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Finite matrix spectral and state calculus
Statement
Use the following conventions on a complex inner-product space of dimension , with inner product linear in its first argument. For an endomorphism , define in an orthonormal basis; step 3.1 proves basis independence. For any Hermitian , its positive spectral subspace (called its positive support here) is ; when this equals . Its support logarithm is , where is the orthogonal projection onto that eigenspace. No value is assigned; for this is the unique endomorphism of the zero space. For the set of positive semidefinite Hermitian endomorphisms with trace one, a point is extreme if every equality with and implies .
Let be a complex inner-product space of finite dimension , with inner product linear in its first argument. Every Hermitian endomorphism has an orthonormal eigenbasis with real eigenvalues. For a real function on its finite spectrum, define by its spectral projections; this definition is independent of the choice of eigenbasis. In particular positive square roots, exponentials, and logarithms on positive supports are well defined.
For a density matrix on , meaning a Hermitian positive semidefinite operator with , for bounded , where . The weighted form satisfies Cauchy–Schwarz, . Finally, , with equality exactly for rank-one densities, and those are exactly the extreme points of the finite density-matrix set.
Facts & Assumptions
Given: A complex inner-product space of finite dimension , a Hermitian , and an ordered orthonormal basis, whose coordinates identify isometrically with .
For every bounded sequence in has a convergent subsequence: every bounded sequence in , , has a convergent subsequence.
Real and complex inner-product spaces and their induced length: the inner product is linear in the first argument, conjugate-linear in the second, and positive definite.
Every finite-dimensional real or complex inner product space has an orthonormal basis supplies an ordered orthonormal basis. Cauchy–Schwarz: , with equality exactly for linearly dependent vectors gives the vector norm estimates used below.
Rational numbers are dense in the reals and countable; finite powers of a countable set are countable, and every nonempty countable set is a surjective image of the natural numbers (The rationals embed densely in the reals, is countably infinite, Every finite power of an at most countable set is at most countable, A nonempty set is at most countable iff it is a surjective image of ).
The Cauchy-sequence reals have the least-upper-bound property: every nonempty bounded-above subset of the Cauchy-sequence real field used in [F4] has a real supremum.
Proof
Choose the ordered orthonormal basis of [F3]. In its coordinates is a real continuous quadratic polynomial, bounded on the unit sphere by the finite sum of the absolute matrix entries. By [F4], enumerate all rational-coordinate vectors , and put when and otherwise. For any unit and , coordinatewise rational approximation gives for such a . Then and the reverse triangle inequality gives . Thus the are dense on the sphere; they are normalizations of rational-coordinate vectors, not necessarily rational-coordinate vectors themselves. The set is nonempty because is a unit vector and is bounded above as just shown; [F5] gives . For each take the least index with , which exists by continuity and density. This deterministic rule uses no countable choice. By [F1] the bounded sequence has a convergent subsequence; its limit has norm one and attains .
Let be a maximizing unit vector and . Differentiating at for real gives . Replacing by shows that the imaginary part also vanishes. Hermiticity gives for every , so with real eigenvalue. Moreover is invariant, since . Induction on , including the one-dimensional case, gives an orthonormal eigenbasis with real eigenvalues.
For , define . The full eigenspaces and their orthogonal projections are intrinsic, so this definition is independent of the basis within each eigenspace. It supplies positive square roots for nonnegative matrices, exponentials for every Hermitian matrix, and the stated logarithm on the positive spectral subspace for every Hermitian : the restriction has exactly the strictly positive eigenvalues. If , the empty spectral sum is the unique endomorphism of that zero space. Finite coordinate sums give , hence invariance under unitary changes of orthonormal basis. Diagonalizing gives for every complex matrix , and in particular .
Put , and . Step 3.1 gives for all complex . If , take to get . If , varying with arbitrarily large magnitude forces , giving the same inequality. This proves the stated weighted Cauchy–Schwarz formula (whose form is conjugate-linear in ).
The density eigenvalues satisfy and , so , with equality exactly when one eigenvalue is one and all others vanish. If a rank-one density is with , then every has . Positivity and the square roots from step 3.1 give . Self-adjointness puts their ranges in , and trace one gives . Conversely, two positive eigenvalues allow a sufficiently small opposite transfer of weight, yielding distinct densities with midpoint . Thus precisely the rank-one densities are extreme.
Depends on
For every bounded sequence in has a convergent subsequence
Real and complex inner-product spaces and their induced length
Every finite-dimensional real or complex inner product space has an orthonormal basis
The rationals embed densely in the reals
is countably infinite
Every finite power of an at most countable set is at most countable
A nonempty set is at most countable iff it is a surjective image of
Cauchy–Schwarz: , with equality exactly for linearly dependent vectors
The Cauchy-sequence reals have the least-upper-bound property