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Table of contents
Mathematical and Scientific Computing in C++
From programming fundamentals to reliable numerical simulation
Read each section in order. Every title can be opened as a TheoryTrace document.
- Cover1
- Copyright2
- How to read this book3
- Introduction4
- Chapter 1: Computing as a Mathematical Tool5
- Chapter 2: C++ Essentials for Numerical Work6
- Chapter 3: Types, Precision, and Floating-Point Arithmetic7
- Chapter 4: Functions, Modularity, and Mathematical Code Design8
- Chapter 5: Arrays, Vectors, and Data Representation9
- Chapter 6: Error, Stability, and Conditioning10
- Chapter 7: Mathematical Algorithms and Complexity11
- Chapter 8: Numerical Differentiation and Integration12
- Chapter 9: Roots and Nonlinear Equations13
- Chapter 10: Linear Algebra Foundations in C++14
- Chapter 11: Solving Linear Systems15
- Chapter 12: Eigenvalues, Least Squares, and Data Fitting16
- Chapter 13: Interpolation and Approximation17
- Chapter 14: Ordinary Differential Equations18
- Chapter 15: Scientific Modeling and Simulation19
- Chapter 16: Random Numbers and Monte Carlo Methods20
- Chapter 17: Optimization and Parameter Estimation21
- Chapter 18: Working with Scientific Data22
- Chapter 19: Using Modern C++ Libraries23
- Chapter 20: Performance, Memory, and Profiling24
- Chapter 21: Testing, Verification, and Reproducibility25
- Chapter 22: Capstone Projects in Mathematical and Scientific Computing26
- Conclusion27