Enhancing the accuracy and efficiency of sample-based quantum diagonalization with phaseless auxiliary-field quantum Monte Carlo
Year: 2025
Type: preprint
Abstract: Quantum Selected Configuration Interaction (QSCI) and an extended protocol known as Sample-based Quantum Diagonalization (SQD) have emerged as promising algorithms to solve the electronic Schrödinger equation with noisy quantum computers. In QSCI/SQD a quantum circuit is repeatedly prepared on the quantum device, and measured configurations form a subspace of the many-body Hilbert space in which the Hamiltonian is diagonalized classically. For the dissociation of N$_2$ and a model $\mathrm{[2Fe-2S]}$ cluster (correlating 10 electrons in 26 orbitals and 30 electrons in 20 orbitals, respectively) we show that a non-perturbative stochastic approach, phaseless auxiliary-field quantum Monte Carlo (ph-AFQMC), using truncated SQD trial wavefunctions obtained from quantum hardware can recover a substantial amount (e.g., O(100) mHa) of correlation energy and alleviate the possible sampling redundancy of the QSCI/SQD procedure. Extrapolation of the ph-AFQMC energy versus the energy variance of the SQD trial wavefunctions has the potential to further improve the energy accuracy.
Source: arXiv (Cornell University)
Authors: Danilov, Don, Robledo-Moreno, Javier, Sung, Kevin J., Motta, Mario, Shee, James
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W6979374904
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