Variational consistent histories as a hybrid algorithm for quantum foundations

Abstract

Although quantum computers are predicted to have many commercial applications, less attention has been given to their potential for resolving foundational issues in quantum mechanics. Here we focus on quantum computers’ utility for the Consistent Histories formalism, which has previously been employed to study quantum cosmology, quantum paradoxes, and the quantum-to-classical transition. We present a variational hybrid quantum-classical algorithm for finding consistent histories, which should revitalize interest in this formalism by allowing classically impossible calculations to be performed. In our algorithm, the quantum computer evaluates the decoherence functional (with exponential speedup in both the number of qubits and the number of times in the history) and a classical optimizer adjusts the history parameters to improve consistency. We implement our algorithm on a cloud quantum computer to find consistent histories for a spin in a magnetic field and on a simulator to observe the emergence of classicality for a chiral molecule.

Abstract

The Consistent Histories formalism can solve paradoxes in quantum mechanics, but finding such consistent sets of histories requires a computational overhead which is exponential in the problem’s size. Here, the authors report a variational hybrid algorithm solving this problem using polynomial resources.

Contributors

Patrick J. Coles: [e-mail]

Journal

Journal ID (nlm-ta): Nat Commun

Journal ID (iso-abbrev): Nat Commun

Title: Nature Communications

Publisher: Nature Publishing Group UK (London )

ISSN (Electronic): 2041-1723

Publication date (Electronic): 31 July 2019

Publication date PMC-release: 31 July 2019

Publication date Collection: 2019

Volume: 10

Affiliations

[1 ]ISNI 0000 0004 0428 3079, GRID grid.148313.c, Theoretical Division, MS 213, Los Alamos National Laboratory, ; Los Alamos, NM 87545 USA

[2 ]ISNI 0000 0004 1936 9684, GRID grid.27860.3b, Department of Physics, University of California Davis, ; Davis, CA 95616 USA

[3 ]ISNI 0000 0004 0428 3079, GRID grid.148313.c, Information Sciences, MS 256, Los Alamos National Laboratory, ; Los Alamos, NM 87545 USA

Article

Publisher ID: 11417

DOI: 10.1038/s41467-019-11417-0

PMC ID: 6668436

Copyright statement: © The Author(s) 2019

License:

Open Access 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/.

Funding

Funded by: FundRef https://doi.org/10.13039/100009566, Foundational Questions Institute (FQXi);

Award ID: FQXi-1821

Award Recipient : Patrick J. Coles

Funded by: FundRef https://doi.org/10.13039/100008902, DOE | LDRD | Los Alamos National Laboratory (Los Alamos Lab);

Categories

Subject: Article

Custom metadata

issue-copyright-statement © The Author(s) 2019