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Enhancing the accuracy and efficiency of sample-based quantum diagonalization with phaseless auxiliary-field quantum Monte Carlo

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arxiv 2503.05967 v2 pith:JM2V4SFC submitted 2025-03-07 quant-ph

classification quant-ph
keywords quantumenergyqsciaccuracyauxiliary-fieldcarlodiagonalizationelectrons
verification ladder T0 review T1 audit T2 compute T3 formal
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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 Schr\"odinger 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.

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Cited by 3 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Towards Chemically Accurate and Scalable Quantum Simulations on IQM Quantum Hardware: A Quantum-HPC Hybrid Approach

    quant-ph 2026-04 accept novelty 5.5 of 10

    SQD with LUCJ (and a new LCNot-UCCSD variant) on IQM Sirius recovers chemically accurate energies, 1D/2D PES, and DMET-embedded ligand/amantadine results versus FCI/CASCI references.

  2. Coupled cluster method tailored by quantum selected configuration interaction

    physics.chem-ph 2025-06 conditional novelty 5.0 of 10

    QSCI-TCC combines quantum-selected CI with tailored coupled-cluster to achieve accurate bond-breaking energies while using far fewer measurement shots.

  3. Machine-Learned Compact Subspace Generation for Quantum Selected Configuration Interaction within Density Matrix Embedding Framework

    quant-ph 2026-07 conditional novelty 4.0 of 10

    An RBM-guided selected-CI solver inside DMET reaches the DMET-CASCI energy within 1.6 mHa using ~4% of the symmetry-valid configuration subspace on an 11-fragment protein–ligand model.

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