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IEEE International Symposium on Information Theory (ISIT)

Tight Analysis of Convex Splitting with Applications in Quantum Information Theory

Hao–Chung Cheng, Li Gao

Published Jun 25, 2023• 6 citations
Publisher

Abstract

Convex splitting is a powerful technique in quantum information theory that applies to proving the achievability of numerous information-processing protocols. In this paper, we establish a one-shot error exponent and a one-shot strong converse for convex splitting with trace distance as the error criterion. Our result exhibits the following features. Firstly, the derived error exponent is given in terms of a generalized sandwiched Rényi mutual information which is additive for product states. Hence, our bound directly applies to the n-fold product scenario for any blocklength. Secondly, the one-shot error bound is meaningful in the sense that the error exponent is all positive on the achievable rate region. This leads to new one-shot exponent results in various tasks in quantum information theory. Conversely, we prove a one-shot strong converse to demonstrate that the convex splitting error converges to one exponentially fast at rates outside the achievable rate region. We also establish an optimal one-shot characterization of the sample complexity for convex splitting, which yields matched second-order asymptotics, showing the tightness of our result. This then leads to a stronger one-shot analysis in quantum information theory.Our technique is to introduce a unified functional analytic approach using Kosaki’s noncommutative weighted Lpnorm. Our results then follow from tight analysis based on such a norm framework.The full version of the manuscript can be found at [arXiv:2304.12055] [1].

