Circuit growth and subspace read-out in quantum-selected configuration interaction: Separating the Hartree-Fock determinant
Abstract
Predicting many molecular properties requires accurate ground-state energies of molecular Hamiltonians. Quantum-selected configuration interaction (QSCI) obtains such energies by measuring an input state to select important electronic configurations and classically diagonalizing the Hamiltonian in the subspace they span. ADAPT-QSCI, an adaptive extension of QSCI, improves the input state through iterative circuit growth. For single-reference molecules, the sampling distribution is dominated by the Hartree-Fock (HF) configuration, so most measurements reproduce a configuration already known. We reduce this redundancy by placing the HF configuration in the diagonalization subspace classically, before any measurement. This invalidates the operator-selection criterion of ADAPT-QSCI, and we derive a consistent replacement with energy and gradient in closed form, adding no query to the quantum device. At the per-iteration shot budgets previously used for ADAPT-QSCI, the proposed scheme reaches chemical accuracy with approximately 63% and 43% of the CNOT gates for H4 and H6, and 44% and 40% of the total shots. The advantage depends on the budget, however: in the infinite-shot limit the H4 CNOT count increases to 125% of that of ADAPT-QSCI. These results identify the per-iteration shot budget as a key design variable governing resource savings in QSCI-based algorithms.
Related
- Rotated-Frame Determinant Discovery for Ground- and Excited-State Quantum Selected Configuration Interaction
- Machine-Learned Compact Subspace Generation for Quantum Selected Configuration Interaction within Density Matrix Embedding Framework
- Selected Coupled Cluster Guided by Selected Configuration Interaction
- QUBO–SAMPLING–DRIVEN SELECTED CONFIGURATION INTERACTION
- A Divide-and-Conquer Quantum-Selected Configuration Interaction for Evaluating π-π Stacking Interaction Energies in the Benzene Dimer
BibTeX
@misc{fujimoto2026circuit,
title = {{Circuit growth and subspace read-out in quantum-selected configuration interaction: Separating the Hartree-Fock determinant}},
author = {Ayaka Fujimoto and Norifumi Matsumoto and Shota Kanasugi and Kazunori Maruyama and Hirotaka Oshima},
howpublished = {arXiv},
year = {2026},
month = oct,
doi = {10.48550/arxiv.2610.03114},
eprint = {2610.03114},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2610.03114},
}
RIS
TY - UNPB
TI - Circuit growth and subspace read-out in quantum-selected configuration interaction: Separating the Hartree-Fock determinant
AU - Ayaka Fujimoto
AU - Norifumi Matsumoto
AU - Shota Kanasugi
AU - Kazunori Maruyama
AU - Hirotaka Oshima
PY - 2026
DA - 2026/10/02
PB - arXiv
DO - 10.48550/arxiv.2610.03114
UR - https://arxiv.org/abs/2610.03114
AB - Predicting many molecular properties requires accurate ground-state energies of molecular Hamiltonians. Quantum-selected configuration interaction (QSCI) obtains such energies by measuring an input state to select important electronic configurations and classically diagonalizing the Hamiltonian in the subspace they span. ADAPT-QSCI, an adaptive extension of QSCI, improves the input state through iterative circuit growth. For single-reference molecules, the sampling distribution is dominated by the Hartree-Fock (HF) configuration, so most measurements reproduce a configuration already known. We reduce this redundancy by placing the HF configuration in the diagonalization subspace classically, before any measurement. This invalidates the operator-selection criterion of ADAPT-QSCI, and we derive a consistent replacement with energy and gradient in closed form, adding no query to the quantum device. At the per-iteration shot budgets previously used for ADAPT-QSCI, the proposed scheme reaches chemical accuracy with approximately 63% and 43% of the CNOT gates for H_4 and H_6, and 44% and 40% of the total shots. The advantage depends on the budget, however: in the infinite-shot limit the H_4 CNOT count increases to 125% of that of ADAPT-QSCI. These results identify the per-iteration shot budget as a key design variable governing resource savings in QSCI-based algorithms.
ER -