Positive-semidefinite matrix algebra #
This file supplements Mathlib's Matrix.PosSemidef API for matrices indexed by arbitrary types.
It provides rank-one and constant matrices, finite pointwise sums and Schur products, Schur powers,
and the quadratic-form characterization.
The results apply in particular to positive-definite kernels, represented directly as matrices, but do not depend on Tau Ceti's positive-definite-function theory.
They supply the matrix prerequisites for Part C of the OneParameterSemigroups roadmap, including
the positive-definite-function/kernel correspondence and the GNS/Kolmogorov decomposition. No
Mathlib code is vendored.
Main declarations #
TauCeti.posSemidef_rankOne: rank-one positive-semidefinite matrices.TauCeti.posSemidef_const_oneandTauCeti.posSemidef_const_of_nonneg: constant matrices.TauCeti.posSemidef_iff_finite_sum: the quadratic-form characterization.TauCeti.posSemidef_finset_sum: finite pointwise sums.TauCeti.posSemidef_schur_finset_prodandTauCeti.posSemidef_schur_pow: finite Schur products and Schur powers.
References #
- C. Berg, J. P. R. Christensen, P. Ressel, Harmonic Analysis on Semigroups (GTM 100, 1984), Chapter 3.
The rank-one matrix (a, b) ↦ star (g a) · g b is positive semidefinite for an arbitrary
index type. Such matrices are elementary building blocks for positive-semidefinite matrices;
taking g ≡ 1 gives the constant matrix 1.
The constant matrix with value 1 is positive semidefinite.
A nonnegative constant gives a positive-semidefinite constant matrix.
The quadratic-form characterization of an arbitrary-index positive-semidefinite matrix. The
reverse direction constructs positivity from conjugate symmetry and finite quadratic-form
nonnegativity without unfolding Matrix.PosSemidef.
Finite pointwise sums of positive-semidefinite matrices are positive semidefinite.
Finite pointwise Schur products of positive-semidefinite matrices are positive semidefinite.
Schur powers of a positive-semidefinite matrix are positive semidefinite.