Jay Wang, Adam Wang

Gebundenes Buch

Introduction to Computation in Physical Sciences

Interactive Computing and Visualization with Python(TM)

Beschreibung

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 symboliccomputations; 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.

Autor

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.

Produktdetails

• Synthesis Lectures on Computation and Analytics
• Verlag: Springer / Springer International Publishing / Springer, Berlin
• Artikelnr. des Verlages: 978-3-031-17645-6
• 1st edition 2023
• Seitenzahl: 272
• Erscheinungstermin: 26. Januar 2023
• Englisch
• Abmessung: 246mm x 173mm x 21mm
• Gewicht: 638g
• ISBN-13: 9783031176456
• ISBN-10: 3031176456
• Artikelnr.: 65435339