Download Free Computer Algebra In Scientific Computing Book in PDF and EPUB Free Download. You can read online Computer Algebra In Scientific Computing and write the review.

This book constitutes the proceedings of the 23rd International Workshop on Computer Algebra in Scientific Computing, CASC 2021, held in Sochi, Russia, in September 2021. The 24 full papers presented together with 1 invited talk were carefully reviewed and selected from 40 submissions. The papers cover theoretical computer algebra and its applications in scientific computing.
This book constitutes the refereed proceedings of the 22nd International Workshop on Computer Algebra in Scientific Computing, CASC 2020, held in Linz, Austria, in September 2020. The conference was held virtually due to the COVID-19 pandemic. The 34 full papers presented together with 2 invited talks were carefully reviewed and selected from 41 submissions. They deal with cutting-edge research in all major disciplines of computer algebra. The papers cover topics such as polynomial algebra, symbolic and symbolic-numerical computation, applications of symbolic computation for investigating and solving ordinary differential equations, applications of CAS in the investigation and solution of celestial mechanics problems, and in mechanics, physics, and robotics.
This non-traditional introduction to the mathematics of scientific computation describes the principles behind the major methods, from statistics, applied mathematics, scientific visualization, and elsewhere, in a way that is accessible to a large part of the scientific community. Introductory material includes computational basics, a review of coo
For this set of lectures we assumed that the reader has a reasonable back ground in physics and some knowledge of general relativity, the modern theory of gravity in macrophysics, and cosmology. Computer methods are present ed by leading experts in the three main domains: in numerics, in computer algebra, and in visualization. The idea was that each of these subdisciplines is introduced by an extended set of main lectures and that each is conceived as being of comparable 'importance. Therefpre we believe that the book represents a good introduction into scientific I computing for any student who wants to specialize in relativity, gravitation, and/or astrophysics. We took great care to select lecturers who teach in a comprehensible way and who are, at the same time, at the research front of their respective field. In numerics we had the privilege of having a lecturer from the National Center for Supercomputing Applications (NCSA, Champaign, IL, USA) and some from other leading institutions of the world; visualization was taught by a visualization expert from Boeing; and in com puter algebra we took recourse to practitioners of different computer algebra systems as applied to classical general relativity up to quantum gravity and differential geometry.
This book is a practical guide to the numerical solution of linear and nonlinear equations, differential equations, optimization problems, and eigenvalue problems. It treats standard problems and introduces important variants such as sparse systems, differential-algebraic equations, constrained optimization, Monte Carlo simulations, and parametric studies. Stability and error analysis are emphasized, and the Matlab algorithms are grounded in sound principles of software design and understanding of machine arithmetic and memory management. Nineteen case studies provide experience in mathematical modeling and algorithm design, motivated by problems in physics, engineering, epidemiology, chemistry, and biology. The topics included go well beyond the standard first-course syllabus, introducing important problems such as differential-algebraic equations and conic optimization problems, and important solution techniques such as continuation methods. The case studies cover a wide variety of fascinating applications, from modeling the spread of an epidemic to determining truss configurations.
This book offers an introduction to computer programming, numerical analysis, and other mathematical ideas that extend the basic topics learned in calculus. It illustrates how mathematicians and scientists write computer programs, covering the general building blocks of programming languages and a description of how these concepts fit together to allow computers to produce the results they do. Topics explored here include binary arithmetic, algorithms for rendering graphics, the smooth interpolation of discrete data, and the numerical approximation of non-elementary integrals. The book uses an open-source computer algebra system called Maxima. Using Maxima, first-time programmers can perform familiar tasks, such as graphing functions or solving equations, and learn the basic structures of programming before moving on to other popular programming languages. The epilogue provides some simple examples of how this process works in practice. The book will particularly appeal to students who have finished their calculus sequence.
Mathematics of Computing -- Mathematical Software.
Taking an interdisciplinary approach, this new book provides a modern introduction to scientific computing, exploring numerical methods, computer technology, and their interconnections, which are treated with the goal of facilitating scientific research across all disciplines. Each chapter provides an insightful lesson and viewpoints from several subject areas are often compounded within a single chapter. Written with an eye on usefulness, longevity, and breadth, Lessons in Scientific Computing will serve as a "one stop shop" for students taking a unified course in scientific computing, or seeking a single cohesive text spanning multiple courses. Features: Provides a unique combination of numerical analysis, computer programming, and computer hardware in a single text Includes essential topics such as numerical methods, approximation theory, parallel computing, algorithms, and examples of computational discoveries in science Not wedded to a specific programming language
The book provides an introduction to common programming tools and methods in numerical mathematics and scientific computing. Unlike widely used standard approaches, it does not focus on any particular language but aims to explain the key underlying concepts. In general, new concepts are first introduced in the particularly user-friendly Python language and then transferred and expanded in various scientific programming environments from C / C ++, Julia and MATLAB to Maple. This includes different approaches to distributed computing. The fact that different languages are studied and compared also makes the book useful for mathematicians and practitioners trying to decide which programming language to use for which purposes.
This book constitutes the refereed proceedings of the 8th International Workshop on Computer Algebra in Scientific Computing, CASC 2005, held in Kalamata, Greece in September 2005. The 41 revised full papers presented were carefully reviewed and selected from 75 submissions. The topics addressed in the workshop cover all the basic areas of scientific computing as they benefit from the application of computer algebra methods and software: algebraic methods for nonlinear polynomial equations and inequalities, symbolic-numeric methods for differential and differential-algebraic equations, algorithmic and complexity considerations in computer algebra, algebraic methods in geometric modelling, aspects of computer algebra programming languages, automatic reasoning in algebra and geometry, complexity of algebraic problems, exact and approximate computation, parallel symbolic-numeric computation, Internet accessible symbolic and numeric computation, problem-solving environments, symbolic and numerical computation in systems engineering and modelling, computer algebra in industry, solving problems in the natural sciences, numerical simulation using computer algebra systems, mathematical communication.