Characteristic polynomial of a matrix
This functionality does not run in MATLAB.
linalg::charpoly(A, x) computes the characteristic polynomial of the matrix A. The characteristic polynomial of a n×n matrix is defined by , where In denotes the n×n identity matrix.
The component ring of A must be a commutative ring, i.e., a domain of category Cat::CommutativeRing.
We define a matrix over the rational numbers:
A := Dom::Matrix(Dom::Rational)([[1, 2], [3, 4]])
Then the characteristic polynomial pA(x) is given by:
It is of the domain type:
We define a matrix over ℤ7:
B := Dom::Matrix(Dom::IntegerMod(7))([[1, 2], [3, 0]])
The characteristic polynomial pB(x) of B is given by:
p := linalg::charpoly(B, x)
We compute the zeros of pB(x), i.e., the eigenvalues of the matrix B:
Polynomial of the domain Dom::DistributedPolynomial([x],R), where R is the component ring of A.
linalg::charpoly implements Hessenberg's algorithm to compute the characteristic polynomial of a square matrix A. See: Henri Cohen: A Course in Computational Algebraic Number Theory, GTM 138, Springer Verlag.
This algorithm works for any field and requires only O(n3) field operations, in contrast to O(n4) when computing the determinant of the characteristic matrix of A.
For any other component ring, the characteristic polynomial is computed using the Berkowitz algorithm.
Reference: Jounaidi Abdeljaoued, The Berkowitz Algorithm, Maple and Computing the Characteristic Polynomial in an Arbitrary Commutative Ring, MapleTech Vol 4 No 3, pp 21-32, Birkhäuser, 1997.