Quantum-assisted Monte Carlo algorithms for fermions
Quantum computing is a promising way to systematically solve the longstanding computational problem, the ground state of a many-body fermion system. Many efforts have been made to realise certain forms of quantum advantage in this problem, for instance, the development of variational quantum algorit...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Verein zur Förderung des Open Access Publizierens in den Quantenwissenschaften
2023-08-01
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| Series: | Quantum |
| Online Access: | https://quantum-journal.org/papers/q-2023-08-03-1072/pdf/ |
| _version_ | 1797755418844332032 |
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| author | Xiaosi Xu Ying Li |
| author_facet | Xiaosi Xu Ying Li |
| author_sort | Xiaosi Xu |
| collection | DOAJ |
| description | Quantum computing is a promising way to systematically solve the longstanding computational problem, the ground state of a many-body fermion system. Many efforts have been made to realise certain forms of quantum advantage in this problem, for instance, the development of variational quantum algorithms. A recent work by Huggins et al. [1] reports a novel candidate, i.e. a quantum-classical hybrid Monte Carlo algorithm with a reduced bias in comparison to its fully-classical counterpart. In this paper, we propose a family of scalable quantum-assisted Monte Carlo algorithms where the quantum computer is used at its minimal cost and still can reduce the bias. By incorporating a Bayesian inference approach, we can achieve this quantum-facilitated bias reduction with a much smaller quantum-computing cost than taking empirical mean in amplitude estimation. Besides, we show that the hybrid Monte Carlo framework is a general way to suppress errors in the ground state obtained from classical algorithms. Our work provides a Monte Carlo toolkit for achieving quantum-enhanced calculation of fermion systems on near-term quantum devices. |
| first_indexed | 2024-03-12T17:46:40Z |
| format | Article |
| id | doaj.art-786b2210fc65469fac70708d97b1c0b2 |
| institution | Directory Open Access Journal |
| issn | 2521-327X |
| language | English |
| last_indexed | 2024-03-12T17:46:40Z |
| publishDate | 2023-08-01 |
| publisher | Verein zur Förderung des Open Access Publizierens in den Quantenwissenschaften |
| record_format | Article |
| series | Quantum |
| spelling | doaj.art-786b2210fc65469fac70708d97b1c0b22023-08-03T14:02:46ZengVerein zur Förderung des Open Access Publizierens in den QuantenwissenschaftenQuantum2521-327X2023-08-017107210.22331/q-2023-08-03-107210.22331/q-2023-08-03-1072Quantum-assisted Monte Carlo algorithms for fermionsXiaosi XuYing LiQuantum computing is a promising way to systematically solve the longstanding computational problem, the ground state of a many-body fermion system. Many efforts have been made to realise certain forms of quantum advantage in this problem, for instance, the development of variational quantum algorithms. A recent work by Huggins et al. [1] reports a novel candidate, i.e. a quantum-classical hybrid Monte Carlo algorithm with a reduced bias in comparison to its fully-classical counterpart. In this paper, we propose a family of scalable quantum-assisted Monte Carlo algorithms where the quantum computer is used at its minimal cost and still can reduce the bias. By incorporating a Bayesian inference approach, we can achieve this quantum-facilitated bias reduction with a much smaller quantum-computing cost than taking empirical mean in amplitude estimation. Besides, we show that the hybrid Monte Carlo framework is a general way to suppress errors in the ground state obtained from classical algorithms. Our work provides a Monte Carlo toolkit for achieving quantum-enhanced calculation of fermion systems on near-term quantum devices.https://quantum-journal.org/papers/q-2023-08-03-1072/pdf/ |
| spellingShingle | Xiaosi Xu Ying Li Quantum-assisted Monte Carlo algorithms for fermions Quantum |
| title | Quantum-assisted Monte Carlo algorithms for fermions |
| title_full | Quantum-assisted Monte Carlo algorithms for fermions |
| title_fullStr | Quantum-assisted Monte Carlo algorithms for fermions |
| title_full_unstemmed | Quantum-assisted Monte Carlo algorithms for fermions |
| title_short | Quantum-assisted Monte Carlo algorithms for fermions |
| title_sort | quantum assisted monte carlo algorithms for fermions |
| url | https://quantum-journal.org/papers/q-2023-08-03-1072/pdf/ |
| work_keys_str_mv | AT xiaosixu quantumassistedmontecarloalgorithmsforfermions AT yingli quantumassistedmontecarloalgorithmsforfermions |