The impact of quantum circuit architecture and hyperparameters on variational quantum algorithms exemplified in the electronic structure of the GaAs crystal
Abstract Variational Quantum Algorithms (VQAs) provide a promising framework for solving electronic structure problems using the computational capabilities of quantum computers to explore high-dimensional Hilbert spaces efficiently. This research investigates the performance of VQAs in electronic st...
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Nature Portfolio
2025-05-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-025-00151-x |
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| author | Ivana Miháliková Michal Krejčí Martin Friák |
| author_facet | Ivana Miháliková Michal Krejčí Martin Friák |
| author_sort | Ivana Miháliková |
| collection | DOAJ |
| description | Abstract Variational Quantum Algorithms (VQAs) provide a promising framework for solving electronic structure problems using the computational capabilities of quantum computers to explore high-dimensional Hilbert spaces efficiently. This research investigates the performance of VQAs in electronic structure calculations of gallium arsenide (GaAs), a semiconductor with a zinc-blende structure. Utilizing a tight-binding Hamiltonian and a Jordan-Wigner-like transformation, we map the problem to a 10-qubit Hamiltonian. We analyze the impact of quantum circuit architectures, algorithm hyperparameters, and optimization methods on two VQAs: Variational Quantum Deflation (VQD) and Subspace Search Variational Quantum Eigensolver (SSVQE). We observed that while both algorithms offer promising results, the choice of ansatz and hyperparameter tuning were especially critical in achieving reliable outcomes, particularly for higher energy states. Adjusting the hyperparameters in VQD significantly enhanced the accuracy of higher energy state calculations, reducing the error by an order of magnitude, whereas tuning the hyperparameters in SSVQE had minimal impact. Our findings provide insights into optimizing VQAs for electronic structure problems, paving the way for their application to more complex systems on near-term quantum devices. |
| format | Article |
| id | doaj-art-e709e48a1f7b43f596c9c4d4d03497c6 |
| institution | OA Journals |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | Nature Portfolio |
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| series | Scientific Reports |
| spelling | doaj-art-e709e48a1f7b43f596c9c4d4d03497c62025-08-20T02:15:15ZengNature PortfolioScientific Reports2045-23222025-05-0115111410.1038/s41598-025-00151-xThe impact of quantum circuit architecture and hyperparameters on variational quantum algorithms exemplified in the electronic structure of the GaAs crystalIvana Miháliková0Michal Krejčí1Martin Friák2Institute of Physics of Materials, Czech Academy of SciencesInstitute of Physics of Materials, Czech Academy of SciencesInstitute of Physics of Materials, Czech Academy of SciencesAbstract Variational Quantum Algorithms (VQAs) provide a promising framework for solving electronic structure problems using the computational capabilities of quantum computers to explore high-dimensional Hilbert spaces efficiently. This research investigates the performance of VQAs in electronic structure calculations of gallium arsenide (GaAs), a semiconductor with a zinc-blende structure. Utilizing a tight-binding Hamiltonian and a Jordan-Wigner-like transformation, we map the problem to a 10-qubit Hamiltonian. We analyze the impact of quantum circuit architectures, algorithm hyperparameters, and optimization methods on two VQAs: Variational Quantum Deflation (VQD) and Subspace Search Variational Quantum Eigensolver (SSVQE). We observed that while both algorithms offer promising results, the choice of ansatz and hyperparameter tuning were especially critical in achieving reliable outcomes, particularly for higher energy states. Adjusting the hyperparameters in VQD significantly enhanced the accuracy of higher energy state calculations, reducing the error by an order of magnitude, whereas tuning the hyperparameters in SSVQE had minimal impact. Our findings provide insights into optimizing VQAs for electronic structure problems, paving the way for their application to more complex systems on near-term quantum devices.https://doi.org/10.1038/s41598-025-00151-x |
| spellingShingle | Ivana Miháliková Michal Krejčí Martin Friák The impact of quantum circuit architecture and hyperparameters on variational quantum algorithms exemplified in the electronic structure of the GaAs crystal Scientific Reports |
| title | The impact of quantum circuit architecture and hyperparameters on variational quantum algorithms exemplified in the electronic structure of the GaAs crystal |
| title_full | The impact of quantum circuit architecture and hyperparameters on variational quantum algorithms exemplified in the electronic structure of the GaAs crystal |
| title_fullStr | The impact of quantum circuit architecture and hyperparameters on variational quantum algorithms exemplified in the electronic structure of the GaAs crystal |
| title_full_unstemmed | The impact of quantum circuit architecture and hyperparameters on variational quantum algorithms exemplified in the electronic structure of the GaAs crystal |
| title_short | The impact of quantum circuit architecture and hyperparameters on variational quantum algorithms exemplified in the electronic structure of the GaAs crystal |
| title_sort | impact of quantum circuit architecture and hyperparameters on variational quantum algorithms exemplified in the electronic structure of the gaas crystal |
| url | https://doi.org/10.1038/s41598-025-00151-x |
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