Memory-efficient tracking of complex temporal and symbolic dynamics with quantum simulators

Tracking the behaviour of stochastic systems is a crucial task in the statistical sciences. It has recently been shown that quantum models can faithfully simulate such processes whilst retaining less information about the past behaviour of the system than the optimal classical models. We extend thes...

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Main Authors: Elliot, Thomas Joseph, Garner, Andrew J. P., Gu, Mile
Other Authors: School of Physical and Mathematical Sciences
Format: Article
Language:English
Published: 2019
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Online Access:https://hdl.handle.net/10356/102677
http://hdl.handle.net/10220/48066
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1026772023-02-28T19:43:02Z Memory-efficient tracking of complex temporal and symbolic dynamics with quantum simulators Elliot, Thomas Joseph Garner, Andrew J. P. Gu, Mile School of Physical and Mathematical Sciences Complexity Institute Quantum Simulators DRNTU::Science::Physics Complex Processes Tracking the behaviour of stochastic systems is a crucial task in the statistical sciences. It has recently been shown that quantum models can faithfully simulate such processes whilst retaining less information about the past behaviour of the system than the optimal classical models. We extend these results to general temporal and symbolic dynamics. Our systematic protocol for quantum model construction relies only on an elementary description of the dynamics of the process. This circumvents restrictions on corresponding classical construction protocols, and allows for a broader range of processes to be modelled efficiently. We illustrate our method with an example exhibiting an apparent unbounded memory advantage of the quantum model compared to its optimal classical counterpart. Published version 2019-04-25T02:58:37Z 2019-12-06T20:58:54Z 2019-04-25T02:58:37Z 2019-12-06T20:58:54Z 2019 2019 Journal Article Elliott, T. J., Garner, A. J. P., & Gu, M. (2019). Memory-efficient tracking of complex temporal and symbolic dynamics with quantum simulators. New Journal of Physics, 21(1), 013021-32. doi:10.1088/1367-2630/aaf824 1367-2630 https://hdl.handle.net/10356/102677 http://hdl.handle.net/10220/48066 10.1088/1367-2630/aaf824 209768 en New Journal of Physics © 2019 The Author(s). Published by IOP Publishing Ltd on behalf of the Institute of Physics and Deutsche Physikalische Gesellschaft. Original content from this work may be used under the terms of the Creative Commons Attribution 3.0 licence. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI. 12 p. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Quantum Simulators
DRNTU::Science::Physics
Complex Processes
spellingShingle Quantum Simulators
DRNTU::Science::Physics
Complex Processes
Elliot, Thomas Joseph
Garner, Andrew J. P.
Gu, Mile
Memory-efficient tracking of complex temporal and symbolic dynamics with quantum simulators
description Tracking the behaviour of stochastic systems is a crucial task in the statistical sciences. It has recently been shown that quantum models can faithfully simulate such processes whilst retaining less information about the past behaviour of the system than the optimal classical models. We extend these results to general temporal and symbolic dynamics. Our systematic protocol for quantum model construction relies only on an elementary description of the dynamics of the process. This circumvents restrictions on corresponding classical construction protocols, and allows for a broader range of processes to be modelled efficiently. We illustrate our method with an example exhibiting an apparent unbounded memory advantage of the quantum model compared to its optimal classical counterpart.
author2 School of Physical and Mathematical Sciences
author_facet School of Physical and Mathematical Sciences
Elliot, Thomas Joseph
Garner, Andrew J. P.
Gu, Mile
format Article
author Elliot, Thomas Joseph
Garner, Andrew J. P.
Gu, Mile
author_sort Elliot, Thomas Joseph
title Memory-efficient tracking of complex temporal and symbolic dynamics with quantum simulators
title_short Memory-efficient tracking of complex temporal and symbolic dynamics with quantum simulators
title_full Memory-efficient tracking of complex temporal and symbolic dynamics with quantum simulators
title_fullStr Memory-efficient tracking of complex temporal and symbolic dynamics with quantum simulators
title_full_unstemmed Memory-efficient tracking of complex temporal and symbolic dynamics with quantum simulators
title_sort memory-efficient tracking of complex temporal and symbolic dynamics with quantum simulators
publishDate 2019
url https://hdl.handle.net/10356/102677
http://hdl.handle.net/10220/48066
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