When we have a square matrix of size $n$, $A$, and we multiply it by a vector $x$ from ${\u2102}^{n}$ to form the matrix-vector product (Definition MVP), the result is another vector in ${\u2102}^{n}$. So we can adopt a functional view of this computation — the act of multiplying by a square matrix is a function that converts one vector ($x$) into another one ($Ax$) of the same size. For some vectors, this seemingly complicated computation is really no more complicated than scalar multiplication. The vectors vary according to the choice of $A$, so the question is to determine, for an individual choice of $A$, if there are any such vectors, and if so, which ones. It happens in a variety of situations that these vectors (and the scalars that go along with them) are of special interest.

We will be solving polynomial equations in this chapter, which raises the specter of roots that are complex numbers. This distinct possibility is our main reason for entertaining the complex numbers throughout the course. You might be moved to revisit Section CNO and Section O.

Section EE Eigenvalues and Eigenvectors

Subsection EEM: Eigenvalues and Eigenvectors of a Matrix

Subsection PM: Polynomials and Matrices

Subsection EEE: Existence of Eigenvalues and Eigenvectors

Subsection CEE: Computing Eigenvalues and Eigenvectors

Subsection ECEE: Examples of Computing Eigenvalues and Eigenvectors

Subsection READ: Reading Questions

Subsection EXC: Exercises

Subsection SOL: Solutions

Section PEE Properties of Eigenvalues and Eigenvectors

Subsection ME: Multiplicities of Eigenvalues

Subsection EHM: Eigenvalues of Hermitian Matrices

Subsection READ: Reading Questions

Subsection EXC: Exercises

Subsection SOL: Solutions

Section SD Similarity and Diagonalization

Subsection SM: Similar Matrices

Subsection PSM: Properties of Similar Matrices

Subsection D: Diagonalization

Subsection FS: Fibonacci Sequences

Subsection READ: Reading Questions

Subsection EXC: Exercises

Subsection SOL: Solutions

Annotated Acronyms E: Eigenvalues

Subsection EEM: Eigenvalues and Eigenvectors of a Matrix

Subsection PM: Polynomials and Matrices

Subsection EEE: Existence of Eigenvalues and Eigenvectors

Subsection CEE: Computing Eigenvalues and Eigenvectors

Subsection ECEE: Examples of Computing Eigenvalues and Eigenvectors

Subsection READ: Reading Questions

Subsection EXC: Exercises

Subsection SOL: Solutions

Section PEE Properties of Eigenvalues and Eigenvectors

Subsection ME: Multiplicities of Eigenvalues

Subsection EHM: Eigenvalues of Hermitian Matrices

Subsection READ: Reading Questions

Subsection EXC: Exercises

Subsection SOL: Solutions

Section SD Similarity and Diagonalization

Subsection SM: Similar Matrices

Subsection PSM: Properties of Similar Matrices

Subsection D: Diagonalization

Subsection FS: Fibonacci Sequences

Subsection READ: Reading Questions

Subsection EXC: Exercises

Subsection SOL: Solutions

Annotated Acronyms E: Eigenvalues