MatrixPolynomialValue[poly,m,x]
evaluates the polynomial poly in the variable x at the matrix m.
MatrixPolynomialValue[{c0,c1,…},m]
evaluates the polynomial whose coefficients are given by the ci at the matrix m.
MatrixPolynomialValue
MatrixPolynomialValue[poly,m,x]
evaluates the polynomial poly in the variable x at the matrix m.
MatrixPolynomialValue[{c0,c1,…},m]
evaluates the polynomial whose coefficients are given by the ci at the matrix m.
Details
- MatrixPolynomialValue evaluates a polynomial with square matrices as variables and scalar coefficients.
- MatrixPolynomialValue[c0+c1x+⋯+cnxn,m,x] gives
. » - MatrixPolynomialValue[{c0,c1,…,cn},m] also gives
. » - Matrix polynomials occur in the study of matrix algebra such as in the statement of the Cayley–Hamilton theorem, which asserts that MatrixPolynomialValue[CharacteristicPolynomial[m,x],m,x] is the zero matrix. »
Examples
open all close allBasic Examples (2)
Scope (10)
Basic Uses (5)
Both the matrix and the polynomial coefficients can be symbolic:
Matrix polynomial evaluation of a real matrix:
Matrix polynomial evaluation of a complex matrix:
Matrix polynomial evaluation of an exact matrix:
Compute a polynomial function—expressed as a list of coefficients—of a symbolic matrix:
Recompute with the polynomial expressed in explicit form:
Verify that both results are consistent with the definition:
Special Matrices (5)
Evaluate the polynomial of spare matrices; the result is also sparse:
Evaluate the polynomial of structured matrices including symmetrized arrays:
For quantity arrays, the coefficients must have units for the sum to be dimensionally consistent:
Use MatrixPolynomialValue with an identity matrix:
The result is equivalent to multiplying the identical matrix by the polynomial evaluated at the point
:
Use MatrixPolynomialValue with a diagonal matrix:
The result is equivalent to evaluating the polynomial at each of the diagonal entries:
The polynomial value of JordanMatrix[λ,k] yields the polynomial on the diagonal plus a correction above the diagonal:
Applications (2)
The Cayley–Hamilton theorem states that any matrix is a root of its characteristic polynomial:
Use CharacteristicPolynomial to find this polynomial:
The value of the polynomial evaluated at m is a zero matrix:
The lowest-degree polynomial of which m is a root is given by MatrixMinimalPolynomial:
The minimal polynomial always divides the characteristic polynomial:
Approximate the cosine of a matrix with a degree-four power series:
Compare with the result returned by MatrixFunction:
Properties & Relations (5)
MatrixPolynomialValue[c0+c1x+⋯+cnxn,m,x] gives
:
MatrixPolynomialValue[{c0,c1,…,cn},m] gives
:
MatrixPolynomialValue[CharacteristicPolynomial[m,x],m,x] is zero by the Cayley–Hamilton theorem:
MatrixPolynomialValue[MatrixMinimalPolynomial[m,x],m,x] is zero by definition:
History
Text
Wolfram Research (2025), MatrixPolynomialValue, Wolfram Language function, https://reference.wolfram.com/language/ref/MatrixPolynomialValue.html.
CMS
Wolfram Language. 2025. "MatrixPolynomialValue." Wolfram Language & System Documentation Center. Wolfram Research. https://reference.wolfram.com/language/ref/MatrixPolynomialValue.html.
APA
Wolfram Language. (2025). MatrixPolynomialValue. Wolfram Language & System Documentation Center. Retrieved from https://reference.wolfram.com/language/ref/MatrixPolynomialValue.html
BibTeX
@misc{reference.wolfram_2025_matrixpolynomialvalue, author="Wolfram Research", title="{MatrixPolynomialValue}", year="2025", howpublished="\url{https://reference.wolfram.com/language/ref/MatrixPolynomialValue.html}", note=[Accessed: 15-November-2025]}
BibLaTeX
@online{reference.wolfram_2025_matrixpolynomialvalue, organization={Wolfram Research}, title={MatrixPolynomialValue}, year={2025}, url={https://reference.wolfram.com/language/ref/MatrixPolynomialValue.html}, note=[Accessed: 15-November-2025]}