Numerical Methods in Physics with Python, Alex Gezerlis
Автор: Riley Название: Mathematical Methods for Physics and Engineering ISBN: 0521679710 ISBN-13(EAN): 9780521679718 Издательство: Cambridge Academ Рейтинг: Цена: 7920.00 р. Наличие на складе: Есть (1 шт.) Описание: This highly acclaimed undergraduate textbook teaches all the mathematics for undergraduate courses in the physical sciences. Containing over 800 exercises, half come with hints and answers and, in a separate manual, complete worked solutions. The remaining exercises are intended for unaided homework; full solutions are available to instructors.
Автор: ?irca Название: Computational Methods in Physics ISBN: 3319786180 ISBN-13(EAN): 9783319786186 Издательство: Springer Рейтинг: Цена: 13974.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Since this is a 2nd Edition, we are giving below the topics we wish to add/update/revise in roughly the same chapter sequence as we had in the existing 1st Edition of the book. In addition to a general revision of the text, we propose the following major modifications (the asterisks denote the amount of text added/modified and/or or the difficulty level of the topics being discussed):
Chapter 2
- Subsection 2.1.2: add discussion on how to find all zeros by means
of the Newton method (*)
Chapter 3
- Expand Subsection 3.2.7 on solving the A*x = b equations with sparse
matrices to a full Section (**)
- Expand Subsection 3.4.5 on solving the eigenvalue problem A*x = lambda*x
to a full Section (**)
- Discuss the exponentiation of a matrix, exp(A) (*)
- Add a Subsection on Pseudospectra (**)
- in general
, enhance the "sparse" aspect of the chapter
Chapter 4
- Add a new Section on Sparse FFT (following present Sec. 4.2),
add corresponding Exercise (**)
- Expand Subsection 4.6.2 on the Discrete Wavelet Transform
to a full Section, add Exercise (***)
- Add a Section on image denoising (**)
- Add Section on Radon transformation (**)
Chapter 5
- Rewrite Sections 5.1-5.5 to better distinguish between general
discussion of distributions and the techniques involving samples,
and to bring the notation in line with the book "Probability
for Physicists" (***)
- Introduce Bayesian data analysis and inference (***)
- Expand Subsection 5.5.8 on Non-linear Regression to a full Section,
add Exercises (**)
Chapter 6
- Expand Section 6.5
on Noise, add Exercise (**)
- Add Section on Takens Theorem and its applications: phase space
reconstruction and optimal size determination (**)
- Add discussion on signal entropies (**)
- Update discussion on autoregressive models (optimal order) (*)
- Add discussion on signal directionality / causality (**)
Chapter 7
- Expand Section 7.10 on Stiff Problems of ODE, add Exercise (**)
Chapter 8
- Expand Subsection 8.7.4 on Singular SL Problems to a Section,
add Exercise (**)
- Motivated by Section 8.8, write a new chapter on Inverse Problems (***)
Chapter 10
- Expand Section 10.8, add Exercise (**)
Chapter 11
- Expand Sections 11.7 and 11.8, add Exercises (**)
New Chapter on Inverse Methods (***)
New short Chapter or Appendix on minimization (**)
- with derivatives or without them
- with constraints or without them
- deterministic and quasi-deterministic (MC methods)
New Appendix on spline methods: B-splines, Bezier splines (**)
Автор: Hutchinson Название: A Student`s Guide to Numerical Methods ISBN: 1107095670 ISBN-13(EAN): 9781107095670 Издательство: Cambridge Academ Рейтинг: Цена: 8078.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Written for senior undergraduates in all disciplines of physical science and engineering, the plain language style of this concise guide to numerical methods concentrates on developing computational skills and avoids potentially intimidating formal mathematical proofs. Including numerous worked examples and exercises, this textbook explains the practical realities of numerical techniques.
Автор: Alex Gezerlis Название: Numerical Methods in Physics with Python ISBN: 1009303864 ISBN-13(EAN): 9781009303866 Издательство: Cambridge Academ Рейтинг: Цена: 7918.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Bringing together idiomatic Python programming, foundational numerical methods, and physics applications, this is an ideal standalone textbook for courses on computational physics. All the frequently used numerical methods in physics are explained, including foundational techniques and hidden gems on topics such as linear algebra, differential equations, root-finding, interpolation, and integration. The second edition of this introductory book features several new codes and 140 new problems (many on physics applications), as well as new sections on the singular-value decomposition, derivative-free optimization, Bayesian linear regression, neural networks, and partial differential equations. The last section in each chapter is an in-depth project, tackling physics problems that cannot be solved without the use of a computer. Written primarily for students studying computational physics, this textbook brings the non-specialist quickly up to speed with Python before looking in detail at the numerical methods often used in the subject.
