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Cambridge University Press eBooks

Strong Quantum Markov Processes

Mou-Hsiung Chang

Published Feb 9, 2015• 0 citations
Publisher
DOI
10.1017/cbo9781107706545.010

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Markovianity lies at the heart of communication problems. This in turn makes the information-theoretic characterization of Markov processes worthwhile. Data-processing inequalities are ubiquitous in this sense, assigning necessary conditions for all Markov processes. We address here the problem of the information-theoretic analysis of constraints on Markov processes in the quantum regime. We show the existence of a class of quantum data-processing inequalities called here quantum Markov monogamy inequalities. This class of necessary conditions on quantum Markov processes is inspired by its counterpart for classical Markov processes, thus providing a strong link between classical and quantum constraints on Markovianity. We go on to construct a family of multitime quantum Markov monogamy inequalities, based on the process tensor formalism and that exploits multitime correlations. We then show, by means of an explicit example, that the Markov monogamy inequalities can be stronger than the usual quantum data-processing inequalities.
Among the predictive hidden Markov models that describe a given stochastic process, the ϵ-machine is strongly minimal in that it minimizes every Rényi-based memory measure. Quantum models can be smaller still. In contrast with the ϵ-machine ’s unique role in the classical setting, however, among the class of processes described by pure-state hidden quantum Markov models, there are those for which there does not exist any strongly minimal model. Quantum memory optimization then depends on which memory measure best matches a given problem’s circumstance.