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Finite-dimensional Golden–Thompson trace inequality
Statement
For Hermitian matrices with , Here is the norm-convergent finite-matrix exponential series. No commutativity assumption is imposed.
Facts & Assumptions
Given: The Hermitian matrices and the usual Euclidean operator norm. The trace is the sum of diagonal entries as in The trace as the sum of the diagonal entries.
The finite singular value decomposition is supplied by Every linear map between finite-dimensional real or complex inner product spaces admits a singular value decomposition. If are the singular values, set for . The operator norm is the largest singular value; this follows immediately by applying the diagonal singular-value matrix to a unit vector. Unitary multiplication preserves these norms.
Complex spectral theorem: a normal endomorphism of a finite-dimensional complex inner product space has an orthonormal eigenbasis, and conversely supplies orthonormal eigenbases for Hermitian matrices. In particular is unitary for real , and is positive definite. The exponential series converges uniformly on every norm-bounded matrix set, because ; thus it is continuous and its entries are entire functions of a scalar complex multiplier.
Hadamard three-lines theorem: a bounded continuous scalar function on that is holomorphic inside and has boundary moduli at most satisfies for .
Proof
We first record two elementary trace estimates. If is a singular value decomposition, cyclically expanding the finite diagonal sum gives , so . Also , so scalar Cauchy–Schwarz gives , since by the singular value decomposition. These arguments also prove the trace cyclicity used here by interchanging two finite sums.
Set and . The function is entrywise entire and uniformly bounded on the closed strip: for each exponential is the product of a bounded positive real exponential with a unitary imaginary exponential of the same Hermitian matrix. On the line , . On , the identity and unitary invariance give .
We need a finite eigenvalue comparison only for a diagonalizable invertible matrix . Order its eigenvalue moduli and its singular values decreasingly. For , the th exterior space has the orthonormal wedge basis , , and its induced map sends a wedge to the wedge of the images. This defines the finite matrix directly by multilinearity and alternation. The singular value decomposition makes its norm : wedges of the two singular-vector orthonormal bases give diagonal coefficients consisting of all -fold singular-value products. Wedges of the first independent eigenvectors are nonzero eigenvectors with eigenvalue ; nonvanishing follows by expanding independent vectors in a basis and noting that some -minor is nonzero. The norm bounds the modulus of an eigenvalue, proving . This uses only finite bases and finite determinants.
Fix , put and , and choose a singular value decomposition . All are positive because is invertible. Set and , so . Define and . These functions are continuous and bounded on the closed strip and holomorphic inside: their entries are finite sums of entire exponentials and their moduli are bounded uniformly in the imaginary coordinate. On its left boundary , and on its right boundary . The two trace estimates of step 1.1 therefore bound by and on the respective boundaries. Since , one has . Applying [F3] yields .
Put and in decreasing order. Step 1.3 gives for every . For any real , the positive terms form an initial segment, so . For every , multiply by and integrate: , as follows by evaluating the elementary exponential primitive at finite lower limits and sending that limit to . The finite sums can be integrated termwise and all integrands are nonnegative, giving .
For each integer , let . It is similar to the positive definite matrix , since conjugating by gives that matrix. Thus [F2] makes diagonalizable with positive eigenvalues. Apply step 2.2 with and step 2.1 with to obtain .
The exponential series gives and in operator norm, where the constants depend only on the fixed matrices. Also for one fixed . The telescoping identity , valid by cancellation without commutativity, gives . The addition law for exponential series of scalar multiples of one matrix gives . Therefore , using and cyclicity to evaluate the Hilbert–Schmidt square . This is the claimed inequality.
Depends on
- Hadamard three-lines theorem
- Every linear map between finite-dimensional real or complex inner product spaces admits a singular value decomposition
- Complex spectral theorem: a normal endomorphism of a finite-dimensional complex inner product space has an orthonormal eigenbasis, and conversely
- The trace $\operatorname{tr}(A)$ as the sum of the diagonal entries
Used by
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Sources
- Joel A. Tropp, An Introduction to Matrix Concentration Inequalities, §3.3, equation (3.3.3), printed p.34 (standard reference, not scraped)