Автор: Simon ?irca; Martin Horvat Название: Computational Methods in Physics ISBN: 3030087468 ISBN-13(EAN): 9783030087463 Издательство: Springer Рейтинг: Цена: 13974.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book is intended to help advanced undergraduate, graduate, and postdoctoral students in their daily work by o?ering them a compendium of numerical methods. The choice of methods pays signi?cant attention to error estimates, stability and convergence issues, as well as optimization of program execution speeds. Numerous examples are given throughout the chapters, followed by comprehensive end-of-chapter problems with a more pronounced physics background, while less stress is given to the explanation of individual algorithms. The readers are encouraged to develop a certain amount of skepticism and scrutiny instead of blindly following readily available commercial tools. The second edition has been enriched by a chapter on inverse problems dealing with the solution of integral equations, inverse Sturm-Liouville problems, as well as retrospective and recovery problems for partial di?erential equations. The revised text now includes an introduction to sparse matrix methods, the solution of matrix equations, and pseudospectra of matrices; it discusses the sparse Fourier, non-uniform Fourier and discrete wavelet transformations, the basics of non-linear regression and the Kolmogorov-Smirnov test; it demonstrates the key concepts in solving sti? di?erential equations and the asymptotics of Sturm-Liouville eigenvalues and eigenfunctions. Among other updates, it also presents the techniques of state-space reconstruction, methods to calculate the matrix exponential, generate random permutations and compute stable derivatives.
Автор: Hutchinson Название: A Student`s Guide to Numerical Methods ISBN: 1107479509 ISBN-13(EAN): 9781107479500 Издательство: Cambridge Academ Рейтинг: Цена: 4118.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Written for senior undergraduates in all disciplines of physical science and engineering, the plain language style of this concise guide to numerical methods concentrates on developing computational skills and avoids potentially intimidating formal mathematical proofs. Including numerous worked examples and exercises, this textbook explains the practical realities of numerical techniques.
Автор: Gerhard Beutler; Leos Mervart; Andreas Verdun Название: Methods of Celestial Mechanics ISBN: 3642148573 ISBN-13(EAN): 9783642148576 Издательство: Springer Рейтинг: Цена: 10480.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: In cooperation with Prof. Leos Mervart and Dr. Andreas Verdun
Автор: Turab Lookman Название: Materials Discovery and Design ISBN: 3319994646 ISBN-13(EAN): 9783319994642 Издательство: Springer Рейтинг: Цена: 23757.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book addresses the current status, challenges and future directions of data-driven materials discovery and design. It presents the analysis and learning from data as a key theme in many science and cyber related applications. The challenging open questions as well as future directions in the application of data science to materials problems are sketched. Computational and experimental facilities today generate vast amounts of data at an unprecedented rate. The book gives guidance to discover new knowledge that enables materials innovation to address grand challenges in energy, environment and security, the clearer link needed between the data from these facilities and the theory and underlying science. The role of inference and optimization methods in distilling the data and constraining predictions using insights and results from theory is key to achieving the desired goals of real time analysis and feedback. Thus, the importance of this book lies in emphasizing that the full value of knowledge driven discovery using data can only be realized by integrating statistical and information sciences with materials science, which is increasingly dependent on high throughput and large scale computational and experimental data gathering efforts. This is especially the case as we enter a new era of big data in materials science with the planning of future experimental facilities such as the Linac Coherent Light Source at Stanford (LCLS-II), the European X-ray Free Electron Laser (EXFEL) and MaRIE (Matter Radiation in Extremes), the signature concept facility from Los Alamos National Laboratory. These facilities are expected to generate hundreds of terabytes to several petabytes of in situ spatially and temporally resolved data per sample. The questions that then arise include how we can learn from the data to accelerate the processing and analysis of reconstructed microstructure, rapidly map spatially resolved properties from high throughput data, devise diagnostics for pattern detection, and guide experiments towards desired targeted properties. The authors are an interdisciplinary group of leading experts who bring the excitement of the nascent and rapidly emerging field of materials informatics to the reader.
Автор: Baumgarte, Thomas W. (bowdoin College, Maine) Shapiro, Stuart L. (university Of Illinois, Urbana-champaign) Название: Numerical relativity: starting from scratch ISBN: 1108928250 ISBN-13(EAN): 9781108928250 Издательство: Cambridge Academ Рейтинг: Цена: 7286.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Numerical relativity has emerged as the key tool to model gravitational waves that are emitted when two black holes collide. This book provides a pedagogical, accessible and concise introduction to the subject for non-experts, acquainting them with the key concepts underlying publicly available numerical relativity codes.
Описание: New insight in many scientific and engineering fields is unthinkable without the use of numerical simulations running efficiently on modern computers. The faster we get new results, the bigger and accurate are the problems that we can solve. It is the combination of mathematical ideas plus efficient programming that drives the progress in many disciplines. Future champions in the area thus will have to be qualified in their application domain, they will need a profound understanding of some mathematical ideas, and they need the skills to deliver fast code. The present textbook targets students which have programming skills already and do not shy away from mathematics, though they might be educated in computer science or an application domain. It introduces the basic concepts and ideas behind applied mathematics and parallel programming that we need to write numerical simulations for today’s multicore workstations. Our intention is not to dive into one particular application domain or to introduce a new programming language – we lay the generic foundations for future courses and projects in the area. The text is written in an accessible style which is easy to digest for students without years and years of mathematics education. It values clarity and intuition over formalism, and uses a simple N-body simulation setup to illustrate basic ideas that are of relevance in various different subdomains of scientific computing. Its primary goal is to make theoretical and paradigmatic ideas accessible to undergraduate students and to bring the fascination of the field across.
Автор: Maurice Holt Название: Numerical Methods in Fluid Dynamics ISBN: 3540127992 ISBN-13(EAN): 9783540127994 Издательство: Springer Рейтинг: Цена: 14365.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: From the reviews of the first edition: "This book is directed to graduate students and research workers interested in the numerical solution of problems of fluid dynamics, primarily those arising in high speed flow.
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