DOI
10.1109/isit54713.2023.10206913

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Convex splitting is a powerful technique in quantum information theory that applies to proving the achievability of numerous information-processing protocols. In this paper, we establish a one-shot error exponent and a one-shot strong converse for convex splitting with trace distance as the error criterion. Our result exhibits the following features. Firstly, the derived error exponent is given in terms of a generalized sandwiched Rényi mutual information which is additive for product states. Hence, our bound directly applies to the n-fold product scenario for any blocklength. Secondly, the one-shot error bound is meaningful in the sense that the error exponent is all positive on the achievable rate region. This leads to new one-shot exponent results in various tasks in quantum information theory. Conversely, we prove a one-shot strong converse to demonstrate that the convex splitting error converges to one exponentially fast at rates outside the achievable rate region. We also establish an optimal one-shot characterization of the sample complexity for convex splitting, which yields matched second-order asymptotics, showing the tightness of our result. This then leads to a stronger one-shot analysis in quantum information theory.Our technique is to introduce a unified functional analytic approach using Kosaki’s noncommutative weighted Lpnorm. Our results then follow from tight analysis based on such a norm framework.The full version of the manuscript can be found at [arXiv:2304.12055] [1].
Quantum information decoupling is a fundamental primitive in quantum information theory, underlying various applications in quantum physics. We prove a novel one-shot decoupling theorem formulated in terms of quantum relative entropy distance, with the decoupling error bounded by two sandwiched Rényi conditional entropies. In the asymptotic i.i.d. setting of standard information decoupling via partial trace, we show that this bound is ensemble-tight in quantum relative entropy distance and thereby yields a characterization of the associated decoupling error exponent in the low-cost-rate regime. Leveraging this framework, we derive several operational applications formulated in terms of purified distance: (i) single-letter expressions for the exact error exponents of quantum state merging in the low-entanglement-cost and high-entanglement-distillation-rate regimes, in terms of Petz-Rényi conditional entropies, and (ii) regularized expressions for achievable error exponents of entanglement distillation and quantum channel coding in terms of Petz-Rényi coherent informations. We further prove that these achievable bounds are tight for maximally correlated states and generalized dephasing channels, respectively, for the high distillation-rate/coding-rate regimes.
Convex splitting is a powerful technique in quantum information theory used in proving the achievability of various information-processing protocols such as quantum state redistribution and quantum network channel coding. In this work, we establish a one-shot error exponent and a one-shot exponential strong converse for convex splitting with trace distance as an error criterion. Our error exponent (resp. strong converse exponent) is positive if and only if the rate is in (resp. outside) the achievable region. This leads to new one-shot exponent results in various tasks such as communication over quantum wiretap channels, secret key distillation, one-way quantum message compression, quantum measurement simulation, and quantum channel coding with side information at the transmitter. We also establish a near-optimal one-shot characterization of the sample complexity for convex splitting, which yields matched second-order asymptotics. This then leads to stronger one-shot analysis in many quantum information-theoretic tasks.
We introduce an improved one-shot characterisation of randomness extraction against quantum side information (privacy amplification), strengthening known one-shot bounds and providing a unified derivation of the tightest known asymptotic constraints. Our main tool is a new class of smooth conditional entropies defined by lifting classical smooth divergences through measurements. A key role is played by the measured smooth Rényi relative entropy of order 2, which we show to admit an equivalent variational form: it can be understood as allowing for smoothing over not only states, but also non-positive Hermitian operators. Building on this, we establish a tightened leftover hash lemma, significantly improving over all known smooth min-entropy bounds on extractable randomness and recovering the sharpest classical achievability results. We extend these methods to decoupling, the coherent analogue of privacy amplification, obtaining a corresponding improved one-shot bound. Relaxing our smooth entropy bounds leads to one-shot achievability results in terms of measured Rényi divergences, tightening the bounds of [Dupuis, arXiv:2105.05342] and recovering state-of-the-art asymptotic i.i.d. error exponents. We show an approximate optimality of our results by giving a matching one-shot converse bound up to additive logarithmic terms. This yields an optimal second-order asymptotic expansion of privacy amplification under trace distance, establishing a significantly tighter one-shot achievability result than previously shown in [Shen et al., arXiv:2202.11590] and proving its optimality for all hash functions.
How well can we approximate a quantum channel output state using a random codebook with a certain size? In this work, we study the quantum soft covering problem, which uses a pairwise-independent random codebook to approximate the target output state of a quantum channel. We establish a one-shot error exponent bound and a one-shot strong converse bound on the approximation error measured in terms of the expected trace distance between the codebook-induced state and the true channel output state. When using independent and identically-distributed random codebook with a rate above the quantum mutual informationI(X : B)ρ, we prove that the error decays exponentially with its error exponent expressed by the sandwiched Rényi information. On the other hand, when the rate of the codebook size is below the quantum mutual information, the error converges to one exponentially fast. Similar results are obtained using a random constant composition codebook, whereas the sandwiched Augustin information gives the error exponent. In addition to the above large deviation analysis, our results also hold in the moderate deviation regime.
Single-shot quantum information theory is governed not only by entropy exponents, but also by the finite-resource constants that multiply them. These constants directly affect the quantitative performance of decoupling, covering, convex-splitting, position-based decoding, and one-shot communication protocols, yet they are often inherited from nonoptimal scalar estimates or from classical-to-quantum lifting arguments that introduce additional losses. In this work we show that the operator layer-cake representation provides a mechanism for lifting sharp scalar inequalities to the noncommutative setting without loss. Using an iterative Riemann--Stieltjes integration-by-parts method, we derive sharp quantum trace inequalities that tighten several standard single-shot bounds. For a logarithmic trace inequality recently introduced by Cheng \emph{et al.}\ and subsequently used in quantum covering and decoupling problems, we determine the exact optimal prefactor, replacing the previously known constant by a smaller Lambert-WWW constant and proving universal optimality for positive operators. We also completely characterize the threshold behavior that appears under normalization to quantum states. In addition, we establish optimal two-sided collision-divergence inequalities, which lead to improved position-based decoding and single-shot classical communication bounds. These results show that several finite-resource bounds in single-shot quantum information can be tightened, and that within the layer-cake Rényi-divergence framework the resulting constants are genuine optimality barriers rather than artifacts of the proof.
We show that the communication cost of quantum broadcast channel simulation under free entanglement assistance between the sender and the receivers is asymptotically characterized by an efficiently computable single-letter formula in terms of the channel's multipartite mutual information. Our core contribution is a new one-shot achievability result for multipartite quantum state splitting via multipartite convex splitting. As part of this, we face a general instance of the quantum joint typicality problem with arbitrarily overlapping marginals. The crucial technical ingredient to sidestep this difficulty is a conceptually novel multipartite mean-zero decomposition lemma, together with employing recently introduced complex interpolation techniques for sandwiched Rényi divergences. Moreover, we establish an exponential convergence of the simulation error when the communication costs are within the interior of the capacity region. As the costs approach the boundary of the capacity region moderately quickly, we show that the error still vanishes asymptotically.