Evaluating Variational Quantum Eigensolver Approaches for Simplified Models of Molecular Systems: A Case Study on Protocatechuic Acid
The Variational Quantum Eigensolver (VQE) is a hybrid algorithm that combines quantum and classical computing to determine the ground-state energy of molecular systems. In this context, this study applies VQE to investigate the ground state of protocatechuic acid, analyzing its performance with various Ansatzes and active spaces. Subsequently, all VQE results were compared to those obtained with the CISD and FCI methods. The results demonstrate that Ansatzes, like Unitary Coupled Cluster Singles and Doubles (UCCSD) and variations of Hardware-Efficient Ansatzes, generally achieve accuracy close to that of FCI. In conclusion, this study highlights the effectiveness of VQE as a robust method for investigating molecular ground-state energies. Additionally, the findings emphasize the pivotal role of Ansatz design and active space selection in optimizing VQE performance, offering meaningful insights into its capabilities and constraints.
Authors
- Mauro Q. Nooblath Neto (ORCID: https://orcid.org/0000-0003-2972-9463)
- Belisario E. Fernández (ORCID: https://orcid.org/0000-0002-5672-1996)
- Maria Heloísa Fraga da Silva (ORCID: https://orcid.org/0009-0002-9553-7988)
- Amanda Marques de Lima (ORCID: https://orcid.org/0000-0003-0813-8218)
- Erico S. Teixeira (ORCID: https://orcid.org/0000-0003-0520-5075)
- Gleydson Fernandes de Jesus (ORCID: https://orcid.org/0009-0006-9076-0012)
- Clebson Cruz (ORCID: https://orcid.org/0000-0003-3318-1111)
- Eivson D. Silva (ORCID: https://orcid.org/0000-0001-5566-3336)
- Lucas Queiroz Galvão
Institutions
- Serviço Nacional de Aprendizagem Industrial (BR)
- Universidade Federal de Pernambuco (BR)
- Universidade Federal do Oeste da Bahia (BR)
- Centro de Estudos e Sistemas Avançados do Recife (BR)
Publication Details
- Journal
- Molecules
- Published
- 2024-12-31
- DOI
- https://doi.org/10.3390/molecules30010119
- Citations
- 4
- Primary Topic
- Quantum Computing Algorithms and Architecture
- Type
- article
- Field-Weighted Citation Impact
- 1.39
Funders
- Ministério da Ciência, Tecnologia e Inovação
- Fundação de Amparo à Pesquisa do Estado da Bahia
- Empresa Brasileira de Pesquisa e Inovação Industrial