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Finite-dimensional Golden–Thompson trace inequality

Statement

For Hermitian matrices H,K∈Cp×p with p≥1, tr⁡exp⁡(H+K)≤tr⁡(exp⁡(H)exp⁡(K)). Here exp⁡(A)=∑j=0∞Aj/j! is the norm-convergent finite-matrix exponential series. No commutativity assumption is imposed.

Facts & Assumptions

Given: The Hermitian matrices H,K and the usual Euclidean operator norm. The trace is the sum of diagonal entries as in The trace tr⁡(A) as the sum of the diagonal entries.

[F1]

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 sj(A) are the singular values, set ∥A∥q=(∑jsj(A)q)1/q for q≥1. 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.

[F2]

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 exp⁡(itH) is unitary for real t, and exp⁡(H) is positive definite. The exponential series converges uniformly on every norm-bounded matrix set, because ∥Aj/j!∥≤∥A∥j/j!; thus it is continuous and its entries are entire functions of a scalar complex multiplier.

[F3]

Hadamard three-lines theorem: a bounded continuous scalar function on 0≤Re⁡z≤1 that is holomorphic inside and has boundary moduli at most M0,M1 satisfies ∣f(s)∣≤M01−sM1s for 0<s<1.

Proof

technique · direct
1.1F1givenalgebra

We first record two elementary trace estimates. If A=Udiag⁡(aj)V∗ is a singular value decomposition, cyclically expanding the finite diagonal sum gives tr⁡(AB)=∑jaj⟨V∗BUej,ej⟩, so ∣tr⁡(AB)∣≤∥A∥1∥B∥op. Also tr⁡(AB)=∑i,jAijBji, so scalar Cauchy–Schwarz gives ∣tr⁡(AB)∣≤∥A∥2∥B∥2, since ∥A∥22=tr⁡(A∗A)=∑i,j∣Aij∣2 by the singular value decomposition. These arguments also prove the trace cyclicity used here by interchanging two finite sums.

1.2F1F2algebra

Set F(z)=exp⁡(zH/2)exp⁡(zK/2) and M=∥exp⁡(H/2)exp⁡(K/2)∥2>0. The function F is entrywise entire and uniformly bounded on the closed strip: for z=x+iy each exponential is the product of a bounded positive real exponential with a unitary imaginary exponential of the same Hermitian matrix. On the line x=0, ∥F(iy)∥op=1. On x=1, the identity F(1+iy)=exp⁡(iyH/2)exp⁡(H/2)exp⁡(K/2)exp⁡(iyK/2) and unitary invariance give ∥F(1+iy)∥2=M.

1.3F1constructalgebra

We need a finite eigenvalue comparison only for a diagonalizable invertible matrix A. Order its eigenvalue moduli and its singular values decreasingly. For 1≤k≤p, the kth exterior space has the orthonormal wedge basis ej1∧⋯∧ejk, j1<⋯<jk, and its induced map sends a wedge to the wedge of the images. This defines the finite matrix ⋀kA directly by multilinearity and alternation. The singular value decomposition makes its norm ∏j=1ksj(A): wedges of the two singular-vector orthonormal bases give diagonal coefficients consisting of all k-fold singular-value products. Wedges of the first k independent eigenvectors are nonzero eigenvectors with eigenvalue ∏j=1kλj(A); nonvanishing follows by expanding independent vectors in a basis and noting that some k-minor is nonzero. The norm bounds the modulus of an eigenvalue, proving ∏j=1k∣λj(A)∣≤∏j=1ksj(A). This uses only finite bases and finite determinants.

2.1F1F2F3step 1.1step 1.2constructalgebra

Fix 0<s<1, put q=2/s and q′=2/(2−s), and choose a singular value decomposition F(s)=Udiag⁡(aj)V∗. All aj are positive because F(s) is invertible. Set N=(∑jajq)1/q>0 and bj=(aj/N)q−1, so ∑jbjq′=1. Define G(z)=Vdiag⁡(exp⁡(q′(1−z/2)log⁡bj))U∗ and g(z)=tr⁡(G(z)F(z)). 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 ∥G(iy)∥1=∑jbjq′=1, and on its right boundary ∥G(1+iy)∥2=(∑jbjq′)1/2=1. The two trace estimates of step 1.1 therefore bound ∣g∣ by 1 and M on the respective boundaries. Since q′(1−s/2)=1, one has g(s)=∑jajbj=N. Applying [F3] yields ∥F(s)∥2/s≤Ms.

2.2step 1.3algebra

Put xj=log⁡∣λj(A)∣ and yj=log⁡sj(A) in decreasing order. Step 1.3 gives ∑j=1kxj≤∑j=1kyj for every k. For any real u, the positive terms form an initial segment, so ∑j(xj−u)+=max⁡0≤k≤p(∑j=1kxj−ku)≤∑j(yj−u)+. For every c>0, multiply by c2ecu and integrate: c2∫−∞x(x−u)ecu du=ecx, 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 ∑j∣λj(A)∣c≤∑jsj(A)c.

3.1F2step 1.2step 2.1step 2.2algebra

For each integer n≥2, let An=F(1/n). It is similar to the positive definite matrix exp⁡(K/4n)exp⁡(H/2n)exp⁡(K/4n), since conjugating An by exp⁡(K/4n) gives that matrix. Thus [F2] makes An diagonalizable with positive eigenvalues. Apply step 2.2 with c=2n and step 2.1 with s=1/n to obtain tr⁡(An2n)≤∑jsj(An)2n=∥An∥2n2n≤M2.

4.1F1F2step 1.1step 3.1algebra∎

The exponential series gives An=I+(H+K)/(2n)+O(n−2) and Bn:=exp⁡((H+K)/(2n))=I+(H+K)/(2n)+O(n−2) in operator norm, where the constants depend only on the fixed matrices. Also ∥An∥,∥Bn∥≤ec/n for one fixed c. The telescoping identity AN−BN=∑j=0N−1Aj(A−B)BN−1−j, valid by cancellation without commutativity, gives ∥An2n−Bn2n∥=O(n−1). The addition law for exponential series of scalar multiples of one matrix gives Bn2n=exp⁡(H+K). Therefore tr⁡exp⁡(H+K)=lim⁡ntr⁡(An2n)≤M2=tr⁡(exp⁡(H)exp⁡(K)), using ∣tr⁡C∣≤p∥C∥op and cyclicity to evaluate the Hilbert–Schmidt square M2. This is the claimed inequality.

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