Abstract
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.
- Received 15 March 2019
- Revised 18 September 2019
DOI:https://doi.org/10.1103/PhysRevX.9.041013
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.
Published by the American Physical Society
Physics Subject Headings (PhySH)
Synopsis
Quantum Simulator Reduces Memory Storage
Published 17 October 2019
A photonic quantum simulator records three possible states in a single qubit, demonstrating a clear memory advantage over classical devices.
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Popular Summary
We experimentally demonstrate a way of simulating time-series data (a so-called stochastic process) using quantum physics to reduce the size of the required computer memory. Our fundamental result demonstrates a reduction in the size (or dimensionality) of the memory system beyond classical limits.
Simulating the behavior of stochastic processes, such as weather patterns and traffic congestion, is a crucial tool in science and technology. These stochastic simulators work by dividing time into discrete steps and projecting what will happen in the future, based on the information available from past steps. Quantum information processors offer the power to store past information in memory states that are not completely distinguishable from one another while still being able to achieve accurate simulation results. Surprisingly, the fact that the states cannot be fully distinguished makes things better, not worse: A quantum simulator needs a smaller memory than its best classical counterpart.
Our quantum simulator uses photons—single particles of light—as its memory. In this experiment, we send this photon memory into a processor especially designed to manipulate the photon’s quantum state. Then, we perform a series of measurements to retrieve the simulation result. While our experiment is based on an example that allows us to run a three-state classical processor inside a single two-level quantum system, it is theoretically known that the improvement can be extended to large-scale problems and to a variety of stochastic processes.
The ease and efficiency of using these new quantum simulators opens the path to more complicated simulators with smaller memory storage requirements.