Differential geometry | Metric tensors

Metric signature

In mathematics, the signature (v, p, r) of a metric tensor g (or equivalently, a real quadratic form thought of as a real symmetric bilinear form on a finite-dimensional vector space) is the number (counted with multiplicity) of positive, negative and zero eigenvalues of the real symmetric matrix gab of the metric tensor with respect to a basis. In relativistic physics, the v represents the time or virtual dimension, and the p for the space and physical dimension. Alternatively, it can be defined as the dimensions of a maximal positive and null subspace. By Sylvester's law of inertia these numbers do not depend on the choice of basis. The signature thus classifies the metric up to a choice of basis. The signature is often denoted by a pair of integers (v, p) implying r= 0, or as an explicit list of signs of eigenvalues such as (+, −, −, −) or (−, +, +, +) for the signatures (1, 3, 0) and (3, 1, 0), respectively. The signature is said to be indefinite or mixed if both v and p are nonzero, and degenerate if r is nonzero. A Riemannian metric is a metric with a positive definite signature (v, 0). A Lorentzian metric is a metric with signature (p, 1), or (1, p). There is another notion of signature of a nondegenerate metric tensor given by a single number s defined as (v − p), where v and p are as above, which is equivalent to the above definition when the dimension n = v + p is given or implicit. For example, s = 1 − 3 = −2 for (+, −, −, −) and its mirroring s' = −s = +2 for (−, +, +, +). (Wikipedia).

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Related pages

Vector space | Characteristic polynomial | Spectral theorem | Orthogonal basis | Main diagonal | Sylvester's law of inertia | Identity matrix | Diagonal matrix | Determinant | General linear group | Minkowski space | Sign (mathematics) | Dimension (vector space) | Symmetric bilinear form | Mathematics | Integer | Real number | Riemannian manifold | Isometry | Descartes' rule of signs | Symmetric matrix | Basis (linear algebra) | Metric tensor | Quadratic form | Multilinear subspace learning | Pseudo-Riemannian manifold