Variational quantum algorithm for low-dimensional systems in the Pauli basis

In the last decade, variational quantum algorithms implemented on modern quantum computers have successfully solved practical problems of optimization, quantum chemistry, and machine learning. We propose new variational quantum algorithm based on a Monte Carlo scheme that uses a random selection of...

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Main Authors: D.O. Golov, N.A. Petrov, A.N. Tsirulev
Format: Article
Language:Russian
Published: Tver State University 2024-12-01
Series:Физико-химические аспекты изучения кластеров, наноструктур и наноматериалов
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Online Access:https://physchemaspects.ru/2024/doi-10-26456-pcascnn-2024-16-343/?lang=en
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author D.O. Golov
N.A. Petrov
A.N. Tsirulev
author_facet D.O. Golov
N.A. Petrov
A.N. Tsirulev
author_sort D.O. Golov
collection DOAJ
description In the last decade, variational quantum algorithms implemented on modern quantum computers have successfully solved practical problems of optimization, quantum chemistry, and machine learning. We propose new variational quantum algorithm based on a Monte Carlo scheme that uses a random selection of the generators for a unitary transformation, and also uses optimization of the objective functional employing the annealing or Metropolis-Hastings algorithm. The states of the quantum system in the form of a density operator and its model Hamiltonian are represented by expansions in the Pauli basis. In the algorithm, the state of the system is changed by means of a random choice of the Pauli generator that determines the unitary transformation of the state. The efficiency of the annealing algorithm directly depends on the equiprobable choice of the transition from one state to the second, so the work uses a compromise version of the uniform distribution of operators on the SU(2n) group – the direct product of the SU(2) group, where n is the number of qubits in the system. The random choice of a single-qubit operator (consistent with the Haar measure on SU(2)) is implemented in Hopf coordinates on the group manifold (the three-sphere). The results of testing the algorithm show that it can be effective for low-dimensional systems.
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institution Kabale University
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2658-4360
language Russian
publishDate 2024-12-01
publisher Tver State University
record_format Article
series Физико-химические аспекты изучения кластеров, наноструктур и наноматериалов
spelling doaj-art-b1cb34f8a7a6481d935f5d397962bb492024-12-26T13:58:00ZrusTver State UniversityФизико-химические аспекты изучения кластеров, наноструктур и наноматериалов2226-44422658-43602024-12-011634335010.26456/pcascnn/2024.16.343Variational quantum algorithm for low-dimensional systems in the Pauli basisD.O. Golov0N.A. Petrov1A.N. Tsirulev2Tver State UniversityTver State UniversityTver State UniversityIn the last decade, variational quantum algorithms implemented on modern quantum computers have successfully solved practical problems of optimization, quantum chemistry, and machine learning. We propose new variational quantum algorithm based on a Monte Carlo scheme that uses a random selection of the generators for a unitary transformation, and also uses optimization of the objective functional employing the annealing or Metropolis-Hastings algorithm. The states of the quantum system in the form of a density operator and its model Hamiltonian are represented by expansions in the Pauli basis. In the algorithm, the state of the system is changed by means of a random choice of the Pauli generator that determines the unitary transformation of the state. The efficiency of the annealing algorithm directly depends on the equiprobable choice of the transition from one state to the second, so the work uses a compromise version of the uniform distribution of operators on the SU(2n) group – the direct product of the SU(2) group, where n is the number of qubits in the system. The random choice of a single-qubit operator (consistent with the Haar measure on SU(2)) is implemented in Hopf coordinates on the group manifold (the three-sphere). The results of testing the algorithm show that it can be effective for low-dimensional systems. https://physchemaspects.ru/2024/doi-10-26456-pcascnn-2024-16-343/?lang=envariational quantum algorithmannealing algorithmunitary transformationpauli basishamiltonian expansionuniform distribution of a random variable on a three-dimensional spherehopf coordinates
spellingShingle D.O. Golov
N.A. Petrov
A.N. Tsirulev
Variational quantum algorithm for low-dimensional systems in the Pauli basis
Физико-химические аспекты изучения кластеров, наноструктур и наноматериалов
variational quantum algorithm
annealing algorithm
unitary transformation
pauli basis
hamiltonian expansion
uniform distribution of a random variable on a three-dimensional sphere
hopf coordinates
title Variational quantum algorithm for low-dimensional systems in the Pauli basis
title_full Variational quantum algorithm for low-dimensional systems in the Pauli basis
title_fullStr Variational quantum algorithm for low-dimensional systems in the Pauli basis
title_full_unstemmed Variational quantum algorithm for low-dimensional systems in the Pauli basis
title_short Variational quantum algorithm for low-dimensional systems in the Pauli basis
title_sort variational quantum algorithm for low dimensional systems in the pauli basis
topic variational quantum algorithm
annealing algorithm
unitary transformation
pauli basis
hamiltonian expansion
uniform distribution of a random variable on a three-dimensional sphere
hopf coordinates
url https://physchemaspects.ru/2024/doi-10-26456-pcascnn-2024-16-343/?lang=en
work_keys_str_mv AT dogolov variationalquantumalgorithmforlowdimensionalsystemsinthepaulibasis
AT napetrov variationalquantumalgorithmforlowdimensionalsystemsinthepaulibasis
AT antsirulev variationalquantumalgorithmforlowdimensionalsystemsinthepaulibasis