{"title":"Series In Computational Physics","description":"\u003cp\u003eExplore the complexities of physics through a computational lens. This series offers deep dives into methodologies and applications, perfect for researchers and students alike. Enhance your understanding today.\u003c\/p\u003e","products":[{"product_id":"introduction-to-numerical-programming-book-titus-a-beu-9781466569676","title":"Introduction to Numerical Programming","description":"Makes Numerical Programming More Accessible to a Wider Audience  Bearing in mind the evolution of modern programming, most specifically emergent programming languages that reflect modern practice, Numerical Programming: A Practical Guide for Scientists and Engineers Using Python and C\/C++ utilizes the author’s many years of practical research and teaching experience to offer a systematic approach to relevant programming concepts. Adopting a practical, broad appeal, this user-friendly book offers guidance to anyone interested in using numerical programming to solve science and engineering problems. Emphasizing methods generally used in physics and engineering—from elementary methods to complex algorithms—it gradually incorporates algorithmic elements with increasing complexity.  Develop a Combination of Theoretical Knowledge, Efficient Analysis Skills, and Code Design Know-How  The book encourages algorithmic thinking, which is essential to numerical analysis. Establishing the fundamental numerical methods, application numerical behavior and graphical output needed to foster algorithmic reasoning, coding dexterity, and a scientific programming style, it enables readers to successfully navigate relevant algorithms, understand coding design, and develop efficient programming skills. The book incorporates real code, and includes examples and problem sets to assist in hands-on learning.          Begins with an overview on approximate numbers and programming in Python and C\/C++, followed by discussion of basic sorting and indexing methods, as well as portable graphic functionality Contains methods for function evaluation, solving algebraic and transcendental equations, systems of linear algebraic equations, ordinary differential equations, and eigenvalue problems Addresses approximation of tabulated functions, regression, integration of one- and multi-dimensional functions by classical and Gaussian quadratures, Monte Carlo integration techniques, generation of random variables, discretization methods for ordinary and partial differential equations, and stability analysis  This text introduces platform-independent numerical programming using Python and C\/C++, and appeals to advanced undergraduate and graduate students in natural sciences and engineering, researchers involved in scientific computing, and engineers carrying out applicative calculations.","brand":"WoB","offers":[{"title":"US \/ GOOD \/ SBYB","offer_id":50376034189585,"sku":"CIN1466569670G","price":0.0,"currency_code":"GBP","in_stock":false},{"title":"GB \/ NEW \/ INGRAM","offer_id":52334311440657,"sku":"NLS9781466569676","price":0.0,"currency_code":"GBP","in_stock":true},{"title":"US \/ NEW \/ INGRAM","offer_id":53558755623185,"sku":"NIN9781466569676","price":0.0,"currency_code":"GBP","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0784\/4072\/6801\/files\/B01MZ728YS.jpg?v=1751404695"},{"product_id":"computational-problems-for-physics-book-rubin-h-landau-9781138705418","title":"Computational Problems for Physics","description":"Our future scientists and professionals must be conversant in computational techniques. In order to facilitate integration of computer methods into existing physics courses, this textbook offers a large number of worked examples and problems with fully guided solutions in Python as well as other languages (Mathematica, Java, C, Fortran, and Maple). It’s also intended as a self-study guide for learning how to use computer methods in physics. The authors include an introductory chapter on numerical tools and indication of computational and physics difficulty level for each problem. Readers also benefit from the following features:  • Detailed explanations and solutions in various coding languages.  • Problems are ranked based on computational and physics difficulty.  • Basics of numerical methods covered in an introductory chapter.  • Programming guidance via flowcharts and pseudocode.  Rubin Landau is a Distinguished Professor Emeritus in the Department of Physics at Oregon State University in Corvallis and a Fellow of the American Physical Society (Division of Computational Physics).  Manuel Jose Paez-Mejia is a Professor of Physics at Universidad de Antioquia in Medellín, Colombia.","brand":"WoB","offers":[{"title":"- \/ - \/ -","offer_id":50555256242449,"sku":"","price":0.0,"currency_code":"GBP","in_stock":true},{"title":"GB \/ VERY_GOOD \/ INTERNAL","offer_id":50555257454865,"sku":"GOR013994033","price":0.0,"currency_code":"GBP","in_stock":false},{"title":"GB \/ NEW \/ INGRAM","offer_id":52145423450385,"sku":"NLS9781138705418","price":0.0,"currency_code":"GBP","in_stock":true},{"title":"US \/ NEW \/ INGRAM","offer_id":53109401452817,"sku":"NIN9781138705418","price":0.0,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0784\/4072\/6801\/files\/1138705411.jpg?v=1751400712"},{"product_id":"introduction-to-python-for-science-and-engineering-book-david-j-pine-9781138583894","title":"Introduction to Python for Science and Engineering","description":"Series in Computational Physics Steven A. Gottlieb and Rubin H. Landau, Series Editors  Introduction to Python for Science and Engineering  This guide offers a quick and incisive introduction to Python programming for anyone. The author has carefully developed a concise approach to using Python in any discipline of science and engineering, with plenty of examples, practical hints, and insider tips.  Readers will see why Python is such a widely appealing program, and learn the basics of syntax, data structures, input and output, plotting, conditionals and loops, user-defined functions, curve fitting, numerical routines, animation, and visualization. The author teaches by example and assumes no programming background for the reader.  David J. Pine is the Silver Professor and Professor of Physics at New York University, and Chair of the Department of Chemical and Biomolecular Engineering at the NYU Tandon School of Engineering. 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Computational examples in Python programming language guide students on how to simulate and visualize thermodynamic principles and processes for themselves.","brand":"WoB","offers":[{"title":"GB \/ NEW \/ GARDNERS","offer_id":50698530750737,"sku":"NGR9781032257563","price":0.0,"currency_code":"GBP","in_stock":false},{"title":"US \/ NEW \/ INGRAM","offer_id":51017574318353,"sku":"NIN9781032257563","price":0.0,"currency_code":"GBP","in_stock":false},{"title":"GB \/ NEW \/ INGRAM","offer_id":52586162979089,"sku":"NLS9781032257563","price":0.0,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0784\/4072\/6801\/files\/1032257563.jpg?v=1750822286"},{"product_id":"electrodynamics-tutorials-with-python-simulations-book-taejoon-kouh-9781032502311","title":"Electrodynamics Tutorials with Python Simulations","description":"This book provides an accessible introduction to intermediate-level electrodynamics with computa- tional approaches to complement a traditional mathematical treatment of the subject. 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The author clarifies the role of different variables and sequences throughout, avoids excessive mathematical detail, emphasizes graphical representations, and highlights illustrative applications in materials science, biology, and biochemistry. The text also presents tips for speeding up calculations and parallelization techniques based on OpenMP. 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Each chapter is about a different model and contains a complete description, together with the algorithm and the result of the operation. There is no mathematics extended to its limits. The book provides a complete description, allowing readers to implement the algorithm themselves. The artificial intelligence (AI) elements in the book relate to the computer implementation and the programs that have been generated on the basis of the algorithms written. The results of these programs have been used as illustrations in the book. The book is mainly of use to graduate students working in computational physics, biology, chemistry, and computer science.  Key Features:    Provides a large collection of very diverse models, the compilation of which is unique Includes elements of AI and the use of large language models (LLM). 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