Benchmarking Variational Quantum Eigensolvers for Quantum Chemistry
Quantum chemistry is one of the most promising applications of quantum computers in the near future. For noisy intermediate-scale quantum devices, the quantum-classical hybrid framework based on the variational quantum eigensolver (VQE) has become the method of choice. In the literature, there are m...
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Zusammenfassung: | Quantum chemistry is one of the most promising applications of quantum
computers in the near future. For noisy intermediate-scale quantum devices, the
quantum-classical hybrid framework based on the variational quantum eigensolver
(VQE) has become the method of choice. In the literature, there are many
different variants of VQE, but it is not known which one is optimal for a given
molecule. For this purpose, we perform a thorough benchmarking on more than ten
different kinds of VQE ansatzes (in systems up to 30 qubits), based on their
performance on the energy accuracy, runtime until convergence, and number of
parameters. Our results show that the ADAPT ansatz can be used to obtain more
accurate energy for small systems (below 14 qubits), but it costs much more
computational resources. For larger molecules, UCCSD0 has better performance.
However, all the tested ansatzes can hardly reach chemical accuracy at
stretched bond lengths. Our results were obtained using MindSpore Quantum,
where the codes and the benchmarking toolkit are publicly available at Gitee. |
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DOI: | 10.48550/arxiv.2211.12775 |