Dimensional Quantum Memory Advantage in the Simulation of Stochastic Processes

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Author(s)
Ghafari, Farzad
Tischler, Nora
Thompson, Jayne
Gu, Mile
Shalm, Lynden K
Verma, Varun B
Nam, Sae Woo
Patel, Raj B
Wiseman, Howard M
Pryde, Geoff J
Griffith University Author(s)
Year published
2019
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Show full item recordAbstract
Stochastic processes underlie a vast range of natural and social phenomena. Some processes such as atomic decay feature intrinsic randomness, whereas other complex processes, e.g., traffic congestion, are effectively probabilistic because we cannot track all relevant variables. To simulate a stochastic system's future behavior, information about its past must be stored, and thus memory is a key resource. Quantum information processing promises a memory advantage for stochastic simulation. Here, we report the first experimental demonstration that a quantum stochastic simulator can encode the required information in fewer ...
View more >Stochastic processes underlie a vast range of natural and social phenomena. Some processes such as atomic decay feature intrinsic randomness, whereas other complex processes, e.g., traffic congestion, are effectively probabilistic because we cannot track all relevant variables. To simulate a stochastic system's future behavior, information about its past must be stored, and thus memory is a key resource. Quantum information processing promises a memory advantage for stochastic simulation. Here, we report the first experimental demonstration that a quantum stochastic simulator can encode the required information in fewer dimensions than any classical simulator, thereby achieving a quantum advantage in minimal memory requirements using an individual simulator. This advantage is in contrast to recent proof-of-concept experiments, where the memory saving would only become accessible in the limit of a large number of parallel simulations. In those examples, the minimal memory registers of individual quantum simulators had the same dimensionality as their classical counterparts. Our photonic experiment thus establishes the potential of new, practical resource savings in the simulation of complex systems.
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View more >Stochastic processes underlie a vast range of natural and social phenomena. Some processes such as atomic decay feature intrinsic randomness, whereas other complex processes, e.g., traffic congestion, are effectively probabilistic because we cannot track all relevant variables. To simulate a stochastic system's future behavior, information about its past must be stored, and thus memory is a key resource. Quantum information processing promises a memory advantage for stochastic simulation. Here, we report the first experimental demonstration that a quantum stochastic simulator can encode the required information in fewer dimensions than any classical simulator, thereby achieving a quantum advantage in minimal memory requirements using an individual simulator. This advantage is in contrast to recent proof-of-concept experiments, where the memory saving would only become accessible in the limit of a large number of parallel simulations. In those examples, the minimal memory registers of individual quantum simulators had the same dimensionality as their classical counterparts. Our photonic experiment thus establishes the potential of new, practical resource savings in the simulation of complex systems.
View less >
Journal Title
Physical Review X
Volume
9
Issue
4
Copyright Statement
© The Author(s) 2019. Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article’s title, journal citation, and DOI.
Subject
Astronomical sciences
Space sciences
Condensed matter physics
Quantum physics
Science & Technology
Physical Sciences
Physics, Multidisciplinary
COMPUTATIONAL MECHANICS