Mathematical Methods for Physics and Engineering
eBook - ePub

Mathematical Methods for Physics and Engineering

Practical Applications

  1. 253 pages
  2. English
  3. ePUB (mobile friendly)
  4. Available on iOS & Android
eBook - ePub

Mathematical Methods for Physics and Engineering

Practical Applications

About this book

This book provides an accessible introduction to mathematical methods essential for physics, engineering, and modern computational analysis. Starting from foundational topics such as ordinary and partial differential equations, readers are then introduced to powerful techniques including Fourier and Laplace transforms, series expansions, matrix and eigenvalue methods, and numerical strategies such as iterative refinement.

"Mathematical Methods for Physics and Engineering: Practical Applications" emphasizes intuitive understanding and real-world applications: why the Lagrangian in classical mechanics takes the form T?V; how stability and sensitivity analysis connect to condition numbers and perturbation theory; and how matrix representations provide insight into optimisation and numerical stability.

Numerical examples and step-by-step derivations encourage active problem-solving and demonstrate how abstract methods translate into practical computations. It also highlights how these mathematical tools form the foundation of many techniques used in contemporary machine learning; from optimization algorithms and least-squares regression to spectral methods, kernel functions, and high-dimensional data analysis.

This is an ideal textbook for advanced undergraduate and graduate students studying mathematical methods for physics and/or engineering. Readers are equipped not only a versatile toolkit of methods, but also a deeper conceptual understanding of when, where, and why each tool is appropriate - empowering them to approach problems in physics and engineering.

Key features:

  • Provides a toolkit of mathematical methods
  • Pedagogically focused, with homework problems included with each chapter
  • Covers exciting topics including high-dimensional data analysis and machine learning

Chong Qi is an Associate Professor in the Division of Nuclear Science and Engineering, Department of Physics, at the KTH Royal Institute of Technology, Stockholm. His research spans theoretical nuclear physics, many-body physics, and computational physics. He teaches courses in mathematical physics, subatomic and nuclear physics, and quantum many-body theory, and supervises students at both undergraduate and graduate levels in nuclear physics and nuclear engineering. He earned his PhD from Peking University, followed by postdoctoral research at KTH, and has since held visiting professorships at several universities around the world, including Sun Yat-sen University, where a large part of this book was written. He also serves in various editorial roles and is an honorary member of the Romanian Academy of Scientists.

Information

Publisher
CRC Press
Year
2026
Print ISBN
9781041139188
9781041134855
eBook ISBN
9781040620731

Table of contents

  1. Cover Page
  2. Half-Title Page
  3. Title Page
  4. Copyright Page
  5. Contents
  6. Preface
  7. Author Biography
  8. Chapter 1 Essential concepts
  9. Chapter 2 Ordinary differential equations
  10. Chapter 3 Partial differential equations
  11. Chapter 4 Infinite series
  12. Chapter 5 Integral transform and Fourier analysis
  13. Chaper 6 The Laplace transform
  14. Chapter 7 Optimization
  15. Chapter 8 Variational problems
  16. Chapter 9 Nonlinear systems and chaos
  17. Chapter 10 Linear algebra equations and matrix operation
  18. Index

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