Variational Quantum Simulations of Multi-Orbital Impurity Models
ORAL
Abstract
We perform a systematic study of preparing ground states of correlated multi-orbital impurity models using the variational quantum eigensolver (VQE). We consider both fixed and adaptive wavefunction ans\"atze and analyze the resulting gate depths and performance. We analyze the qubit-adaptive VQE algorithm in the Hartree-Fock orbital basis, as well as the Hamiltonian variational ansatz (HVA) and a variant of adaptive VQE in the atomic orbital basis.
An operator pool composed of pairwise commutators of the Hamiltonian terms is developed to allow a fair comparison between the adaptive and the fixed HVA ansatz. Using state vector simulations, we show that the most compact ans\"atze is obtained in the atomic orbital representation with symmetry-based Pauli tapering within parity encoding. Finally, we perform adaptive VQE calculations including sampling noise and demonstrate that using a doubly decomposed form of the impurity Hamiltonian, symmetry-based qubit reduction, and stochastic optimizers dramatically reduces the number of shots required for the desired accuracy.
An operator pool composed of pairwise commutators of the Hamiltonian terms is developed to allow a fair comparison between the adaptive and the fixed HVA ansatz. Using state vector simulations, we show that the most compact ans\"atze is obtained in the atomic orbital representation with symmetry-based Pauli tapering within parity encoding. Finally, we perform adaptive VQE calculations including sampling noise and demonstrate that using a doubly decomposed form of the impurity Hamiltonian, symmetry-based qubit reduction, and stochastic optimizers dramatically reduces the number of shots required for the desired accuracy.
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Publication: Variational Quantum Simulations of Multi-Orbital Impurity Models (in preparation)
Presenters
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Anirban Mukherjee
Ames Laboratory, U.S. Department of Energy, Ames, Iowa 50011, USA
Authors
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Anirban Mukherjee
Ames Laboratory, U.S. Department of Energy, Ames, Iowa 50011, USA
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Noah Berthusen
Department of Computer Science, University of Maryland, College Park, MD, 20742, USA
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Peter P Orth
Department of Physics and Astronomy, Iowa State University, Ames, Iowa 50011, USA, Iowa State University, Ames Laboratory / Iowa State University, Ames Laboratory and Iowa State University, Iowa State University / Ames Laboratory
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Yongxin Yao
Ames Lab, Ames Laboratory, U.S. Department of Energy, Ames, Iowa 50011, USA