Reducing Circuit Depth in Adaptive Variational Quantum Algorithms via Effective Hamiltonian TheoriesClick to copy article linkArticle link copied!
- Jie LiuJie LiuHefei National Laboratory, University of Science and Technology of China, Hefei 230088, ChinaMore by Jie Liu
- Zhenyu Li*Zhenyu Li*Email: [email protected] (Zhenyu Li).Hefei National Research Center for Physical Sciences at the Microscale, University of Science and Technology of China, Hefei 230026, ChinaHefei National Laboratory, University of Science and Technology of China, Hefei 230088, ChinaMore by Zhenyu Li
- Jinlong Yang*Jinlong Yang*Email: [email protected] (Jinlong Yang).Hefei National Research Center for Physical Sciences at the Microscale, University of Science and Technology of China, Hefei 230026, ChinaHefei National Laboratory, University of Science and Technology of China, Hefei 230088, ChinaMore by Jinlong Yang
Abstract
The electronic structure is an anticipated application for quantum computers. However, quantum circuits required to represent the highly entangled electronic wave functions within the variational quantum eigensolver (VQE) framework are far beyond the capacity of current quantum devices. To adapt the VQE algorithms to near-term quantum hardware, it has been suggested to incorporate a part of the electronic correlation into an effective Hamiltonian, leaving the wave function in a less entangled form. We propose a new scheme to construct the effective Hamiltonian with the transformation in the form of a product of linear combinations of excitation operators. This new scheme promises a quadratic multiplicative growth of the effective Hamiltonian. We integrate this effective Hamiltonian method into the adaptive VQE algorithms to maintain constant-size quantum circuits. The new computational scheme is assessed by performing numerical simulations for small molecules. A milli-Hartree accuracy in a minimal basis is achieved with a much shallower circuit depth.
Cited By
This article is cited by 5 publications.
- Francesco A. Evangelista, Victor S. Batista. Editorial: Quantum Computing for Chemistry. Journal of Chemical Theory and Computation 2023, 19
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, 7435-7436. https://doi.org/10.1021/acs.jctc.3c01043
- Robert A. Lang, Aadithya Ganeshram, Artur F. Izmaylov. Growth Reduction of Similarity-Transformed Electronic Hamiltonians in Qubit Space. Journal of Chemical Theory and Computation 2023, 19
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, 6656-6667. https://doi.org/10.1021/acs.jctc.3c00712
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, 5407-5417. https://doi.org/10.1021/acs.jctc.3c00068
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, 119-128. https://doi.org/10.1360/SSC-2022-0222
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