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Theory of Probability and Its Applications

Probability Measures on the Set of Quantum States in Optimization Problems for Information Quantities

A. S. Holevo

Published Aug 1, 2026• 0 citations
Publisher

Abstract

A number of optimization problems in quantum information theory, such as one-shot classical capacity of a quantum channel, entanglement of formation of a state, classical capacity of a quantum observable, and accessible information of an ensemble of quantum states, can be formulated as the calculation of the convex closure of the output entropy of a certain quantum channel. This general problem can be considered as a convex programming problem for which necessary and sufficient optimality conditions can be established along with a dual problem. These optimality conditions imply some tight lower bounds for entropy, either quantum or classical, which are related to the famous logarithmic Sobolev inequality.

DOI
10.1137/s0040585x97t992987

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A number of optimization problems in quantum information theory, such as one-shot classical capacity of a quantum channel, entanglement of formation of a state, classical capacity of a quantum observable, and accessible information of an ensemble of quantum states, can be formulated as the calculation of the convex closure of the output entropy of a certain quantum channel. This general problem can be considered as a convex programming problem for which necessary and sufficient optimality conditions can be established along with a dual problem. These optimality conditions imply some tight lower bounds for entropy, either quantum or classical, which are related to the famous logarithmic Sobolev inequality.
It is shown that a number of optimization problems in quantum information theory: the χ\chiχ -capacity (called the Holevo capacity in literature) of a quantum channel; the classical capacity of quantum observable; entanglement of formation—can be recast as a generalization of a Bayes problem over the set of all quantum states. This allows us to consider it as a convex programming problem for which necessary and sufficient optimality conditions along with the dual problem can be formulated.
Abstract In this work we apply the general convex programming approach of [A. S. Holevo, Lobachevskii J. Math. 43(7), 1646–1650 (2022)] to the problem of minimization of convex closure of the output differential entropy of quantum measurement channel, involved in computation of the classical capacity of the channel, and representing noise in the channel. We show that in the bosonic Gaussian case the optimality conditions derived from the convex programming approach lead to formulation of some new generalizations of the famous logarithmic Sobolev inequality which we call ‘‘homodyne’’ and ‘‘heterodyne’’ inequalities. We also show that the ‘‘heterodyne’’ inequality implies the ‘‘homodyne’’ one.
Abstract Computing accessible information for an ensemble of quantum states is a basic problem in quantum information theory. We show that the recently obtained optimality criterion (A.S. Holevo, Lobachevskii J. Math., 43, 1646–1650 (2022)), when applied to specific ensembles of states leads to nontrivial tight entropy inequalities that are discrete relatives of the famous log-Sobolev inequality. In this light, the hypothesis of globally information-optimal measurement for an ensemble of equiangular equiprobable states (quantum pyramids) (B.-G. Englert and J. Řeháček, J. Mod. Optics 57 (3), 218–226 (2010)) is reconsidered and the corresponding entropy inequalities are proposed. Via the optimality criterion, this suggests also an approach to the proof of the conjectures concerning globally information-optimal observables for quantum pyramids.
This paper is devoted to further study of the Holevo capacity of infinite-dimensional quantum channels. The existence of a unique optimal average state for a quantum channel constrained by an arbitrary convex set of states is shown. The minimax expression for the Holevo capacity of a constrained channel is obtained. The χ\chiχ-function and the convex closure of the output entropy of an infinite-dimensional quantum channel are considered. It is shown that the χ\chiχ-function of an arbitrary channel is lower semicontinuous on the set of all states and has continuous restrictions to subsets of states with continuous output entropy. The explicit expression for the convex closure of the output entropy of an infinite-dimensional quantum channel is obtained and its properties are explored. It is shown that the convex closure of the output entropy coincides with the convex hull of the output entropy on the set of states with finite output entropy and, similarly to the χ\chiχ-function, it has continuous restrictions to subsets of states with continuous output entropy. The applications of the obtained results to the theory of entanglement are considered. The properties of the convex closure of the output entropy make it possible to generalize some results related to the additivity problem to the infinite-dimensional case.
A long-standing problem in quantum Shannon theory is the classical capacity of bosonic Gaussian channels of various kinds [6].The Hypothesis of Gaussian Maximizers (HGM) states that the full capacity of such channels is attained at Gaussian encodings.A breakthrough was made in the papers [1] and [2], where HGM was proved for the important class of multimode gauge co-or contra-variant Gaussian channels [4].In [8] and [5] the solution was extended to a much broader class of channels satisfying a certain 'threshold condition'.At the same time the HGM remains open for a large variety of Gaussian channels lying beyond the scope of the threshold condition [7].In this note we sketch a novel approach to such problems, based on principles of convex programming, and illustrate it using the characteristic case of an approximate position measurement with energy constraint, underlying noisy Gaussian homodyning in quantum optics.Rather remarkably, for this particular model the method reduces the solution of the optimization problem to a generalization of the celebrated log-Sobolev inequality.Let S be the convex set of all density operators in a separable Hilbert space H of the quantum system and X and Y be standard measurable spaces.Consider a measurement channel M : ρ → p ρ (y) = Tr ρm(y), where ρ ∈ S and m(y) is a uniformly bounded positive operator-valued function of y ∈ Y such that m(y) µ(dy) = I (I is the identity operator on H and µ is a measure).The encoding E = {π(dx), ρ(x)} is a probability measure π(dx) with a measurable family of
We identify necessary and sufficient conditions for a quantum channel to be optimal for any convex optimization problem in which the optimization is taken over the set of all quantum channels of a fixed size. Optimality conditions for convex optimization problems over the set of all quantum measurements of a given system having a fixed number of measurement outcomes are obtained as a special case. In the case of linear objective functions for measurement optimization problems, our conditions reduce to the well-known Holevo-Yuen-Kennedy-Lax measurement optimality conditions. We illustrate how our conditions can be applied to various state transformation problems having non-linear objective functions based on the fidelity, trace distance, and quantum relative entropy.