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Euclidean vector spaces
Aaron Greicius
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\(\newcommand{\Z}{{\mathbb Z}} \newcommand{\Q}{{\mathbb Q}} \newcommand{\R}{{\mathbb R}} \newcommand{\C}{{\mathbb C}} \newcommand{\T}{{\mathbb T}} \newcommand{\F}{{\mathbb F}} \newcommand{\HH}{{\mathbb H}} \newcommand{\compose}{\circ} \newcommand{\bolda}{{\mathbf a}} \newcommand{\boldb}{{\mathbf b}} \newcommand{\boldc}{{\mathbf c}} \newcommand{\boldd}{{\mathbf d}} \newcommand{\bolde}{{\mathbf e}} \newcommand{\boldi}{{\mathbf i}} \newcommand{\boldj}{{\mathbf j}} \newcommand{\boldk}{{\mathbf k}} \newcommand{\boldn}{{\mathbf n}} \newcommand{\boldp}{{\mathbf p}} \newcommand{\boldq}{{\mathbf q}} \newcommand{\boldr}{{\mathbf r}} \newcommand{\bolds}{{\mathbf s}} \newcommand{\boldt}{{\mathbf t}} \newcommand{\boldu}{{\mathbf u}} \newcommand{\boldv}{{\mathbf v}} \newcommand{\boldw}{{\mathbf w}} \newcommand{\boldx}{{\mathbf x}} \newcommand{\boldy}{{\mathbf y}} \newcommand{\boldz}{{\mathbf z}} \newcommand{\boldzero}{{\mathbf 0}} \newcommand{\boldmod}{\boldsymbol{ \bmod }} \newcommand{\boldT}{{\mathbf T}} \newcommand{\boldN}{{\mathbf N}} \newcommand{\boldB}{{\mathbf B}} \newcommand{\boldF}{{\mathbf F}} \newcommand{\boldS}{{\mathbf S}} \newcommand{\boldG}{{\mathbf G}} \newcommand{\boldK}{{\mathbf K}} \newcommand{\boldL}{{\mathbf L}} \DeclareMathOperator{\lcm}{lcm} \DeclareMathOperator{\Span}{span} \DeclareMathOperator{\tr}{tr} \DeclareMathOperator{\NS}{null} \DeclareMathOperator{\RS}{row} \DeclareMathOperator{\CS}{col} \DeclareMathOperator{\im}{im} \DeclareMathOperator{\range}{range} \DeclareMathOperator{\rank}{rank} \DeclareMathOperator{\nullity}{nullity} \DeclareMathOperator{\sign}{sign} \DeclareMathOperator{\Fix}{Fix} \DeclareMathOperator{\Aff}{Aff} \DeclareMathOperator{\Frac}{Frac} \DeclareMathOperator{\Ann}{Ann} \DeclareMathOperator{\Tor}{Tor} \DeclareMathOperator{\id}{id} \DeclareMathOperator{\mdeg}{mdeg} \DeclareMathOperator{\Lt}{Lt} \DeclareMathOperator{\Lc}{Lc} \DeclareMathOperator{\disc}{disc} \DeclareMathOperator{\Frob}{Frob} \DeclareMathOperator{\adj}{adj} \DeclareMathOperator{\curl}{curl} \DeclareMathOperator{\grad}{grad} \DeclareMathOperator{\diver}{div} \DeclareMathOperator{\flux}{flux} \def\Gal{\operatorname{Gal}} \def\ord{\operatorname{ord}} \def\ML{\operatorname{M}} \def\GL{\operatorname{GL}} \def\PGL{\operatorname{PGL}} \def\SL{\operatorname{SL}} \def\PSL{\operatorname{PSL}} \def\GSp{\operatorname{GSp}} \def\PGSp{\operatorname{PGSp}} \def\Sp{\operatorname{Sp}} \def\PSp{\operatorname{PSp}} \def\Aut{\operatorname{Aut}} \def\Inn{\operatorname{Inn}} \def\Hom{\operatorname{Hom}} \def\End{\operatorname{End}} \def\ch{\operatorname{char}} \def\Zp{\Z/p\Z} \def\Zm{\Z/m\Z} \def\Zn{\Z/n\Z} \def\Fp{\F_p} \newcommand{\surjects}{\twoheadrightarrow} \newcommand{\injects}{\hookrightarrow} \newcommand{\bijects}{\leftrightarrow} \newcommand{\isomto}{\overset{\sim}{\rightarrow}} \newcommand{\floor}[1]{\lfloor#1\rfloor} \newcommand{\ceiling}[1]{\left\lceil#1\right\rceil} \newcommand{\mclass}[2][m]{[#2]_{#1}} 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\newcommand{\abcdmatrix}[4]{\begin{bmatrix}#1\amp #2\\ #3\amp #4 \end{bmatrix} } \newenvironment{amatrix}[1][ccc|c]{\left[\begin{array}{#1}}{\end{array}\right]} \newenvironment{linsys}[2][m]{ \begin{array}[#1]{@{}*{#2}{rc}r@{}} }{ \end{array}} \newcommand{\eqsys}{\begin{array}{rcrcrcr} a_{11}x_{1}\amp +\amp a_{12}x_{2}\amp +\cdots+\amp a_{1n}x_{n}\amp =\amp b_1\\ a_{21}x_{1}\amp +\amp a_{22}x_{2}\amp +\cdots+\amp a_{2n}x_{n}\amp =\amp b_2\\ \amp \vdots\amp \amp \vdots \amp \amp \vdots \amp \\ a_{m1}x_{1}\amp +\amp a_{m2}x_{2}\amp +\cdots +\amp a_{mn}x_{n}\amp =\amp b_m \end{array} } \newcommand{\numeqsys}{\begin{array}{rrcrcrcr} e_1:\amp a_{11}x_{1}\amp +\amp a_{12}x_{2}\amp +\cdots+\amp a_{1n}x_{n}\amp =\amp b_1\\ e_2: \amp a_{21}x_{1}\amp +\amp a_{22}x_{2}\amp +\cdots+\amp a_{2n}x_{n}\amp =\amp b_2\\ \amp \vdots\amp \amp \vdots \amp \amp \vdots \amp \\ e_m: \amp a_{m1}x_{1}\amp +\amp a_{m2}x_{2}\amp +\cdots +\amp a_{mn}x_{n}\amp =\amp b_m \end{array} } 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Front Matter
Colophon
Acknowledgements
0
Foundations
0.1
Sets
0.1
Exercises
0.2
Functions
0.2
Exercises
0.3
Tuples and Cartesian products
0.4
Logic
0.4.1
Propositional logic
0.4.2
Predicate logic
0.4.3
Exercises
0.5
Proof techniques
0.5.1
Logical structure
Implication
Disjunction
Equivalence
Chains of implications/equivalences
Proof by contradiction
0.5.2
Equalities
Chain of equalities
0.5.3
Basic set properties
Set inclusion
Set equality
0.5.4
Basic function properties
Function equality
Injective, surjective, bijective
0.5.5
Mathematical induction
Proof by induction
Proof by strong induction
0.6
Complex numbers
0.6.1
Definition of
\(\C\)
0.6.2
Absolute value and complex conjugation
0.6.3
Exercises
0.7
Polynomials
0.7.1
Basic definitions
0.7.2
Degree of a polynomial
0.7.3
Factoring polynomials
0.7.4
Exercises
1
Euclidean
\(n\)
-space
1.1
Vector space structure of
\(\R^n\)
1.1.1
Vector operations on
\(\R^n\)
Vector spaces
1.1.2
Visualizing
\(\R^n\)
1.1.3
Exercises
1.2
Inner product structure of
\(\R^n\)
2
Systems of linear equations
2.1
Systems of linear equations
2.1.1
Systems of linear equations
2.1.2
Row operations
2.1.3
Exercises
2.2
Gaussian elimination
2.2.1
Row echelon matrices
2.2.2
Gaussian elimination
Model example
2.2.3
Exercises
2.3
Solving linear systems
2.3.1
Model example continued
2.3.2
General method for solving linear systems
2.3.3
Vector parametrization description
2.3.4
Exercises
3
Matrices, their arithmetic, and their algebra
3.1
Matrix arithmetic
3.1.1
The basics
3.1.2
Vector space structure of
\(M_{mn}\)
3.1.3
Matrix multiplication
3.1.4
Alternative methods of multiplication
3.1.5
Transpose of a matrix
3.1.6
Exercises
3.2
Matrix algebra
3.2.1
Matrix multiplication properties
3.2.2
Cancellation laws fulfilled and violated
3.2.3
Transpostition properties
3.2.4
Exercises
3.3
Invertible matrices
3.3.1
Invertible matrices
3.3.2
Powers of matrices, matrix polynomials
3.3.3
Exercises
3.4
The invertibility theorem
3.4.1
Elementary matrices
3.4.2
Interlude on matrix equations
3.4.3
The invertibility theorem
3.4.4
Invertibility algorithms
3.4.5
Some theoretical loose ends
3.4.6
Exercises
3.5
The determinant
3.5.1
