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Using the language of exterior algebra, the characteristic polynomial of an matrix may be expressed as = = where is the trace of the th exterior power of , which has dimension (). This trace may be computed as the sum of all principal minors of A {\displaystyle A} of size k . {\displaystyle k.}
The trace of a linear map f : V → V can then be defined as the trace, in the above sense, of the element of V ⊗ V* corresponding to f under the above mentioned canonical isomorphism. Using an explicit basis for V and the corresponding dual basis for V*, one can show that this gives the same definition of the trace as given above.
When L/K is separable, the trace provides a duality theory via the trace form: the map from L × L to K sending (x, y) to Tr L/K (xy) is a nondegenerate, symmetric bilinear form called the trace form. If L/K is a Galois extension, the trace form is invariant with respect to the Galois group.
Because matrices are similar if and only if they represent the same linear operator with respect to (possibly) different bases, similar matrices share all properties of their shared underlying operator: Rank; Characteristic polynomial, and attributes that can be derived from it: Determinant; Trace; Eigenvalues, and their algebraic multiplicities
This polynomial is called the characteristic polynomial of A. Equation is called the characteristic equation or the secular equation of A. The fundamental theorem of algebra implies that the characteristic polynomial of an n-by-n matrix A, being a polynomial of degree n, can be factored into the product of n linear terms,
The Cayley–Hamilton theorem says that every square matrix satisfies its own characteristic polynomial.This also implies that all square matrices satisfy + + () = where the coefficients are given by the elementary symmetric polynomials of the eigenvalues of A.
The roots of the characteristic polynomial () are the eigenvalues of ().If there are n distinct eigenvalues , …,, then () is diagonalizable as () =, where D is the diagonal matrix and V is the Vandermonde matrix corresponding to the λ 's: = [], = [].
In linear algebra, similarity invariance is a property exhibited by a function whose value is unchanged under similarities of its domain. That is, f {\displaystyle f} is invariant under similarities if f ( A ) = f ( B − 1 A B ) {\displaystyle f(A)=f(B^{-1}AB)} where B − 1 A B {\displaystyle B^{-1}AB} is a matrix similar to A .