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|Title:||Provably unbounded memory advantage in stochastic simulation using quantum mechanics||Authors:||Garner, Andrew J. P.
|Issue Date:||2017||Source:||Garner, A. J. P., Liu, Q., Thompson, J., Vedral, V., & Gu, M. (2017). Provably unbounded memory advantage in stochastic simulation using quantum mechanics. New Journal of Physics, 19(10), 103009-.||Series/Report no.:||New Journal of Physics||Abstract:||Simulating the stochastic evolution of real quantities on a digital computer requires a trade-off between the precision to which these quantities are approximated, and the memory required to store them. The statistical accuracy of the simulation is thus generally limited by the internal memory available to the simulator. Here, using tools from computational mechanics, we show that quantum processors with a fixed finite memory can simulate stochastic processes of real variables to arbitrarily high precision. This demonstrates a provable, unbounded memory advantage that a quantum simulator can exhibit over its best possible classical counterpart.||URI:||https://hdl.handle.net/10356/87218
|DOI:||http://dx.doi.org/10.1088/1367-2630/aa82df||Rights:||© 2017 IOP Publishing Ltd 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.||Fulltext Permission:||open||Fulltext Availability:||With Fulltext|
|Appears in Collections:||SPMS Journal Articles|
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