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|Title:||Superior memory efficiency of quantum devices for the simulation of continuous-time stochastic processes||Authors:||Elliott, Thomas Joseph
|Keywords:||Information Theory and Computation
|Issue Date:||2018||Source:||Elliott, T. J., & Gu, M. (2018). Superior memory efficiency of quantum devices for the simulation of continuous-time stochastic processes. npj Quantum Information, 4, 18-.||Series/Report no.:||npj Quantum Information||Abstract:||Continuous-time stochastic processes pervade everyday experience, and the simulation of models of these processes is of great utility. Classical models of systems operating in continuous-time must typically track an unbounded amount of information about past behaviour, even for relatively simple models, enforcing limits on precision due to the finite memory of the machine. However, quantum machines can require less information about the past than even their optimal classical counterparts to simulate the future of discrete-time processes, and we demonstrate that this advantage extends to the continuous-time regime. Moreover, we show that this reduction in the memory requirement can be unboundedly large, allowing for arbitrary precision even with a finite quantum memory. We provide a systematic method for finding superior quantum constructions, and a protocol for analogue simulation of continuous-time renewal processes with a quantum machine.||URI:||https://hdl.handle.net/10356/88439
|DOI:||10.1038/s41534-018-0064-4||Rights:||© 2018 The Author(s) (published by Springer Nature in partnership with the University of New South Wales). This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.||Fulltext Permission:||open||Fulltext Availability:||With Fulltext|
|Appears in Collections:||SPMS Journal Articles|
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