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arXiv:1710.02409 · Journal of Physics A Mathematical and Theoretical

Recovery map stability for the data processing inequality

Eric A. Carlen, Anna Vershynina

Published Nov 22, 2019• 26 citations
arXivHTMLPDF

Abstract

Abstract Let be a finite dimensional von Neumann algebra and a von Neumann subalgebra of it. For states and on , let and be the corresponding states induced on . The data processing inequality implies that where is the relative entropy. Petz proved that there is equality if and only if , where is the Petz recovery map . We prove a quantitative version of Petz’s theorem. In it simplest form, our bound is where is the relative modular operator. Since , this yields a bound that is independent of . We also prove an analogous result with a more complicated constant in which the roles of and are interchanged on the right. Quantum information theoretic inequalities are usually much harder to prove, or differ from, their classical counterparts because classical proofs often rely on conditioning argument that do not carry over to the quantum setting. In particular, quantum conditional expectations rarely preserve expectations—something that always happens in the classical setting. We also prove a simple theorem characterizing states and subalgebras for which conditional expectations do preserve expectation with respect to , illuminating the quantum obstacle to the existence of nicely behaved conditional expectations and the origins the Petz recovery map.

DOI
10.1088/1751-8121/ab5ab7

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Abstract Let be a finite dimensional von Neumann algebra and a von Neumann subalgebra of it. For states and on , let and be the corresponding states induced on . The data processing inequality implies that where is the relative entropy. Petz proved that there is equality if and only if , where is the Petz recovery map . We prove a quantitative version of Petz’s theorem. In it simplest form, our bound is where is the relative modular operator. Since , this yields a bound that is independent of . We also prove an analogous result with a more complicated constant in which the roles of and are interchanged on the right. Quantum information theoretic inequalities are usually much harder to prove, or differ from, their classical counterparts because classical proofs often rely on conditioning argument that do not carry over to the quantum setting. In particular, quantum conditional expectations rarely preserve expectations—something that always happens in the classical setting. We also prove a simple theorem characterizing states and subalgebras for which conditional expectations do preserve expectation with respect to , illuminating the quantum obstacle to the existence of nicely behaved conditional expectations and the origins the Petz recovery map.
We prove a number of quantitative stability bounds for the cases of equality in Petz's monotonicity theorem for quasi-relative entropies Sf(p||σ) defined in terms of an operator monotone decreasing functions f and, in particular, the Rényi relative entropies. Included in our results are bounds in terms of the Petz recovery map, but we obtain more general results. The present treatment is entirely elementary and developed in the context of finite dimensional von Neumann algebras, where the results are already non-trivial and of interest in quantum information theory.
In this paper, we discuss a refinement of quantum data processing inequality for the sandwiched quasi-relative entropy S2\mathcal{S}_2S2​ on a tracial von-Neumann algebra. The main result is a universal recoverability bound with the Petz recovery map, which was previously obtained in the finite dimensional setup.
The quantum relative entropy between two states satisfies a monotonicity property meaning that applying the same quantum channel to both states can never increase their relative entropy. It is known that this inequality is only tight when there is a recovery map that exactly reverses the effects of the quantum channel on both states. In this paper, we strengthen this inequality by showing that the difference of relative entropies is bounded below by the measured relative entropy between the first state and a recovered state from its processed version. The recovery map is a convex combination of rotated Petz recovery maps and perfectly reverses the quantum channel on the second state. As a special case, we reproduce recent lower bounds on the conditional mutual information, such as the one proved by Fawzi and Renner. Our proof only relies on the elementary properties of pinching maps and the operator logarithm.
The quantum data processing inequality asserts that quantum relative entropy is monotonically non-increasing under quantum channels. Here, we promote this fundamental inequality to an exact equality via boundary and surface Poisson integral representations across a complex strip. The relative-entropy loss is resolved into two independent, nonnegative physical mechanisms: an operational Petz recovery component governing state reconstructibility, and a boundary term measuring the mismatch of relative modular dynamics. We further express the loss as the measured relative entropy between the original state and its averaged Petz recovery state plus a nonnegative variational remainder. For the Belavkin--Staszewski (BS) loss, analogous integral representations yield a decomposition into negative log Uhlmann fidelity with an averaged reconstruction plus a nonnegative variational remainder. Furthermore, we establish recovery bounds at any prescribed modular parameter, including the canonical unrotated Petz map, with optimal square-root scaling in the relative entropy loss. The prefactors depend on distinct-eigenvalue counts or logarithmic spectral quantities, improving upon the inverse-power dependence on small eigenvalues in previous bounds.
The quantum relative entropy between two states satisfies a monotonicity property, meaning that applying the same quantum channel to both states can never increase their relative entropy. It is known that this inequality is only tight when there is a “recovery map” that exactly reverses the effects of the quantum channel on both states. In this paper we strengthen this inequality by showing that the difference of relative entropies is bounded below by the measured relative entropy between the first state and a recovered state from its processed version. The recovery map is a convex combination of rotated Petz recovery maps and perfectly reverses the quantum channel on the second state. As a special case we reproduce recent lower bounds on the conditional mutual information such as the one proved in [Fawzi and Renner, Commun. Math. Phys., 2015]. Our proof only relies on elementary properties of pinching maps and the operator logarithm.
Abstract We generalize our results in paper I in this series to quantum channels between general von Neumann algebras, proving the approximate recoverability of states which undergo a small change in relative entropy through the channel. To this end, we derive a strengthened form of the quantum data processing inequality for the change in relative entropy of two states under a channel between two von Neumann algebras. Compared to the usual inequality, there is an explicit lower bound involving the fidelity between the original state and a recovery channel.