Mathematical Methods for Scientists and Engineers
Donald A. McQuarrie University of California, Davis
Detailed Table of Contents
Chapter 1: Functions of a Single Variable
1-1. Functions
1-2. Limits
1-3. Continuity
1-4. Differentiation
1-5. Differentials
1-6. Mean Value Theorems
1-7. Integration
1-8. Improper Integrals
1-9. Uniform Convergence of Integrals
Chapter 2: Infinite Series
2-1. Infinite Sequences
2-2. Convergence and Divergence of Infinite Series
2-3. Tests for Convergence
2-4. Alternating Series
2-5. Uniform Convergence
2-6. Power Series
2-7. Taylor Series
2-8. Applications of Taylor Series
2-9. Asymptotic Expansions
Chapter 3: Functions Defined As Integrals
3-1. The Gamma Function
3-2. The Beta Function
3-3. The Error Function
3-4. The Exponential Integral
3-5. Elliptic Integrals
3-6. The Dirac Delta Function
3-7. Bernoulli Numbers and Bernoulli Polynomials
Chapter 4: Complex Numbers and Complex Functions
4-1. Complex Numbers and the Complex Plane
4-2. Functions of a Complex Variable
4-3. Euler’s Formula and the Polar Form of Complex Numbers
4-4. Trigonometric and Hyperbolic Functions
4-5. The Logarithms of Complex Numbers
4-6. Powers of Complex Numbers
Chapter 5: Vectors
5-1. Vectors in Two Dimensions
5-2. Vector Functions in Two Dimensions
5-3. Vectors in Three Dimensions
5-4. Vector Functions in Three Dimensions
5-5. Lines and Planes in Space
Chapter 6: Functions of Several Variables
6-1. Functions
6-2. Limits and Continuity
6-3. Partial Derivatives
6-4. Chain Rules for Partial Differentiation
6-5. Differentials and the Total Differential
6-6. The Directional Derivative and the Gradient
6-7. Taylor’s Formula in Several Variables
6-8. Maxima and Minima
6-9. The Method of Lagrange Multipliers
6-10. Multiple Integrals
Chapter 7: Vector Calculus
7-1. Vector Fields
7-2. Line Integrals
7-3. Surface Integrals
7-4. The Divergence Theorem
7-5. Stokes’s Theorem
Chapter 8: Curvilinear Coordinates
8-1. Plane Polar Coordinates
8-2. Vectors in Plane Polar Coordinates
8-3. Cylindrical Coordinates
8-4. Spherical Coordinates
8-5. Curvilinear Coordinates
8-6. Some Other Coordinate Systems
Chapter 9: Linear Algebra and Vector Spaces
9-1. Determinants
9-2. Gaussian Elimination
9-3. Matrices
9-4. Rank of a Matrix
9-5. Vector Spaces
9-6. Inner Product Spaces
9-7. Complex Inner Product Spaces
Chapter 10: Matrices and Eigenvalue Problems
10-1. Orthogonal and Unitary Transformations
10-2. Eigenvalues and Eigenvectors
10-3. Some Applied Eigenvalue Problems
10-4. Change of Basis
10-5. Diagonalization of Matrices
10-6. Quadratic Forms
Chapter 11: Ordinary Differential Equations
11-1. Differential Equations of First Order and First Degree
11-2. Linear First-Order Differential Equations
11-3. Homogeneous Linear Differential Equations with Constant Coefficients
11-4. Nonhomogeneous Linear Differential Equations with Constant Coefficients
11-5. Some Other Types of Higher-Order Differential Equations
11-6. Systems of First-Order Differential Equations
11-7. Two Invaluable Resources for Solutions to Differential Equations
Chapter 12: Series Solutions of Differential Equations
12-1. The Power Series Method
12-2. Ordinary Points and Singular Points of Differential Equations
12-3. Series Solutions Near an Ordinary Point: Legendre’s Equation
12-4. Solutions Near Regular Singular Points
12-5. Bessel’s Equation
12-6. Bessel Functions
Chapter 13: Qualitative Methods for Nonlinear Differential Equations
13-1. The Phase Plane
13-2. Critical Points in the Phase Plane
13-3. Stability of Critical Points
13-4. Nonlinear Oscillators
13-5. Population Dynamics
Chapter 14: Orthogonal Polynomials and Sturm–Liouville Problems
14-1. Legendre Polynomials
14-2. Orthogonal Polynomials
14-3. Sturm–Liouville Theory
14-4. Eigenfunction Expansions
14-5. Green’s Functions
Chapter 15: Fourier Series
15-1. Fourier Series as Eigenfunction Expansions
15-2. Sine and Cosine Series
15-3. Convergence of Fourier Series
15-4. Fourier Series and Ordinary Differential Equations
Chapter 16: Partial Differential Equations
16-1. Some Examples of Partial Differential Equations
16-2. Laplace’s Equation
16-3. The One-Dimensional Wave Equation
16-4. The Two-Dimensional Wave Equation
16-5. The Heat Equation
16-6. The Schrödinger Equation
a. Particle in a Box
b. A Rigid Rotor
c. The Electron in a Hydrogen Atom
16-7. The Classification of Partial Differential Equations
Chapter 17: Integral Transforms
17-1. The Laplace Transform
17-2. The Inversion of Laplace Transforms
17-3. Laplace Transforms and Ordinary Differential Equations
17-4. Laplace Transforms and Partial Differential Equations
17-5. Fourier Transforms
17-6. Fourier Transforms and Partial Differential Equations
17-7. The Inversion Formula for Laplace Transforms
Chapter 18: Functions of a Complex Variable: Theory
18-1. Functions, Limits, and Continuity
18-2. Differentiation. The Cauchy–Riemann Equations
18-3. Complex Integration. Cauchy’s Theorem
18-4. Cauchy’s Integral Formula
18-5. Taylor Series and Laurent Series
18-6. Residues and the Residue Theorem
Chapter 19: Functions of a Complex Variable: Applications
19-1. The Inversion Formula for Laplace Transforms
19-2. Evaluation of Real, Definite Integrals
19-3. Summation of Series
19-4. Location of Zeros
19-5. Conformal Mapping
19-6. Conformal Mapping and Boundary Value Problems
19-7. Conformal Mapping and Fluid Flow
Chapter 20: Calculus of Variations
20-1. The Euler’s Equation
20-2. Two Laws of Physics in Variational Form
20-3. Variational Problems with Constraints
20-4. Variational Formulation of Eigenvalue Problems
20-5. Multidimensional Variational Problems
Chapter 21: Probability Theory and Stochastic Processes
21-1. Discrete Random Variables
21-2. Continuous Random Variables
21-3. Characteristic Functions
21-4. Stochastic Processes—General
21-5. Stochastic Processes—Examples
a. Poisson Process
b. The Shot Effect
Chapter 22: Mathematical Statistics
22-1. Estimation of Parameters
22-2. Three Key Distributions Used in Statistical Tests
a. The Normal Distribution
b. The Chi–Square Distribution
c. Student t-Distribution
22-3. Confidence Intervals
a. Confidence Intervals for the Mean of a Normal Distribution Whose Variance is Known
b. Confidence Intervals for the Mean of a Normal Distribution with Unknown Variance
c. Confidence Intervals for the Variance of a Normal Distribution
22-4. Goodness of Fit
22-5. Regression and Correlation
Index