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Hidden Quantum Markov Models and non-adaptive read-out of many-body states

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arxiv 1002.2337 v2 pith:KGUE3UNF submitted 2010-02-11 quant-ph

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keywords quantumstochasticcompressedgeneratorsstatesdescriptiondescriptionsexample
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Stochastic finite-state generators are compressed descriptions of infinite time series. Alternatively, compressed descriptions are given by quantum finite- state generators [K. Wiesner and J. P. Crutchfield, Physica D 237, 1173 (2008)]. These are based on repeated von Neumann measurements on a quantum dynamical system. Here we generalise the quantum finite-state generators by replacing the von Neumann pro jections by stochastic quantum operations. In this way we assure that any time series with a stochastic compressed description has a compressed quantum description. Moreover, we establish a link between our stochastic generators and the sequential readout of many-body states with translationally-invariant matrix product state representations. As an example, we consider the non-adaptive read-out of 1D cluster states. This is shown to be equivalent to a Hidden Quantum Model with two internal states, providing insight on the inherent complexity of the process. Finally, it is proven by example that the quantum description can have a higher degree of compression than the classical stochastic one.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Quantum Dimension Reduction of Hidden Markov Models

    quant-ph 2026-01 conditional novelty 7.0 of 10

    Any finite ergodic HMM can be made deterministic by labelling transitions, yielding a normal iMPS that can be variationally compressed into a smaller quantum model.

  2. Identifiability and minimality bounds of quantum and post-quantum models of classical stochastic processes

    quant-ph 2025-09 conditional novelty 6.0 of 10

    Quantum hidden Markov models are shown to be identifiable via a finite set of word probabilities, and the minimal quantum memory dimension is proved to be at least the square root of the minimal generalized hidden Mar...

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