Belief Propagation algorithms acting on Graphical Models of classical probability distributions, such as Markov Networks, Factor Graphs and Bayesian Networks, are amongst the most powerful known methods for deriving probabilistic inferences amongst large numbers of random variables. This paper presents a generalization of these concepts and methods to the quantum case, based on the idea that quantum theory can be thought of as a noncommutative, operator-valued, generalization of classical probability theory. Some novel characterizations of quantum conditional independence are derived, and definitions of Quantum n-Bifactor Networks, Markov Networks, Factor Graphs and Bayesian Networks are proposed. The structure of Quantum Markov Networks is investigated and some partial characterization results are obtained, along the lines of the Hammersely-Clifford theorem. A Quantum Belief Propagation algorithm is presented and is shown to converge on 1-Bifactor Networks and Markov Networks when the underlying graph is a tree. The use of Quantum Belief Propagation as a heuristic algorithm in cases where it is not known to converge is discussed. Applications to decoding quantum error correcting codes and to the simulation of many-body quantum systems are described.
There has also been work on Quantum Markov networks within the quantum probability literature @cite_35 @cite_5 @cite_52 , although Belief Propagation has not been investigated in this literature. This is closer to the spirit of the present work, in the sense that it is based on the generalization of classical probability to a noncommutative, operator-valued probability theory. These works are primarily concerned with defining the Markov condition in such a way that it can be applied to systems with an infinite number of degrees of freedom, and hence an operator algebraic formalism is used. This is important for applications to statistical physics because the thermodynamic limit can be formally defined as the limit of an infinite number of systems, but it is not so important for numerical simulations, since these necessarily operate with a finite number of discretized degrees of freedom. Also conditional independence is defined in a different way via quantum conditional expectations, rather than the approach based on conditional mutual information and conditional density operators used in the present work. Nevertheless, it seems likely that there are connections to our approach that should to be investigated in future work.
@cite_35 @cite_5 @cite_52
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We study a model of communication complexity that encompasses many well-studied problems, including classical and quantum communication complexity, the complexity of simulating distributions arising from bipartite measurements of shared quantum states, and XOR games. In this model, Alice gets an input x, Bob gets an input y, and their goal is to each produce an output a, b distributed according to some pre-specified joint distribution p(a, b|x, y). Our results apply to any non-signaling distribution, that is, those where Alice's marginal distribution does not depend on Bob's input, and vice versa. By taking a geometric view of the non-signaling distributions, we introduce a simple new technique based on affine combinations of lower-complexity distributions, and we give the first general technique to apply to all these settings, with elementary proofs and very intuitive interpretations. Specifically, we introduce two complexity measures, one which gives lower bounds on classical communication, and one for quantum communication. These measures can be expressed as convex optimization problems. We show that the dual formulations have a striking interpretation, since they coincide with maximum violations of Bell and Tsirelson inequalities. The dual expressions are closely related to the winning probability of XOR games. Despite their apparent simplicity, these lower bounds subsume many known communication complexity lower bound methods, most notably the recent lower bounds of Linial and Shraibman for the special case of Boolean functions. We show that as in the case of Boolean functions, the gap between the quantum and classical lower bounds is at most linear in the size of the support of the distribution, and does not depend on the size of the inputs. This translates into a bound on the gap between maximal Bell and Tsirelson inequality violations, which was previously known only for the case of distributions with Boolean outcomes and uniform marginals. It also allows us to show that for some distributions, information theoretic methods are necessary to prove strong lower bounds. Finally, we give an exponential upper bound on quantum and classical communication complexity in the simultaneous messages model, for any non-signaling distribution. One consequence of this is a simple proof that any quantum distribution can be approximated with a constant number of bits of communication. AbstractIn this paper we propose a continuous-time, dissipative Markov dynamics that asymp-totically drives a network of n-dimensional quantum systems to the set of states that areinvariant under the action of the subsystem permutation group. The Lindblad-type gen-erator of the dynamics is built with two-body subsystem swap operators, thus satisfyinglocality constraints, and preserve symmetric observables. The potential use of the pro-posed generator in combination with local control and measurement actions is illustratedwith two applications: the generation of a global pure state and the estimation of thenetwork size. 1 INTRODUCTION Classical consensus algorithms and the related distributed control problems have recentlygenerated an impressive body of literature, motivated by applications in distributed com-putation and multi-agent coordination, see e.g. [1, 2, 3, 4, 5, 6, 7, 8, 9]. We have recentlyrecast the problem, and a class of algorithms for its solution, as a dynamical symmetriza-tion problem in a group-theoretic framework [10]. This allows to extend the use of simpleand robust algorithms, e.g. of gossip type [11], to new settings and applications. Amongthese, we have studied a quantum version of consensus problems and its applications [12],which can be seen as symmetrization with respect to the subsystem-permutation group, aswell as control methods like quantum dynamical decoupling [13], in which we generally donot have a multipartite structure and symmetrization is attained with respect to other ﬁnitegroups. The emerging dynamics are intrinsically in discrete time, and suitable for sequentialimplementation in dissipative quantum simulators [14]. We give an explicit characterisation of the quantum states which saturate the strong subadditivity inequality for the von Neumann entropy. By combining a result of Petz characterising the equality case for the monotonicity of relative entropy with a recent theorem by Koashi and Imoto, we show that such states will have the form of a so–called short quantum Markov chain, which in turn implies that two of the systems are independent conditioned on the third, in a physically meaningful sense. This characterisation simultaneously generalises known necessary and sufficient entropic conditions for quantum error correction as well as the conditions for the achievability of the Holevo bound on accessible information. We study the problem of k-pair communication (or multiple unicast problem) of quantum information in networks of quantum channels. We consider the asymptotic rates of high fidelity quantum communication between specific sender-receiver pairs. Four scenarios of classical communication assistance (none, forward, backward, and two-way) are considered. (I) We obtain outer and inner bounds of the achievable rate regions in the most general directed networks. (II) For two particular networks (including the butterfly network), routing is proved optimal, and the free assisting classical communication can at best be used to modify the directions of quantum channels in the network. Consequently, the achievable rate regions are given by counting edge avoiding paths, and precise achievable rate regions in all four assisting scenarios can be obtained. (III) Optimality of routing can also be proved in classes of networks. The first class consists of directed unassisted networks in which (1) the receivers are information sinks, (2) the maximum distance from senders to receivers is small, and (3) a certain type of 4-cycles are absent, but without further constraints (such as on the number of communicating and intermediate parties). The second class consists of arbitrary backward-assisted networks with two sender-receiver pairs. (IV) Beyond the k-pair communication problem, observations are made on quantum multicasting and a static version of network communication related to the entanglement of assistance.