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Computational Physics
The use of computation and simulation has become an essential part of the scientific process. Being able to transform a theory into an algorithm requires significant theoretical insight, detailed physical and mathematical understanding, and a working level of competency in programming. This upper-division text provides an unusually broad survey of the topics of modern computational physics from a multidisciplinary, computational science point of view. Its philosophy is rooted in learning by doing (assisted by many model programs), with new scientific materials as well as with the Python programming language. Python has become very popular, particularly for physics education and large scienti...
Quantum Mechanics II
Here is a readable and intuitive quantum mechanics text that covers scattering theory, relativistic quantum mechanics, and field theory. This expanded and updated Second Edition - with five new chapters - emphasizes the concrete and calculable over the abstract and pure, and helps turn students into researchers without diminishing their sense of wonder at physics and nature. As a one-year graduate-level course, Quantum Mechanics II: A Second Course in Quantum Theory leads from quantum basics to basic field theory, and lays the foundation for research-oriented specialty courses. Used selectively, the material can be tailored to create a one-semester course in advanced topics. In either case, it addresses a broad audience of students in the physical sciences, as well as independent readers - whether advanced undergraduates or practicing scientists.
A Survey of Computational Physics
Computational physics is a rapidly growing subfield of computational science, in large part because computers can solve previously intractable problems or simulate natural processes that do not have analytic solutions. The next step beyond Landau's First Course in Scientific Computing and a follow-up to Landau and Páez's Computational Physics, this text presents a broad survey of key topics in computational physics for advanced undergraduates and beginning graduate students, including new discussions of visualization tools, wavelet analysis, molecular dynamics, and computational fluid dynamics. By treating science, applied mathematics, and computer science together, the book reveals how this knowledge base can be applied to a wider range of real-world problems than computational physics texts normally address. Designed for a one- or two-semester course, A Survey of Computational Physics will also interest anyone who wants a reference on or practical experience in the basics of computational physics. Accessible to advanced undergraduates Real-world problem-solving approach Java codes and applets integrated with text Companion Web site includes videos of lectures
Computational Physics
This second edition increases the universality of the previous edition by providing all its codes in the Java language, whose compiler and development kit are available for free for essentially all operating systems. In addition, the accompanying CD provides many of the same codes in Fortran 95, Fortran 77, and C, for even more universal application, as well as MPI codes for parallel applications. The book also includes new materials on trial-and-error search techniques, IEEE floating point arithmetic, probability and statistics, optimization and tuning in multiple languages, parallel computing with MPI, JAMA the Java matrix library, the solution of simultaneous nonlinear equations, cubic splines, ODE eigenvalue problems, and Java plotting programs. From the reviews of the first edition: "Landau and Paez's book would be an excellent choice for a course on computational physics which emphasizes computational methods and programming." - American Journal of Physics
Computational Problems for Physics
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 lan...
A First Course in Scientific Computing
This book offers a new approach to introductory scientific computing. It aims to make students comfortable using computers to do science, to provide them with the computational tools and knowledge they need throughout their college careers and into their professional careers, and to show how all the pieces can work together. Rubin Landau introduces the requisite mathematics and computer science in the course of realistic problems, from energy use to the building of skyscrapers to projectile motion with drag. He is attentive to how each discipline uses its own language to describe the same concepts and how computations are concrete instances of the abstract. Landau covers the basics of comput...
Introduction to Python for Science and Engineering
Introduction to Python for Science and Engineering offers a quick and incisive introduction to the Python programming language for use in any science or engineering discipline. The approach is pedagogical and “bottom up,” which means starting with examples and extracting more general principles from that experience. No prior programming experience is assumed. Readers will learn the basics of Python syntax, data structures, input and output, conditionals and loops, user-defined functions, plotting, animation, and visualization. They will also learn how to use Python for numerical analysis, including curve fitting, random numbers, linear algebra, solutions to nonlinear equations, numerical...
A Scientist's and Engineer's Guide to Workstations and Supercomputers
A scientist’s and engineer’s guide to Workstations and Supercomputers Crack the Unix code and put its power to work for you. If you’re seeking such clear-cut guidance, your search will end with the first Unix survival manual designed specifically for practicing scientists and engineers like you. Avoiding the narrower concerns and complicated jargon of computer science, this guide shows you how to master the complexities of accomplishing computer projects—from start to finish—predominantly under a Unix operating system. With the help of clarifying examples and tutorials, you’ll learn how to write and organize files and programs as well as run, debug, and visualize the results of s...
The End of Strategic Stability?
During the Cold War, many believed that the superpowers shared a conception of strategic stability, a coexistence where both sides would compete for global influence but would be deterred from using nuclear weapons. In actuality, both sides understood strategic stability and deterrence quite differently. Today’s international system is further complicated by more nuclear powers, regional rivalries, and nonstate actors who punch above their weight, but the United States and other nuclear powers still cling to old conceptions of strategic stability. The purpose of this book is to unpack and examine how different states in different regions view strategic stability, the use or non-use of nucl...
Computational Modeling and Visualization of Physical Systems with Python
Computational Modeling, by Jay Wang introduces computational modeling and visualization of physical systems that are commonly found in physics and related areas. The authors begin with a framework that integrates model building, algorithm development, and data visualization for problem solving via scientific computing. Through carefully selected problems, methods, and projects, the reader is guided to learning and discovery by actively doing rather than just knowing physics.
