Eigenvalues and Eigenvectors.

Let be an matrix. If there exists a non-zero vector such that for some scalar then

  • The scalar is called an eigenvalue of .
  • The vector is called an eigenvector of .

Remark

  • In general, given any matrix, . A scalar is an eigenvalue of iff the homogeneous equation has a non-trivial solution .
  • The homogeneous equation has a non-trivial solution iff is singular, which in turn is equivalent to .
  • The equation is called the characteristic equation of the matrix . The solutions to the characteristic equation are the eigenvalues of .
  • For each eigenvalue , we can find the corresponding eigenvector by solving the equation

Algebraic and Geometric Multiplicity

Suppose is an matrix with eigenvalues , some of them may be repeated.

  • If one of the appears times as a root to the characteristic equation then we say has algebraic multiplicity .
  • If an eigenvalue gives rise to linearly independent eigenvectors, then we say that has geometric multiplicity .

Homogeneous Linear Systems with Constant Coefficients

Suppose the matrix has eigenvalues (some of them may be repeated) and linearly independent eigenvectors . Then the general solution to the homogeneous system is given by
where ‘s are arbitrary constants.