CSQD improves SQD energy estimates in strongly correlated systems by replacing a global reference occupancy vector with cluster-specific ones, lowering energies by up to 15.95 mHa for stretched N2 and 57.82 mHa for [2Fe-2S].
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2026 3representative citing papers
Hybrid QSCI method with LCNot-UCCSD ansatz and RBM-based configuration recovery enables NISQ-era molecular simulations, demonstrated on small molecules and DMET-embedded protein-ligand systems.
SQD-AA reduces total query complexity by more than 100x on model distributions and achieves the lowest T-gate counts with 3-4 orders shallower circuits than iQPE for molecular examples.
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Cluster-Adaptive Sample-Based Quantum Diagonalization for Strongly Correlated Systems
CSQD improves SQD energy estimates in strongly correlated systems by replacing a global reference occupancy vector with cluster-specific ones, lowering energies by up to 15.95 mHa for stretched N2 and 57.82 mHa for [2Fe-2S].
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Bridging the NISQ and Fault-Tolerant Regimes: Generative-ML-Assisted Quantum Selected CI for Molecular Simulations
Hybrid QSCI method with LCNot-UCCSD ansatz and RBM-based configuration recovery enables NISQ-era molecular simulations, demonstrated on small molecules and DMET-embedded protein-ligand systems.
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Sample-Based Quantum Diagonalization with Amplitude Amplification
SQD-AA reduces total query complexity by more than 100x on model distributions and achieves the lowest T-gate counts with 3-4 orders shallower circuits than iQPE for molecular examples.