Introduction to Computation in Physical Sciences: Interactive Computing and Visualization with Python™...

— —

Jay Wang Adam Wang

Introduction to Computation in Physical Sciences

Interactive Computing and Visualization with Python™

Jay Wang, Adam Wang

$168.95 $135.06

Paperback

Not in-store but you can order this
How long will it take?

Availability Information

We source books from suppliers in Australia and overseas. For books we don't currently have in stock, the time it takes to get them from our suppliers can vary widely - from a few days to a few months - so we check each book with each supplier to determine the expected time it will take to be supplied to us.

We then advise you accordingly. If the time taken to get any book is too long for you, you can let us know and we will cancel or adjust your order, and refund as required.

To find out the anticipated arrival time for specific items prior to ordering, please contact us by phone or email:

Phone +61 2 9264 3111, or 1800 4 BOOKS (1800 4 26657) if outside Sydney:
option 1 Abbey's Bookshop (Crime, History, Science, Kids & more) • info@abbeys.com.au
option 2 Language Book Centre (ESL & Foreign Languages) • language@abbeys.com.au
option 3 Galaxy Bookshop (Sci-fi, Fantasy, Romance, Graphic Novels) • sf@galaxybooks.com.au

QTY:

English

Springer International Publishing AG
26 January 2024

Numerical analysis; Mathematical physics; Computer programming & software development; Programming & scripting languages: general; Maths for computer scientists

Series: Synthesis Lectures on Computation and Analytics

This book provides a practical and comprehensive introduction to computational problem solving from the viewpoints of practitioners in both academic and industrial worlds. The authors present scientific problem-solving using computation and aim to increase computational thinking, which is the mindset and skillset required to solve scientific problems with computational methodologies via model building, simulation, data analysis, and visualization using the Python programming language. Topics and examples span fundamental areas of physical science as well as contemporary topics including quantum computing, neural networks, machine learning, global warming, and energy balance. The book features unique and innovative techniques and practices including: intentional scaffolding to help beginners learn computational problem solving; multimodal computing environments including cloud-based platforms and just-in-time computing; emphasis and connection between both numerical and symbolic computations; and extensive exercise sets carefully designed for further exploration as project assignments or self-paced study. The book is suitable for introductory level readers in physical sciences, engineering, and related STEM disciplines. Specifically, the book is appropriate for use in either a standalone course on computation and modeling and as a resource for readers interested in learning about proven techniques in interactive computing.

By: Jay Wang, Adam Wang
Imprint: Springer International Publishing AG
Country of Publication: Switzerland
Edition: 1st ed. 2023
Dimensions: Height: 240mm, Width: 168mm,
Weight: 466g
ISBN: 9783031176487
ISBN 10: 3031176480
Series: Synthesis Lectures on Computation and Analytics
Pages: 255
Publication Date: 26 January 2024
Audience: Professional and scholarly , Undergraduate
Format: Paperback
Publisher's Status: Active

Programming environments.- Python Tutorial.- Interactive computing and visualization.- Basic algorithms.- Force and motion.- Oscillations and waves.- Modern physics and quantum mechanics.- Statistical and thermal processes.- Complex Systems.

Jay J. Wang, Ph.D. is a Professor and Chairperson in the Department of Physics at UMass Dartmouth. He received his Ph.D. in Theoretical Atomic Physics from the University of Tennessee. Dr. Wang's interests include computational physics, physics education, and research pertaining to the computation and integration of interactive computation in physics and related STEM curricula. Adam L. Wang received his M.S. in Physics from the University of Chicago, where he was awarded an NSF Graduate Research Fellowship. He has worked on complex systems and nonlinear dynamics, aided by computational tools. More recently, he uses machine learning, interactive computing, and visualization as a data scientist.