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Exploring Parameter Redundancy in the Unitary Coupled-Cluster Ansätze for Hybrid Variational Quantum Computing
Abstract
One of the commonly used chemical-inspired approaches in variational quantum computing is the unitary coupled-cluster (UCC) ansatze. Despite being a systematic way of approaching the exact limit, the number of parameters in the standard UCC ansatze exhibits unfavorable scaling with respect to the system size, hindering its practical use on near-term quantum devices. Efforts have been taken to propose some variants of UCC ansatze with better scaling. In this paper we explore the parameter redundancy in the preparation of unitary coupled-cluster singles and doubles (UCCSD) ansatze employing spin-adapted formulation, small amplitude filtration, and entropy-based orbital selection approaches. Numerical results of using our approach on some small molecules have exhibited a significant cost reduction in the number of parameters to be optimized and in the time to convergence compared with conventional UCCSD-VQE simulations. Further, we also discuss the potential application of some machine learning techniques in further exploring the parameter redundancy, providing a possible direction for future studies.
- Authors:
-
- Indian Institute of Science Education and Research (IISER), Kolkata (India)
- Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)
- Argonne National Laboratory (ANL), Argonne, IL (United States)
- Publication Date:
- Research Org.:
- Argonne National Laboratory (ANL), Argonne, IL (United States); National Quantum Information Science (QIS) Research Centers (United States). Next Generation Quantum Science and Engineering (Q-NEXT); Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)
- Sponsoring Org.:
- USDOE Office of Science (SC)
- OSTI Identifier:
- 2203855
- Alternate Identifier(s):
- OSTI ID: 1985900
- Report Number(s):
- PNNL-SA-181544
Journal ID: ISSN 1089-5639; 182187
- Grant/Contract Number:
- AC02-06CH11357; 1F-60579; AC05-76RL01830
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Journal of Physical Chemistry. A, Molecules, Spectroscopy, Kinetics, Environment, and General Theory
- Additional Journal Information:
- Journal Volume: 127; Journal Issue: 20; Journal ID: ISSN 1089-5639
- Publisher:
- American Chemical Society
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CHEMISTRY; Energy; Entropy; Mathematical methods; Molecules; Quantum mechanics
Citation Formats
Mehendale, Shashank G., Peng, Bo, Govind, Niranjan, and Alexeev, Yuri. Exploring Parameter Redundancy in the Unitary Coupled-Cluster Ansätze for Hybrid Variational Quantum Computing. United States: N. p., 2023.
Web. doi:10.1021/acs.jpca.3c00550.
Mehendale, Shashank G., Peng, Bo, Govind, Niranjan, & Alexeev, Yuri. Exploring Parameter Redundancy in the Unitary Coupled-Cluster Ansätze for Hybrid Variational Quantum Computing. United States. https://doi.org/10.1021/acs.jpca.3c00550
Mehendale, Shashank G., Peng, Bo, Govind, Niranjan, and Alexeev, Yuri. Tue .
"Exploring Parameter Redundancy in the Unitary Coupled-Cluster Ansätze for Hybrid Variational Quantum Computing". United States. https://doi.org/10.1021/acs.jpca.3c00550.
@article{osti_2203855,
title = {Exploring Parameter Redundancy in the Unitary Coupled-Cluster Ansätze for Hybrid Variational Quantum Computing},
author = {Mehendale, Shashank G. and Peng, Bo and Govind, Niranjan and Alexeev, Yuri},
abstractNote = {One of the commonly used chemical-inspired approaches in variational quantum computing is the unitary coupled-cluster (UCC) ansatze. Despite being a systematic way of approaching the exact limit, the number of parameters in the standard UCC ansatze exhibits unfavorable scaling with respect to the system size, hindering its practical use on near-term quantum devices. Efforts have been taken to propose some variants of UCC ansatze with better scaling. In this paper we explore the parameter redundancy in the preparation of unitary coupled-cluster singles and doubles (UCCSD) ansatze employing spin-adapted formulation, small amplitude filtration, and entropy-based orbital selection approaches. Numerical results of using our approach on some small molecules have exhibited a significant cost reduction in the number of parameters to be optimized and in the time to convergence compared with conventional UCCSD-VQE simulations. Further, we also discuss the potential application of some machine learning techniques in further exploring the parameter redundancy, providing a possible direction for future studies.},
doi = {10.1021/acs.jpca.3c00550},
journal = {Journal of Physical Chemistry. A, Molecules, Spectroscopy, Kinetics, Environment, and General Theory},
number = 20,
volume = 127,
place = {United States},
year = {Tue May 16 00:00:00 EDT 2023},
month = {Tue May 16 00:00:00 EDT 2023}
}
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