Basic Analysis II: A Modern Calculus in Many Variables

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Basic Analysis II: A Modern Calculus in Many Variables focuses on differentiation in Rn and important concepts about mappings from Rn to Rm, such as the inverse and implicit function theorem and change of variable formulae for multidimensional integration. These topics converge nicely with many other important applied and theoretical areas which are no longer covered in mathematical science curricula. Although it follows on from the preceding volume, this is a self-contained book, accessible to undergraduates with a minimal grounding in analysis.

    Features

      • Can be used as a traditional textbook as well as for self-study

      • Suitable for undergraduates in mathematics and associated disciplines

      • Emphasises learning how to understand the consequences of assumptions using a variety of tools to provide the proofs of propositions

      Author(s): James K. Peterson
      Edition: 1
      Publisher: Chapman and Hall/CRC
      Year: 2020

      Language: English
      Pages: 517
      City: Boca Raton
      Tags: Topology; Bolzano; Weierstrass; Vector Spaces; Linear Transformations; Symmetric Matrices; Continuity; Rotations; Orbital Mechanics; Determinants; Matrix Manipulation; Calculus Of Many Variables; Differentiability; Multivariable Extremal Theory; Inverse Theory; Implicit Function Theory; Linear Approximations Applications; Integration; Change Of Variables; Fubini's Theorem; Line Integrals; Differential Forms

