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Validating quantum-classical programming models with tensor network simulations

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dc.contributor.authorMcCaskey, Alexanderen
dc.contributor.authorDumitrescu, Eugeneen
dc.contributor.authorChen, Mengsuen
dc.contributor.authorLyakh, Dmitryen
dc.contributor.authorHumble, Travisen
dc.contributor.departmentPhysicsen
dc.date.accessioned2019-05-31T14:08:24Zen
dc.date.available2019-05-31T14:08:24Zen
dc.date.issued2018-12-10en
dc.description.abstractThe exploration of hybrid quantum-classical algorithms and programming models on noisy near-term quantum hardware has begun. As hybrid programs scale towards classical intractability, validation and benchmarking are critical to understanding the utility of the hybrid computational model. In this paper, we demonstrate a newly developed quantum circuit simulator based on tensor network theory that enables intermediate-scale verification and validation of hybrid quantum-classical computing frameworks and programming models. We present our tensor-network quantum virtual machine (TNQVM) simulator which stores a multi-qubit wavefunction in a compressed (factorized) form as a matrix product state, thus enabling single-node simulations of larger qubit registers, as compared to brute-force state-vector simulators. Our simulator is designed to be extensible in both the tensor network form and the classical hardware used to run the simulation (multicore, GPU, distributed). The extensibility of the TNQVM simulator with respect to the simulation hardware type is achieved via a pluggable interface for different numerical backends (e.g., ITensor and Exa-TENSOR numerical libraries). We demonstrate the utility of our TNQVM quantum circuit simulator through the verification of randomized quantum circuits and the variational quantum eigensolver algorithm, both expressed within the eXtreme-scale ACCelerator (XACC) programming model.en
dc.description.notesThis work was supported by U.S. Department of Energy ASCR Quantum Algorithms Team (ERKJ332, Mr. Alexander McCaskey), U.S. Department of Energy ASCR Quantum Testbed Pathfinder (ERKJ335, Mr. Alexander McCaskey), Laboratory Directed Research and Development Program of Oak Ridge National Laboratory (ID 8297, Mr. Alexander McCaskey), and U.S. Department of Energy Early Career Award (Dr. Travis Humble). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.; This manuscript has been authored by UT-Battelle, LLC, under Contract No. DE-AC0500OR22725 with the U.S. Department of Energy. The United States Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a non-exclusive, paid-up, irrevocable, world-wide license to publish or reproduce the published form of this manuscript, or allow others to do so, for the United States Government purposes. The Department of Energy will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan. This work has been supported by the Laboratory Directed Research and Development Program of Oak Ridge National Laboratory, the US Department of Energy (DOE) Office of Science Advanced Scientific Computing Research (ASCR) Early Career Research Award, and the DOE Office of Science ASCR quantum algorithms and testbed programs, under field work proposal numbers ERKJ332 and ERKJ335. This work was also supported by the ORNL Undergraduate Research Participation Program, which is sponsored by ORNL and administered jointly by ORNL and the Oak Ridge Institute for Science and Education (ORISE). ORNL is managed by UT-Battelle, LLC, for the US Department of Energy under contract no. DE-AC05-00OR22725. ORISE is managed by Oak Ridge Associated Universities for the US Department of Energy under contract no. DE-AC05-00OR22750.en
dc.description.sponsorshipU.S. Department of Energy ASCR Quantum Algorithms Team [ERKJ332]; U.S. Department of Energy ASCR Quantum Testbed Pathfinder [ERKJ335]; Laboratory Directed Research and Development Program of Oak Ridge National Laboratory [8297]; U.S. Department of Energy Early Career Award; U.S. Department of Energy [DE-AC0500OR22725, DE-AC05-00OR22725, DE-AC05-00OR22750]; Laboratory Directed Research and Development Program of Oak Ridge National Laboratory; US Department of Energy (DOE) Office of Science Advanced Scientific Computing Research (ASCR) Early Career Research Award; DOE Office of Science ASCR quantum algorithms and testbed programs [ERKJ332, ERKJ335]; ORNL Undergraduate Research Participation Program - ORNLen
dc.format.mimetypeapplication/pdfen
dc.identifier.doihttps://doi.org/10.1371/journal.pone.0206704en
dc.identifier.eissn1932-6203en
dc.identifier.issue12en
dc.identifier.othere0206704en
dc.identifier.pmid30532151en
dc.identifier.urihttp://hdl.handle.net/10919/89656en
dc.identifier.volume13en
dc.language.isoenen
dc.publisherPLOSen
dc.rightsCreative Commons Attribution 4.0 Internationalen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en
dc.titleValidating quantum-classical programming models with tensor network simulationsen
dc.title.serialPLOS ONEen
dc.typeArticle - Refereeden
dc.type.dcmitypeTexten
dc.type.dcmitypeStillImageen

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