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Thermal Physics Tutorials with Python SimulationsНазвание: Thermal Physics Tutorials with Python Simulations
Автор: Minjoon Kouh, Taejoon Kouh
Издательство: CRC Press
Год: 2023
Страниц: 238
Язык: английский
Формат: pdf (true)
Размер: 34.96 MB

This book provides an accessible introduction to thermal physics with computational approaches that complement the traditional mathematical treatments of classical thermodynamics and statistical mechanics. It guides readers through visualizations and simulations in the Python programming language, helping them to develop their own technical computing skills (including numerical and symbolic calculations, optimizations, recursive operations, and visualizations). Python is a highly readable and practical programming language, making this book appropriate for students without extensive programming experience.

Mathematics is one of the most powerful and essential tools of a physicist, or may even be considered as the language of physics. However, in recent years, computational methods have risen to complement and supplement the traditional, mathematical approaches to physics. As the new generation of physicists is expected to be well versed in modern computational tools, this tutorial was written with the goal of introducing a few elementary skills in data visualization, modeling, and simulation with a popular (as of the 2020s) programming language, Python, within the context of classical thermodynamics and statistical physics.

This book provides step-by-step instructions for each of the programming examples, and prior experience with Python is not necessary. If you are just venturing into the world of Python, the official homepage of the Python language is a great place to visit. There are other resources on Python, many of which are free and easily accessible online. There are different ways to set up your own computing environment, so that you can follow the codes in this book. For example, you may download and install the Anaconda distribution, which contains an interactive Jupyter Notebook environment as well as key Python modules. You may also use a cloud-based Python environment like Google Colab. See Appendix for more information.

This book may serve as a thermal physics textbook for a semester-long undergraduate thermal physics course or may be used as a tutorial on scientific computing with focused examples from thermal physics. This book will also appeal to engineering students studying intermediate-level thermodynamics as well as computer science students looking to understand how to apply their computer programming skills to science.

Key features:

Major concepts in thermal physics are introduced cohesively through computational and mathematical treatments.
Computational examples in Python programming language guide students on how to simulate and visualize thermodynamic principles and processes for themselves.

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