of scientific programming with Matlab is included. A parallel edition using Python instead of Matlab is also available.Last but not least, each chapter is accompanied by an extensive set of course-tested exercises and solutions.

This course-based open access textbook delves into percolation theory, examining the physical properties of random media—materials characterized by varying sizes of holes and pores. The focus is on both the mathematical foundations and the computational and statistical methods used in this field. Designed as a practical introduction, the book places particular emphasis on providing a comprehensive set of computational tools necessary for studying percolation theory.Readers will learn how to generate, analyze, and comprehend data and models, with detailed theoretical discussions complemented by accessible computer codes. The book's structure ensures a complete exploration of worked examples, encompassing theory, modeling, implementation, analysis, and the resulting connections between theory and analysis.Beginning with a simplified model system—a model porous medium—whose mathematical theory is well-established, the book subsequently applies the same framework to realistic random systems. Key topics covered include one- and infinite-dimensional percolation, clusters, scaling theory, diffusion in disordered media, and dynamic processes. Aimed at graduate students and researchers, this textbook serves as a foundational resource for understanding essential concepts in modern statistical physics, such as disorder, scaling, and fractal geometry.

This textbook presents the core elements of an introductory electromagnetism course, integrating computational methods throughout the explanations, examples, and exercises. This approach helps students develop stronger problem‑solving skills, enabling them to tackle complex and realistic physics problems earlier than would be possible using only analytical techniques. It promotes creativity, encourages exploration, and equips students with the tools to become active investigators while learning physics.The book’s philosophy is to provide worked examples that demonstrate the full workflow of solving physics problems, from modeling a system and simplifying it to an analytically solvable form to solving the complete model using computational methods. Each theoretical and computational step is clearly explained. Key computational techniques include numerical line, surface, and volume integrals; solutions to Laplace’s and Poisson’s equations; and computational analyses of simple and complex circuits. Laplace’s and Poisson’s equations receive particular emphasis, as the computational tools developed allow students to study complex systems in depth. By applying similar computational methods across different topics, students can identify connections within the theory and build confidence and proficiency.The book offers clear explanations of both analytical and computational techniques and includes a wide range of exercises: discussion questions, skill‑building tutorials, advanced homework problems, and extended projects that combine analytical and computational approaches in rich, contextual settings.

This book – specifically developed as a novel textbook on elementary classical mechanics – shows how analytical and numerical methods can be seamlessly integrated to solve physics problems. This approach allows students to solve more advanced and applied problems at an earlier stage and equips them to deal with real-world examples well beyond the typical special cases treated in standard textbooks.Another advantage of this approach is that students are brought closer to the way physics is actually discovered and applied, as they are introduced right from the start to a more exploratory way of understanding phenomena and of developing their physical concepts.While not a requirement, it is advantageous for the reader to have some prior knowledge of scientific programming with a scripting-type language. This edition of the book uses Matlab, and a chapter devoted to the basics of scientific programming with Matlab is included. A parallel edition using Python instead of Matlab is also available.Last but not least, each chapter is accompanied by an extensive set of course-tested exercises and solutions.

This book – specifically developed as a novel textbook on elementary classical mechanics – shows how analytical and numerical methods can be seamlessly integrated to solve physics problems. This approach allows students to solve more advanced and applied problems at an earlier stage and equips them to deal with real-world examples well beyond the typical special cases treated in standard textbooks.Another advantage of this approach is that students are brought closer to the way physics is actually discovered and applied, as they are introduced right from the start to a more exploratory way of understanding phenomena and of developing their physical concepts.While not a requirement, it is advantageous for the reader to have some prior knowledge of scientific programming with a scripting-type language. This edition of the book uses Python, and a chapter devoted to the basics of scientific programming with Python is included. A parallel edition using Matlab instead of Python is also available.Last but not least, each chapter is accompanied by an extensive set of course-tested exercises and solutions.