Artificial Neural Network Encoding of Molecular Wavefunction for Quantum Computing

11 January 2023, Version 3
This content is a preprint and has not undergone peer review at the time of posting.

Abstract

Artificial neural networks (ANNs) for material modeling have received significant interest. We recently reported an adaptation of ANNs based on Boltzmann machine (BM) architectures to an ansatz of the multiconfigurational many-electron wavefunction, designated neural-network quantum state (NQS), for quantum chemistry calculations [Yang et al., J. Chem. Theory Comput., 2020, 16, 3513--3529]. Here, this study presents its extended formalism to a quantum algorithm that enables the preparation of the NQS through quantum gates. The descriptors of the ANN model, which are chosen as the occupancies of electronic configurations, are quantum-mechanically represented by qubits. Our algorithm may thus bring potential advantages over classical sampling-based computation employed in the previous studies. The NQS can be accurately formed using quantum-native procedures. Still, the training of the model in terms of energy minimization is efficiently performed on a classical computer; thus, our approach is a class of variational quantum eigensolver. The BM models are related to the Gibbs distribution, and our preparation procedures exploit techniques of quantum phase estimation but with no Hamiltonian evolution. The proposed algorithm is assessed by implementing it on a quantum computer simulator. Illustrative molecular calculations at the complete-active-space configuration interaction level of theory are displayed, confirming consistency with the accuracy of our previous classical approaches.

Keywords

Neural Networks
Multireference Wavefunction
Quantum Computing

Supplementary materials

Title
Description
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Title
Algorithms and theory. Benchmark data.
Description
Algorithms acting as subroutines. Details of formulations and prototyping. Tabulated data of total energies obtained by calculations.
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Title
Geometric data of butadiene
Description
s-trans and s-cis butadiene: XYZ format
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Title
Geometric data of PABI
Description
XYZ format of geometry data of isomerization of pentaarylbiimidazole (PABI)
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