# Reference for trace/norm inequality

I'm looking for a reference for a matrix-norm inequality that I used in this answer, which has a few equivalent forms. I will use notation that applies to complex vector spaces with a sesquilinear inner product, but of course the same applies over real matrices.

The statement is as follows:

Take $A,B \in \Bbb F^{n \times n}$. Then $$\vert\operatorname{tr}(A^*B)\vert \leq \sigma_1(A)\sum_{i=1}^n \sigma_i(B) = \|A\| \operatorname{tr}|B|$$ where $\sigma_i$ denotes the $i$th singular value, $|B| = (B^*B)^{1/2}$, and $\|\cdot\|$ denotes the spectral norm (induced Euclidean norm).

I did manage to find some references, but they're overkill, and the texts themselves are not readily accessible to the faint of heart (Bhatia's text is dense and Pedersen's is not about matrices in particular).

A suitable reference would be greatly appreciated.

• Is the sum supposed to be over $\sigma_i(B)$? – Gunnar Þór Magnússon Apr 19 '17 at 14:27
• @GunnarÞórMagnússon of course. Good catch. – Omnomnomnom Apr 19 '17 at 14:30
• Horn and Johnson's Matrix Analysis would be a decent place to go. And the $B=(B^*B)^{1/2}$ is confusing. – Batman Apr 19 '17 at 14:37
• @Batman typo! Good thinking. I don't have it on hand. If someone can point to the page/theorem from Horn and Johnson, I'd accept that. – Omnomnomnom Apr 19 '17 at 14:39
• @Boby This inequality is more closely analogous to Hölder's inequality with $p = \infty, q = 1$. The inequality I use in the first part of my answer is exactly the Cauchy-Schwarz inequality. – Omnomnomnom Apr 19 '17 at 14:46

A proof in linear algebra. I hope you're familiar with SVD.

Lemma 1 For any matrix $A$, $|tr(A)|\le \sum_i \sigma_i(A)$

Proof: By SVD decomposition, and properties of the trace function $$tr(A) = tr(U^*\Sigma V) = tr(\Sigma VU)$$ If $Z=VU$ then it is still an unitary matrix, and $$|tr(\Sigma Z)| = |\sum_i \sigma_i(A)z_{ii}|\le \sum_i |\sigma_i(A)z_{ii}|\le \sum_i \sigma_i(A)$$ since $|z_{ii}|\le 1$.

Lemma 2 For any matrix $A,B$, $\sigma_i(A^*B)\le \sigma_i(A)\sigma_1(B)$

Proof: Using Fischer minmax theorem, we know $$\sigma_i(A^*B) = \max_{\dim V=i}\min_{x\in V,\,\|x\|=1}\|A^*Bx\|$$ but $$\min_{x\in V,\,\|x\|=1} \|A^*Bx\| \le \max_{x\in V,\,\|x\|=1}\|Bx\| \min_{y\in BV,\,\|y\|=1}\|Ay\|$$ so $$\sigma_i(A^*B) \le \max_{\dim V=i}(\max_{x\in V,\,\|x\|=1}\|Bx\| \min_{y\in BV,\,\|y\|=1}\|Ay\|)$$ $$\le \max_{\dim V=i}\max_{x\in V,\,\|x\|=1}\|Bx\| \max_{\dim V=i}\min_{y\in BV,\,\|y\|=1}\|Ay\| \le \sigma_1(B)\sigma_i(A)$$

• That is a nifty proof! I think it's fair to say that any numerical linear algebra person is fine using SVD. Thanks. – Omnomnomnom Apr 19 '17 at 18:45
• @Omnomnomnom Don't take it for granted. I've met people in numerical l.a. who weren't aware of its existence – Exodd Apr 19 '17 at 18:55

This holds true more generally when $\Bbb F^n$ is replaced by a(-ny) Hilbert space $H$.

Let $\mathcal K(H)\,$, $\ell^1(H)$, and $\mathcal L(H)$ denote the compact, the trace class, and all bounded linear operators on $H$, respectively. They form a chain of dual Banach spaces, i.e., each is followed by its (topological) dual.
The duality map is given by the trace-based pairing, which is central to the OP, in detail:
Every continuous linear functional $\varphi$ on $\mathcal K(H)$ has the form $$\varphi(k)=\operatorname{tr}(kt)$$ for some fixed $t\in\ell^1(H)$, and one gets $\big(\mathcal K(H)\big)'=\ell^1(H)$.
Furthermore, every continuous linear functional $\phi$ on $\mathcal\ell^1(H)$ has the form $$\phi(t)=\operatorname{tr}(tx)$$ for some $x\in\mathcal L(H)$, hence $\big(\ell^1(H)\big)'=\mathcal L(H)$.

Note that $\sum_{i=1}^\infty \sigma_i(t) = \operatorname{tr}(\,|t|\,) = \|t\|_{\ell^1}$ which is the trace-class norm; and the norm inequality expresses the continuity in each case.
In the finite-dimensional case one has $\mathcal K(H)=\ell^1(H)=\mathcal L(H)$, but what "remains" is the conceptual & worthwhile view, that the trace implements the duality.

Hope all this is helpful and not an overkill.

Ref's out of my mind are

• Barry Simon: Trace ideals and their applications
• Gohberg & Krein: Introduction to the Theory of Linear nonselfadjoint operators
• Reed & Simon: Methods of Modern mathematical physics, Volume 1
• Again, I was looking for a reference that focuses on the finite dimensional case. I appreciate it, though! – Omnomnomnom Apr 19 '17 at 18:42
• @Omnomnomnom Welcome! (Appears as if I feel less comfortable if there are only finitely many dim's around :-) Just spotted in your post the absence of the absolute value bars to enclose the LHS $\,\operatorname{tr}(A^*B)$. – Hanno Apr 20 '17 at 6:25