Quantum circuit cutting with maximum-likelihood tomography

Abstract We introduce maximum-likelihood fragment tomography (MLFT) as an improved circuit cutting technique for running clustered quantum circuits on quantum devices with a limited number of qubits. In addition to minimizing the classical computing overhead of circuit cutting methods, MLFT finds th...

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Autores principales:	Michael A. Perlin, Zain H. Saleem, Martin Suchara, James C. Osborn
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Physics QC1-999 Electronic computers. Computer science QA75.5-76.95
Acceso en línea:	https://doaj.org/article/6d690b13e5984bdc98e87c8ee6e893eb
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spelling	oai:doaj.org-article:6d690b13e5984bdc98e87c8ee6e893eb2021-12-02T18:27:57ZQuantum circuit cutting with maximum-likelihood tomography10.1038/s41534-021-00390-62056-6387https://doaj.org/article/6d690b13e5984bdc98e87c8ee6e893eb2021-04-01T00:00:00Zhttps://doi.org/10.1038/s41534-021-00390-6https://doaj.org/toc/2056-6387Abstract We introduce maximum-likelihood fragment tomography (MLFT) as an improved circuit cutting technique for running clustered quantum circuits on quantum devices with a limited number of qubits. In addition to minimizing the classical computing overhead of circuit cutting methods, MLFT finds the most likely probability distribution for the output of a quantum circuit, given the measurement data obtained from the circuit’s fragments. We demonstrate the benefits of MLFT for accurately estimating the output of a fragmented quantum circuit with numerical experiments on random unitary circuits. Finally, we show that circuit cutting can estimate the output of a clustered circuit with higher fidelity than full circuit execution, thereby motivating the use of circuit cutting as a standard tool for running clustered circuits on quantum hardware.Michael A. PerlinZain H. SaleemMartin SucharaJames C. OsbornNature PortfolioarticlePhysicsQC1-999Electronic computers. Computer scienceQA75.5-76.95ENnpj Quantum Information, Vol 7, Iss 1, Pp 1-8 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Physics QC1-999 Electronic computers. Computer science QA75.5-76.95
spellingShingle	Physics QC1-999 Electronic computers. Computer science QA75.5-76.95 Michael A. Perlin Zain H. Saleem Martin Suchara James C. Osborn Quantum circuit cutting with maximum-likelihood tomography
description	Abstract We introduce maximum-likelihood fragment tomography (MLFT) as an improved circuit cutting technique for running clustered quantum circuits on quantum devices with a limited number of qubits. In addition to minimizing the classical computing overhead of circuit cutting methods, MLFT finds the most likely probability distribution for the output of a quantum circuit, given the measurement data obtained from the circuit’s fragments. We demonstrate the benefits of MLFT for accurately estimating the output of a fragmented quantum circuit with numerical experiments on random unitary circuits. Finally, we show that circuit cutting can estimate the output of a clustered circuit with higher fidelity than full circuit execution, thereby motivating the use of circuit cutting as a standard tool for running clustered circuits on quantum hardware.
format	article
author	Michael A. Perlin Zain H. Saleem Martin Suchara James C. Osborn
author_facet	Michael A. Perlin Zain H. Saleem Martin Suchara James C. Osborn
author_sort	Michael A. Perlin
title	Quantum circuit cutting with maximum-likelihood tomography
title_short	Quantum circuit cutting with maximum-likelihood tomography
title_full	Quantum circuit cutting with maximum-likelihood tomography
title_fullStr	Quantum circuit cutting with maximum-likelihood tomography
title_full_unstemmed	Quantum circuit cutting with maximum-likelihood tomography
title_sort	quantum circuit cutting with maximum-likelihood tomography
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/6d690b13e5984bdc98e87c8ee6e893eb
work_keys_str_mv	AT michaelaperlin quantumcircuitcuttingwithmaximumlikelihoodtomography AT zainhsaleem quantumcircuitcuttingwithmaximumlikelihoodtomography AT martinsuchara quantumcircuitcuttingwithmaximumlikelihoodtomography AT jamescosborn quantumcircuitcuttingwithmaximumlikelihoodtomography
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Quantum circuit cutting with maximum-likelihood tomography

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