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This text is the product of several years' effort to develop a course to fill a specific educational gap. It is our belief that computer science students should know how a computer works, particularly in light of rapidly changing tech nologies. The text was designed for computer science students who have a calculus background but have not necessarily taken prior physics courses. However, it is clearly not limited to these students. Anyone who has had first-year physics can start with Chapter 17. This includes all science and engineering students who would like a survey course of the ideas, theories, and experiments that made our modern electronics age possible. This textbook is meant to be used in a two-semester sequence. Chapters 1 through 16 can be covered during the first semester, and Chapters 17 through 28 in the second semester. At Queens College, where preliminary drafts have been used, the material is presented in three lecture periods (50 minutes each) and one recitation period per week, 15 weeks per semester. The lecture and recitation are complemented by a two-hour laboratory period per week for the first semester and a two-hour laboratory period biweekly for the second semester.
Physics is really important to game programmers who need to know how to add physical realism to their games. They need to take into account the laws of physics when creating a simulation or game engine, particularly in 3D computer graphics, for the purpose of making the effects appear more real to the observer or player.The game engine ne
The Physics of Computing gives a foundational view of the physical principles underlying computers. Performance, power, thermal behavior, and reliability are all harder and harder to achieve as transistors shrink to nanometer scales. This book describes the physics of computing at all levels of abstraction from single gates to complete computer systems. It can be used as a course for juniors or seniors in computer engineering and electrical engineering, and can also be used to teach students in other scientific disciplines important concepts in computing. For electrical engineering, the book provides the fundamentals of computing that link core concepts to computing. For computer science, it provides foundations of key challenges such as power consumption, performance, and thermal. The book can also be used as a technical reference by professionals. - Links fundamental physics to the key challenges in computer design, including memory wall, power wall, reliability - Provides all of the background necessary to understand the physical underpinnings of key computing concepts - Covers all the major physical phenomena in computing from transistors to systems, including logic, interconnect, memory, clocking, I/O
Using computers to solve problems and model physical problems has fast become an integral part of undergraduate and graduate education in physics. This 3rd year undergraduate and subsequent graduate course is a supplement to courses in theoretical physics and develops problem-solving techniques using the computer. It makes use of the newest version of Mathematica (3.0) while still remaining compatible with older versions The programs using Mathematica 3.0 and C are written for both PCs and workstations, and the problems, source files, and graphic routines help students gain experience from the very beginning.
Aims to reinforce the interface between physical sciences, theoretical computer science, and discrete mathematics. This book assembles theoretical physicists and specialists of theoretical informatics and discrete mathematics in order to learn about developments in cryptography, algorithmics, and more.
Computer science and physics have been closely linked since the birth of modern computing. In recent years, an interdisciplinary area has blossomed at the junction of these fields, connecting insights from statistical physics with basic computational challenges. Researchers have successfully applied techniques from the study of phase transitions to analyze NP-complete problems such as satisfiability and graph coloring. This is leading to a new understanding of the structure of these problems, and of how algorithms perform on them. Computational Complexity and Statistical Physics will serve as a standard reference and pedagogical aid to statistical physics methods in computer science, with a particular focus on phase transitions in combinatorial problems. Addressed to a broad range of readers, the book includes substantial background material along with current research by leading computer scientists, mathematicians, and physicists. It will prepare students and researchers from all of these fields to contribute to this exciting area.
In the 1990's it was realized that quantum physics has some spectacular applications in computer science. This book is a concise introduction to quantum computation, developing the basic elements of this new branch of computational theory without assuming any background in physics. It begins with an introduction to the quantum theory from a computer-science perspective. It illustrates the quantum-computational approach with several elementary examples of quantum speed-up, before moving to the major applications: Shor's factoring algorithm, Grover's search algorithm, and quantum error correction. The book is intended primarily for computer scientists who know nothing about quantum theory, but will also be of interest to physicists who want to learn the theory of quantum computation, and philosophers of science interested in quantum foundational issues. It evolved during six years of teaching the subject to undergraduates and graduate students in computer science, mathematics, engineering, and physics, at Cornell University.
An engaging introduction to vectors and matrices and the algorithms that operate on them, intended for the student who knows how to program. Mathematical concepts and computational problems are motivated by applications in computer science. The reader learns by "doing," writing programs to implement the mathematical concepts and using them to carry out tasks and explore the applications. Examples include: error-correcting codes, transformations in graphics, face detection, encryption and secret-sharing, integer factoring, removing perspective from an image, PageRank (Google's ranking algorithm), and cancer detection from cell features. A companion web site, codingthematrix.com provides data and support code. Most of the assignments can be auto-graded online. Over two hundred illustrations, including a selection of relevant "xkcd" comics. Chapters: "The Function," "The Field," "The Vector," "The Vector Space," "The Matrix," "The Basis," "Dimension," "Gaussian Elimination," "The Inner Product," "Special Bases," "The Singular Value Decomposition," "The Eigenvector," "The Linear Program" A new edition of this text, incorporating corrections and an expanded index, has been issued as of September 4, 2013, and will soon be available on Amazon.
A very active field of research is emerging at the frontier of statistical physics, theoretical computer science/discrete mathematics, and coding/information theory. This book sets up a common language and pool of concepts, accessible to students and researchers from each of these fields.
Popular among university applicants and their advisers alike, these guides present a wide range of information on a specific degree discipline, laid out in tabular format enabling at-a-glance course comparison.