Definition of the determinant
3.5.2
Expansion along rows and columns
3.5.3
Row operations and determinant
3.5.4
Exercises
4
Vector spaces
4.1
Subspaces
4.1.1
Definition of subspace
4.1.2
Subspaces of
\(\R^n\)
4.1.3
Important subspaces of
\(M_{nn}\)
4.1.4
Exercises
4.2
Span and linear independence
4.2.1
Span
4.2.2
Linear independence
4.2.3
Invertibility, span, and linear independence
4.2.4
Exercises
4.3
Bases
4.3.1
Bases of vector spaces
4.3.2
Exercises
4.4
Dimension
4.4.1
Dimension of a vector space
4.4.2
Further properties of dimension
4.4.3
Exercises
4.5
Fundamental spaces
4.5.1
Fundamental spaces of matrices
4.5.2
Contracting and expanding to bases
4.5.3
Fundamental spaces and invertibility
4.5.4
Exercises
5
Linear transformations
5.1
Linear transformations
5.1.1
Linear transformations
5.1.2
Bases and linear transformations
5.1.3
Matrix transformations
5.1.4
Reflections and rotations in the plane
5.1.5
Composition of linear transformations and matrix multiplication
5.1.6
Exercises
5.2
Null space, image, and isomophisms
5.2.1
Null space and image
5.2.2
The rank-nullity theorem
5.2.3
Injective and surjective linear transformations
5.2.4
Invertibility and isomorphisms
5.2.5
Exercises
5.3
Coordinate vectors
5.3.1
Coordinate vectors
5.3.2
Coordinate vector transformation
5.3.3
Exercises
5.4
Matrix representations of linear transformations
5.4.1
Matrix representations of linear transformations
5.4.2
Matrix representations as models
5.4.3
Exercises
5.5
Change of basis
5.5.1
Change of basis matrix
5.5.2
Change of basis for transformations
5.5.3
Similarity and the holy commutative tent of linear algebra
5.5.4
Exercises
6
Eigenvectors and diagonalization
6.1
Eigenvectors and eigenvalues
6.1.1
Eigenvectors
6.1.2
Finding eigenvalues and eigenvectors systematically
6.1.3
Properties of the characteristic polynomial
6.1.4
Exercises
6.2
Diagonalization
6.2.1
Diagonalizable transformations
6.2.2
Linear independence of eigenvectors
6.2.3
Diagonalizable matrices
6.2.4
Algebraic and geometric multiplicity
6.2.5
Exercises
7
Inner product spaces
7.1
Inner product spaces
7.1.1
Norm and distance
7.1.2
Cauchy-Schwarz inequality, triangle inequalities, and angles between vectors
7.1.3
Choosing your inner product
7.1.4
Exercises
7.2
Orthogonal bases
7.2.1
Orthogonal vectors and sets
7.2.2
Orthogonal bases
7.2.3
Coordinate vectors and matrix representations
7.2.4
Exercises
7.3
Orthogonal projection
7.3.1
Orthogonal complement
7.3.2
Orthogonal Projection
7.3.3
Orthogonal projection in
\(\R^2\)
and
\(\R^3\)
7.3.4
Trigonometric polynomial approximation
7.3.5
Least-squares solution to linear systems
7.3.6
Exercises
7.4
The spectral theorem
7.4.1
Self-adjoint operators
7.4.2
The spectral theorem for self-adjoint operators
7.4.3
Exercises
Backmatter
A
Notation
B
Exercises
C
Definitions
D
Theory and procedures
E
Examples
F
Sage examples
G
Figures and video examples
H
Mantras and fiats
Index
Colophon
Colophon
Website
Personal website
©2020–2025 Aaron Greicius
This work is licensed under the Creative Commons Attribution-ShareAlike 4.0 International License. To view a copy of this license, visit
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