Contextual Subspace Auxiliary-Field Quantum Monte Carlo: Improved bias with reduced quantum resources

Fuente: arXiv
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Hauptverfasser: Kiser, Matthew, Beuerle, Matthias, Simkovic IV, Fedor
Format: Preprint
Veröffentlicht: 2024
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author Kiser, Matthew
Beuerle, Matthias
Simkovic IV, Fedor
author_facet Kiser, Matthew
Beuerle, Matthias
Simkovic IV, Fedor
contents Using trial wavefunctions prepared on quantum devices to reduce the bias of auxiliary-field quantum Monte Carlo (QC-AFQMC) has established itself as a promising hybrid approach to the simulation of strongly correlated many body systems. Here, we further reduce the required quantum resources by decomposing the trial wavefunction into classical and quantum parts, respectively treated by classical and quantum devices, within the contextual subspace projection formalism. Importantly, we show that our algorithm is compatible with the recently developed matchgate shadow protocol for efficient overlap calculation in QC-AFQMC. Investigating the nitrogen dimer and the reductive decomposition of ethylene carbonate in lithium-based batteries, we observe that our method outperforms a number of established algorithm for ground state energy computations, while reaching chemical accuracy with less than half of the original number of qubits.
format Preprint
id arxiv_https___arxiv_org_abs_2408_06160
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Contextual Subspace Auxiliary-Field Quantum Monte Carlo: Improved bias with reduced quantum resources
Kiser, Matthew
Beuerle, Matthias
Simkovic IV, Fedor
Quantum Physics
Strongly Correlated Electrons
Chemical Physics
Using trial wavefunctions prepared on quantum devices to reduce the bias of auxiliary-field quantum Monte Carlo (QC-AFQMC) has established itself as a promising hybrid approach to the simulation of strongly correlated many body systems. Here, we further reduce the required quantum resources by decomposing the trial wavefunction into classical and quantum parts, respectively treated by classical and quantum devices, within the contextual subspace projection formalism. Importantly, we show that our algorithm is compatible with the recently developed matchgate shadow protocol for efficient overlap calculation in QC-AFQMC. Investigating the nitrogen dimer and the reductive decomposition of ethylene carbonate in lithium-based batteries, we observe that our method outperforms a number of established algorithm for ground state energy computations, while reaching chemical accuracy with less than half of the original number of qubits.
title Contextual Subspace Auxiliary-Field Quantum Monte Carlo: Improved bias with reduced quantum resources
topic Quantum Physics
Strongly Correlated Electrons
Chemical Physics
url https://arxiv.org/abs/2408.06160