Extreme Quantum Advantage when Simulating Classical Systems with Long-Range Interaction
Abstract Classical stochastic processes can be generated by quantum simulators instead of the more standard classical ones, such as hidden Markov models. One reason for using quantum simulators has recently come to the fore: they generally require less memory than their classical counterparts. Here,...
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Nature Portfolio
2017
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oai:doaj.org-article:8a6055075381407dbac3db4100dcc6a42021-12-02T11:52:42ZExtreme Quantum Advantage when Simulating Classical Systems with Long-Range Interaction10.1038/s41598-017-04928-72045-2322https://doaj.org/article/8a6055075381407dbac3db4100dcc6a42017-07-01T00:00:00Zhttps://doi.org/10.1038/s41598-017-04928-7https://doaj.org/toc/2045-2322Abstract Classical stochastic processes can be generated by quantum simulators instead of the more standard classical ones, such as hidden Markov models. One reason for using quantum simulators has recently come to the fore: they generally require less memory than their classical counterparts. Here, we examine this quantum advantage for strongly coupled spin systems—in particular, the Dyson one-dimensional Ising spin chain with variable interaction length. We find that the advantage scales with both interaction range and temperature, growing without bound as interaction range increases. In particular, simulating Dyson’s original spin chain with the most memory-efficient classical algorithm known requires infinite memory, while a quantum simulator requires only finite memory. Thus, quantum systems can very efficiently simulate strongly coupled one-dimensional classical spin systems.Cina AghamohammadiJohn R. MahoneyJames P. CrutchfieldNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 7, Iss 1, Pp 1-11 (2017) |
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Medicine R Science Q Cina Aghamohammadi John R. Mahoney James P. Crutchfield Extreme Quantum Advantage when Simulating Classical Systems with Long-Range Interaction |
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Abstract Classical stochastic processes can be generated by quantum simulators instead of the more standard classical ones, such as hidden Markov models. One reason for using quantum simulators has recently come to the fore: they generally require less memory than their classical counterparts. Here, we examine this quantum advantage for strongly coupled spin systems—in particular, the Dyson one-dimensional Ising spin chain with variable interaction length. We find that the advantage scales with both interaction range and temperature, growing without bound as interaction range increases. In particular, simulating Dyson’s original spin chain with the most memory-efficient classical algorithm known requires infinite memory, while a quantum simulator requires only finite memory. Thus, quantum systems can very efficiently simulate strongly coupled one-dimensional classical spin systems. |
format |
article |
author |
Cina Aghamohammadi John R. Mahoney James P. Crutchfield |
author_facet |
Cina Aghamohammadi John R. Mahoney James P. Crutchfield |
author_sort |
Cina Aghamohammadi |
title |
Extreme Quantum Advantage when Simulating Classical Systems with Long-Range Interaction |
title_short |
Extreme Quantum Advantage when Simulating Classical Systems with Long-Range Interaction |
title_full |
Extreme Quantum Advantage when Simulating Classical Systems with Long-Range Interaction |
title_fullStr |
Extreme Quantum Advantage when Simulating Classical Systems with Long-Range Interaction |
title_full_unstemmed |
Extreme Quantum Advantage when Simulating Classical Systems with Long-Range Interaction |
title_sort |
extreme quantum advantage when simulating classical systems with long-range interaction |
publisher |
Nature Portfolio |
publishDate |
2017 |
url |
https://doaj.org/article/8a6055075381407dbac3db4100dcc6a4 |
work_keys_str_mv |
AT cinaaghamohammadi extremequantumadvantagewhensimulatingclassicalsystemswithlongrangeinteraction AT johnrmahoney extremequantumadvantagewhensimulatingclassicalsystemswithlongrangeinteraction AT jamespcrutchfield extremequantumadvantagewhensimulatingclassicalsystemswithlongrangeinteraction |
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1718394937425264640 |