      Cover
      Half Title
      Title Page
      Copyright Page
      Dedication Page
      Table of Contents
      I Introduction
      1 Beginning Remarks
      1.1 Table of Contents
      1.2 Acknowledgments
      II Linear Mappings
      2 Preliminaries
      2.1 The Basics
      2.2 Some Topology in ℜ2
      2.2.1 Homework
      2.3 Bolzano - Weierstrass in ℜ2
      2.3.1 Homework
      3 Vector Spaces
      3.1 Vector Spaces over a Field
      3.1.1 The Span of a Set of Vectors
      3.2 Inner Products
      3.2.1 Homework
      3.3 Examples
      3.3.1 Two Dimensional Vectors in the Plane
      3.3.2 The Connection between Two Orthonormal Bases
      3.3.3 The Invariance of the Inner Product
      3.3.4 Two Dimensional Vectors as Functions
      3.3.5 Three Dimensional Vectors in Space
      3.3.6 The Solution Space of Higher Dimensional ODE Systems
      3.4 Best Approximation in a Vector Space with Inner Product
      3.4.1 Homework
      4 Linear Transformations
      4.1 Organizing Point Cloud Data
      4.1.1 Homework
      4.2 Linear Transformations
      4.2.1 Homework
      4.3 Sequence Spaces Revisited
      4.3.1 Homework
      4.4 Linear Transformations between Normed Linear Spaces
      4.4.1 Basic Properties
      4.4.2 Mappings between Finite Dimensional Vector Spaces
      4.5 Magnitudes of Linear Transformations
      5 Symmetric Matrices
      5.1 The General Two by Two Symmetric Matrix
      5.1.1 Examples
      5.1.2 A Canonical Form
      5.1.3 Two Dimensional Rotations
      5.1.4 Homework
      5.2 Rotating Surfaces
      5.2.1 Homework
      5.3 A Complex ODE System Example
      5.3.1 The General Real and Complex Solution
      5.3.2 Rewriting the Real Solution
      5.3.3 Signed Definite Matrices
      5.3.4 Summarizing
      5.4 Symmetric Systems of ODEs
      5.4.1 Writing the Solution Another Way
      5.4.2 Homework
      6 Continuity and Topology
      6.1 Topology in n Dimensions
      6.1.1 Homework
      6.2 Cauchy Sequences
      6.3 Compactness
      6.3.1 Homework
      6.4 Functions of Many Variables
      6.4.1 Limits and Continuity for Functions of Many Variables
      7 Abstract Symmetric Matrices
      7.1 Input-Output Ratios for Matrices
      7.1.1 Homework
      7.2 The Norm of a Symmetric Matrix
      7.2.1 Constructing Eigenvalues
      7.3 What Does This Mean?
      7.4 Signed Definite Matrices Again
      7.4.1 Homework
      8 Rotations and Orbital Mechanics
      8.1 Introduction
      8.1.1 Homework
      8.2 Orbital Planes
      8.2.1 Orbital Constants
      8.2.2 The Orbital Motion
      8.2.3 The Constant B Vector
      8.2.4 The Orbital Conic
      8.3 Three Dimensional Rotations
      8.3.1 Homework
      8.3.2 Drawing Rotations
      8.3.3 Rotated Ellipses
      8.4 Drawing the Orbital Plane
      8.4.1 The Perifocal Coordinate System
      8.4.2 Orbital Elements
      8.5 Drawing Orbital Planes Given Radius and Velocity Vectors
      8.5.1 Homework
      9 Determinants and Matrix Manipulations
      9.1 Determinants
      9.1.1 Consequences One
      9.1.2 Homework
      9.1.3 Consequences Two
      9.1.4 Homework
      9.2 Matrix Manipulation
      9.2.1 Elementary Row Operations and Determinants
      9.2.2 Code Implementations
      9.2.3 Matrix Inverse Calculations
      9.3 Back to Definite Matrices
      III Calculus of Many Variables
      10 Differentiability
      10.1 Partial Derivatives
      10.1.1 Homework
      10.2 Tangent Planes
      10.3 Derivatives for Scalar Functions of n Variables
      10.3.1 The Chain Rule for Scalar Functions of n Variables
      10.4 Partials and Differentiability
      10.4.1 Partials Can Exist but Not be Continuous
      10.4.2 Higher Order Partials
      10.4.3 When Do Mixed Partials Match?
      10.5 Derivatives for Vector Functions of n Variables
      10.5.1 The Chain Rule for Vector-Valued Functions
      10.6 Tangent Plane Error
      10.6.1 The Mean Value Theorem
      10.6.2 Hessian Approximations
      10.7 A Specific Coordinate Transformation
      10.7.1 Homework
      11 Multivariable Extremal Theory
      11.1 Differentiability and Extremals
      11.2.1 Positive and Negative Definite Hessians
      11.2.2 Expressing Conditions in Terms of Partials
      12 The Inverse and Implicit Function Theorems
      12.1 Mappings
      12.2 Invertibility Results
      12.2.1 Homework
      12.3 Implicit Function Results
      12.3.1 Homework
      12.4 Constrained Optimization
      12.4.1 What Does the Lagrange Multiplier Mean?
      12.4.2 Homework
      13 Linear Approximation Applications
      13.1 Linear Approximations to Nonlinear ODE
      13.1.1 An Insulin Model
      13.2 Finite Difference Approximations in PDE
      13.2.1 First Order Approximations
      13.2.2 Second Order Approximations
      13.2.3 Homework
      13.3 FD Approximations
      13.3.1 Error Analysis
      13.3.2 Homework
      13.4 FD Diffusion Code
      13.4.1 Homework
      IV Integration
      14 Integration in Multiple Dimensions
      14.1 The Darboux Integral
      14.1.1 Homework
      14.2 The Riemann Integral in n Dimensions
      14.2.1 Homework
      14.3 Volume Zero and Measure Zero
      14.3.1 Measure Zero
      14.3.2 Volume Zero
      14.4 When is a Function Riemann Integrable?
      14.4.1 Homework
      14.5 Integration and Sets of Measure Zero
      14.5.1 Homework
      15 Change of Variables and Fubini’s Theorem
      15.1 Linear Maps
      15.1.1 Homework
      15.2 The Change of Variable Theorem
      15.2.1 Homework
      15.3 Fubini Type Results
      15.3.1 Fubini on a Rectangle
      15.3.2 Homework
      16 Line Integrals
      16.1 Paths
      16.1.1 Homework
      16.2 Conservative Force Fields
      16.2.1 Homework
      16.3 Potential Functions
      16.3.1 Homework
      16.4 Green’s Theorem
      16.4.1 Homework
      16.5 Green’s Theorem for Images of the Unit Square
      16.5.1 Homework
      16.6 Motivational Notation
      16.6.1 Homework
      17 Differential Forms
      17.1 One Forms
      17.1.1 Smooth Paths
      17.1.2 What is a Winding Number?
      17.2 Exact and Closed 1-Forms
      17.2.1 Smooth Segmented Paths
      17.3 Two and Three Forms
      V Applications
      18 The Exponential Matrix
      18.1 The Exponential Matrix
      18.2 The Jordan Canonical Form
      18.2.1 Homework
      18.3 Exponential Matrix Calculations
      18.3.1 Jordan Block Matrices
      18.3.2 General Matrices
      18.3.3 Homework
      18.4 Applications to Linear ODE
      18.4.1 The Homogeneous Solution
      18.4.2 Homework
      18.5 The Non-Homogeneous Solution
      18.5.1 Homework
      18.6 A Diagonalizable Test Problem
      18.6.1 Homework
      18.7 Simple Jordan Blocks
      18.7.1 Homework
      19 Nonlinear Parametric Optimization Theory
      19.1 The More Precise and Careful Way
      19.2 Unconstrained Parametric Optimization
      19.3 Constrained Parametric Optimization
      19.3.1 Hessian Error Estimates
      19.3.2 A First Look at Constraint Satisfaction
      19.3.3 Constraint Satisfaction and the Implicit Function Theorem
      19.4 Lagrange Multipliers
      VI Summing It All Up
      20 Summing It All Up
      VII References
      VIII Detailed Index