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Thermal Physics Tutorials with Python Simulations in pdf

 

Download this PDF book: Thermal Physics Tutorials with Python Simulations

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.

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.

T. Kouh earned his B.A. in physics from Boston University and Sc.M. and Ph.D. degrees in physics from Brown University. After his study in Providence, RI, he returned to Boston, MA, and worked as a postdoctoral research associate in the Department of Aerospace and Mechanical Engineering at Boston University. 

He is a full faculty member in the Department of Nano and Electronic Physics at Kookmin University in Seoul, Korea, teaching and supervising undergraduate and graduate students. 

His current research involves the dynamics of nanoelectromechanical systems and the development of fast and reliable transduction methods and innovative applications based on tiny motion. M. Kouh holds Ph.D. and B.S. degrees in physics from MIT and M.A. from UC Berkeley. He completed a postdoctoral research fellowship at the Salk Institute for Biological Studies in La Jolla, CA. 

His research includes computational modeling of the primate visual cortex, information-theoretic analysis of neural responses, machine learning, and pedagogical innovations in undergraduate science education. He taught more than 30 distinct types of courses at Drew University (Madison, NJ), including two study-abroad programs. 

His professional experiences include a role as a program scientist for a philanthropic initiative, a data scientist at a healthcare AI startup, and an IT consultant at a software company.

T. Kouh would like to thank the faculty members in the Department of Nano and Electronic Physics at Kookmin University for their support, along with his current and former students from the lab. Stimulating and engaging discussions with his students on various topics in physics have started him to mull over intriguing and entertaining ways of answering the questions, which has been valuable to completing this book. He is also grateful to his mentors, Prof. J. Valles from Brown University and Prof. K. Ekinci from Boston University, for guiding him through his academic career and showing him the fun of doing physics. 

Last but not least, his biggest and deepest thanks go to his dearest Sarah. M. Kouh would like to thank his colleagues from the Drew University Physics Department, R. Fenstermacher, J. Supplee, D. McGee, R. Murawski, and B. Larson, as well as his students. They helped him to think deeply about physics from the first principles and from different perspectives. 

He is indebted to his academic mentors, T. Poggio and T. Sharpee, who have shown the power and broad applicability of computational approaches, especially when they are thoughtfully combined with mathematical and experimental approaches. His family is a constant source of his inspiration and energy. Thank you, Yumi, Chris, and Cailyn!

About the Author

Taejoon Kouh is a Professor of Nano and Electronic Physics at Kookmin University, Republic of Korea.

Minjoon Kouh is a Professor of Physics and Neuroscience at Drew University, USA.

About the book:

Publisher ‏ : ‎ CRC Press; 1st edition 

Publication date ‏ : ‎ March 14, 2023

Language ‏ : ‎ English

Pages ‏ : ‎ 238 

File : PDF, 15 MB

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