Adaptive Bayesian phase estimation for quantum error correcting codes

Garcia, Fernando Martinez; Vodola, Davide; Muller, Markus

doi:10.1088/1367-2630/ab5c51

Journal article 651 views 130 downloads

Adaptive Bayesian phase estimation for quantum error correcting codes

Fernando Martinez Garcia, Davide Vodola

, Markus Muller

New Journal of Physics, Volume: 21, Issue: 12, Start page: 123027

Swansea University Authors: Fernando Martinez Garcia, Davide Vodola , Markus Muller

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DOI (Published version): 10.1088/1367-2630/ab5c51

Abstract

Realisation of experiments even on small and medium-scale quantum computers requires an optimisation of several parameters to achieve high-fidelity operations. As the size of the quantum register increases, the characterisation of quantum states becomes more difficult since the number of parameters...

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Published in:	New Journal of Physics
ISSN:	1367-2630
Published:	IOP Publishing 2019
Online Access:	Check full text
URI:	https://cronfa.swan.ac.uk/Record/cronfa52967
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first_indexed	2019-12-05T13:16:14Z
last_indexed	2020-12-15T04:15:02Z
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spelling	2020-12-14T16:37:05.4781390 v2 52967 2019-12-05 Adaptive Bayesian phase estimation for quantum error correcting codes 0f796657d158c24445cc6abf0d3582ea Fernando Martinez Garcia Fernando Martinez Garcia true false d00cf42047dd74f072891c2c8f37f32e 0000-0003-0880-3548 Davide Vodola Davide Vodola true false 9b2ac559af27c967ece69db08b83762a Markus Muller Markus Muller true false 2019-12-05 SPH Realisation of experiments even on small and medium-scale quantum computers requires an optimisation of several parameters to achieve high-fidelity operations. As the size of the quantum register increases, the characterisation of quantum states becomes more difficult since the number of parameters to be measured grows as well and finding efficient observables in order to estimate the parameters of the model becomes a crucial task. Here we propose a method relying on application of Bayesian inference that can be used to determine systematic, unknown phase shifts of multi-qubit states. This method offers important advantages as compared to Ramsey-type protocols. First, application of Bayesian inference allows the selection of an adaptive basis for the measurements which yields the optimal amount of information about the phase shifts of the state. Secondly, this method can process the outcomes of different observables at the same time. This leads to a substantial decrease in the resources needed for the estimation of phases, speeding up the state characterisation and optimisation in experimental implementations. The proposed Bayesian inference method can be applied in various physical platforms that are currently used as quantum processors. Journal Article New Journal of Physics 21 12 123027 IOP Publishing 1367-2630 16 12 2019 2019-12-16 10.1088/1367-2630/ab5c51 COLLEGE NANME Physics COLLEGE CODE SPH Swansea University 2020-12-14T16:37:05.4781390 2019-12-05T10:45:51.9968357 Faculty of Science and Engineering School of Biosciences, Geography and Physics - Physics Fernando Martinez Garcia 1 Davide Vodola 0000-0003-0880-3548 2 Markus Muller 3 52967__16126__8ec54f05a4da430b9506bd0d40784756.pdf 52967.pdf 2019-12-17T15:51:13.0542783 Output 1505870 application/pdf Version of Record true Released under the terms of a Creative Commons Attribution 3.0 licence (CC-BY). true eng http://creativecommons.org/licenses/by/3.0/
title	Adaptive Bayesian phase estimation for quantum error correcting codes
spellingShingle	Adaptive Bayesian phase estimation for quantum error correcting codes Fernando Martinez Garcia Davide Vodola Markus Muller
title_short	Adaptive Bayesian phase estimation for quantum error correcting codes
title_full	Adaptive Bayesian phase estimation for quantum error correcting codes
title_fullStr	Adaptive Bayesian phase estimation for quantum error correcting codes
title_full_unstemmed	Adaptive Bayesian phase estimation for quantum error correcting codes
title_sort	Adaptive Bayesian phase estimation for quantum error correcting codes
author_id_str_mv	0f796657d158c24445cc6abf0d3582ea d00cf42047dd74f072891c2c8f37f32e 9b2ac559af27c967ece69db08b83762a
author_id_fullname_str_mv	0f796657d158c24445cc6abf0d3582ea_*_Fernando Martinez Garcia d00cf42047dd74f072891c2c8f37f32e__Davide Vodola 9b2ac559af27c967ece69db08b83762a_**_Markus Muller
author	Fernando Martinez Garcia Davide Vodola Markus Muller
author2	Fernando Martinez Garcia Davide Vodola Markus Muller
format	Journal article
container_title	New Journal of Physics
container_volume	21
container_issue	12
container_start_page	123027
publishDate	2019
institution	Swansea University
issn	1367-2630
doi_str_mv	10.1088/1367-2630/ab5c51
publisher	IOP Publishing
college_str	Faculty of Science and Engineering
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department_str	School of Biosciences, Geography and Physics - Physics{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Biosciences, Geography and Physics - Physics
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description	Realisation of experiments even on small and medium-scale quantum computers requires an optimisation of several parameters to achieve high-fidelity operations. As the size of the quantum register increases, the characterisation of quantum states becomes more difficult since the number of parameters to be measured grows as well and finding efficient observables in order to estimate the parameters of the model becomes a crucial task. Here we propose a method relying on application of Bayesian inference that can be used to determine systematic, unknown phase shifts of multi-qubit states. This method offers important advantages as compared to Ramsey-type protocols. First, application of Bayesian inference allows the selection of an adaptive basis for the measurements which yields the optimal amount of information about the phase shifts of the state. Secondly, this method can process the outcomes of different observables at the same time. This leads to a substantial decrease in the resources needed for the estimation of phases, speeding up the state characterisation and optimisation in experimental implementations. The proposed Bayesian inference method can be applied in various physical platforms that are currently used as quantum processors.
published_date	2019-12-16T04:05:40Z
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Adaptive Bayesian phase estimation for quantum error correcting codes

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