Sylvester's law of inertia
Template:Short description Sylvester's law of inertia is a theorem in matrix algebra about certain properties of the coefficient matrix of a real quadratic form that remain invariant under a change of basis. Namely, if is a symmetric matrix, then for any invertible matrix , the numbers of positive, negative, and zero eigenvalues of are constant (i.e., the inertia of is constant). This result is particularly useful when is diagonal, as the inertia of a diagonal matrix can easily be obtained by looking at the signs of its diagonal elements.
This property is named after James Joseph Sylvester, who published its proof in 1852.[1][2]
Statement
Let be a symmetric square matrix of order with real entries. Any non-singular square matrix of the same order is said to transform into another symmetric matrix Template:Tmath, also of order Template:Tmath, where is the transpose of Template:Tmath. It is also said that matrices and are congruent. If is the coefficient matrix of some quadratic form on Template:Tmath, then is the coefficient matrix of the same form after the change of basis defined by Template:Tmath.
A symmetric matrix can always be transformed in this way into a diagonal matrix which has entries only Template:Tmath, Template:Tmath, Template:Tmath along the diagonal. Sylvester's law of inertia states that the number of diagonal entries of each kind is an invariant of Template:Tmath, i.e., does not depend on the matrix used.
The number of Template:Tmath's, denoted Template:Tmath, is called the positive index of inertia of Template:Tmath, and the number of Template:Tmath's, denoted Template:Tmath, is called the negative index of inertia of Template:Tmath. The number of Template:Tmath's, denoted Template:Tmath, is the dimension of the null space of Template:Tmath, known as the nullity of Template:Tmath. These numbers satisfy the obvious relation
The difference is usually called the signature of Template:Tmath. However, some authors use that term for the triple consisting of the nullity, the positive, and the negative indices of inertia of Template:Tmath. For a non-degenerate form of a given dimension, these are equivalent data; but in general, the triple yields more data.
If the matrix has the property that every principal upper left minor is non-zero, then the negative index of inertia is equal to the number of sign changes in the sequence
Statement in terms of eigenvalues
The law can also be stated as follows: two symmetric square matrices and of the same size have the same numbers of positive, negative, and zero eigenvalues if and only if they are congruent[3] (i.e., Template:Tmath for some non-singular square matrix Template:Tmath).
The positive and negative indices of a symmetric matrix are also the numbers of positive and negative eigenvalues of Template:Tmath. Any symmetric real matrix has an eigendecomposition of the form Template:Tmath, where is a diagonal matrix containing the eigenvalues of Template:Tmath, and is an orthogonal square matrix containing the eigenvectors. The matrix can be written Template:Tmath, where is diagonal with entries Template:Tmath, and is diagonal with each Template:Tmath. The matrix transforms to Template:Tmath, since Template:Tmath.
Statement in terms of quadratic forms
A real quadratic form in variables (or on an Template:Tmath-dimensional real vector space) can, by a suitable change of basis (by non-singular linear transformation from to Template:Tmath), be brought to the diagonal form
- Template:Tmath, with each Template:Tmath.
Sylvester's law of inertia states that the number of coefficients of a given sign is an invariant of Template:Tmath, i.e., does not depend on a particular choice of diagonalizing basis.
Expressed geometrically, the law of inertia says that all maximal subspaces on which the restriction of the quadratic form is positive definite (respectively, negative definite) have the same dimension. These dimensions are the positive and negative indices of inertia of Template:Tmath.
Generalizations
Two complex matrices (i.e., with complex entries) and are said to be Template:Tmath-congruent if (and only if) there exists a non-singular complex matrix such that Template:Tmath, where denotes the conjugate transpose of Template:Tmath.
The definition of inertia is still valid for a Hermitian matrix, as its eigenvalues are always real numbers.
Sylvester's law of inertia can be generalized to complex matrices:
Two Hermitian matrices and are Template:Tmath-congruent if and only if they have the same inertia.
Ostrowski proved a quantitative generalization of Sylvester's law of inertia:[4][5]
If two complex matrices and are Template:Tmath-congruent, with Template:Tmath where is a non-singular complex matrix, then their eigenvalues are related by
where Template:Tmath, and each is such that
A theorem due to Ikramov generalizes the law of inertia to normal matrices:[6]
Two normal matrices and are Template:Tmath-congruent if and only if they have the same number of eigenvalues on each open ray from the origin in the complex plane.Template:Efn