Matrix Poincar\'e, \Phi-Sobolev inequalities, and quantum ensembles

TL;DR

This paper develops new Sobolev-type inequalities for matrix-valued functions, extending classical results to quantum settings, and applies these to bound quantum information quantities like the Holevo quantity.

Contribution

It introduces matrix Poincaré and -Sobolev inequalities for matrix functions, bridging classical and quantum analysis frameworks.

Findings

Established matrix Poincare9 inequalities for Gaussian ensembles.

Derived -Sobolev inequalities for matrix functions on Boolean hypercubes.

Provided bounds for the Holevo quantity in quantum information science.

Abstract

Sobolev-type inequalities have been extensively studied in the frameworks of real-valued functions and non-commutative $\mathbb{L}_p$ spaces, and have proven useful in bounding the time evolution of classical/quantum Markov processes, among many other applications. In this paper, we consider yet another fundamental setting - matrix-valued functions - and prove new Sobolev-type inequalities for them. Our technical contributions are two-fold: (i) we establish a series of matrix Poincar\'e inequalities for separably convex functions and general functions with Gaussian unitary ensembles inputs; and (ii) we derive $\Phi$-Sobolev inequalities for matrix-valued functions defined on Boolean hypercubes and for those with Gaussian distributions. Our results recover the corresponding classical inequalities (i.e.~real-valued functions) when the matrix has one dimension. Finally, as an application of our technical outcomes, we derive the upper bounds for a fundamental entropic quantity - the Holevo quantity - in quantum information science since classical-quantum channels are a special instance of matrix-valued functions. This is obtained through the equivalence between the constants in the strong data processing inequality and the $\Phi$-Sobolev inequality.