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Autori principali: Huynh, Trung, An, Gwangil, Kim, Minsu, Jeon, Yu-Seong, Lee, Jinhyoung
Natura: Preprint
Pubblicazione: 2024
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Accesso online:https://arxiv.org/abs/2410.03130
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author Huynh, Trung
An, Gwangil
Kim, Minsu
Jeon, Yu-Seong
Lee, Jinhyoung
author_facet Huynh, Trung
An, Gwangil
Kim, Minsu
Jeon, Yu-Seong
Lee, Jinhyoung
contents The variational quantum eigensolver algorithm has gained attentions due to its capability of locating the ground state and ground energy of a Hamiltonian, which is a fundamental task in many physical and chemical problems. Although it has demonstrated promising results, the use of various types of measurements remains a significant obstacle. Recently, a quantum phase estimation algorithm inspired measurement scheme has been proposed to overcome this issue by introducing an additional ancilla system that is coupled to the primary system. Based on this measurement scheme, we present a novel approach that employs Bayesian inference principles together with von Mises-Fisher distribution and theoretically demonstrates the new algorithm's capability in identifying the ground state with certain for various random Hamiltonian matrices. This also opens a new way for exploring the von Mises-Fisher distribution potential in other quantum information science problems.
format Preprint
id arxiv_https___arxiv_org_abs_2410_03130
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle A variational quantum algorithm by Bayesian Inference with von Mises-Fisher distribution
Huynh, Trung
An, Gwangil
Kim, Minsu
Jeon, Yu-Seong
Lee, Jinhyoung
Quantum Physics
The variational quantum eigensolver algorithm has gained attentions due to its capability of locating the ground state and ground energy of a Hamiltonian, which is a fundamental task in many physical and chemical problems. Although it has demonstrated promising results, the use of various types of measurements remains a significant obstacle. Recently, a quantum phase estimation algorithm inspired measurement scheme has been proposed to overcome this issue by introducing an additional ancilla system that is coupled to the primary system. Based on this measurement scheme, we present a novel approach that employs Bayesian inference principles together with von Mises-Fisher distribution and theoretically demonstrates the new algorithm's capability in identifying the ground state with certain for various random Hamiltonian matrices. This also opens a new way for exploring the von Mises-Fisher distribution potential in other quantum information science problems.
title A variational quantum algorithm by Bayesian Inference with von Mises-Fisher distribution
topic Quantum Physics
url https://arxiv.org/abs/2410.03130