发表机构
Fujitsu Limited.（富士通株式会社）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本研究提出在QSCI中经典预置Hartree-Fock组态以减少测量冗余，推导出替代算子选择准则的闭式能量梯度，在相同射击预算下显著减少CNOT门和射击数，但优势受预算影响。
AI 中文摘要
预测许多分子性质需要分子哈密顿量的精确基态能量。量子选择组态相互作用（QSCI）通过测量输入态以选择重要的电子组态，并在它们张成的子空间中经典地对角化哈密顿量来获得此类能量。ADAPT-QSCI是QSCI的自适应扩展，通过迭代电路增长改进输入态。对于单参考分子，采样分布由Hartree-Fock（HF）组态主导，因此大多数测量重复了已知的组态。我们通过在测量前将HF组态经典地放入对角化子空间来减少这种冗余。这使得ADAPT-QSCI的算子选择准则失效，我们推导出一个一致的能量和梯度闭式替代，且不增加量子设备的查询次数。在先前用于ADAPT-QSCI的每迭代射击预算下，所提出的方案以约63%和43%的CNOT门数（对于H4和H6）以及总射击数的44%和40%达到化学精度。然而，优势取决于预算：在无限射击极限下，H4的CNOT计数增加到ADAPT-QSCI的125%。这些结果将每迭代射击预算确定为控制基于QSCI算法资源节省的关键设计变量。
英文摘要
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 $\mathrm{H}_4$ and $\mathrm{H}_6$, and $44\%$ and $40\%$ of the total shots. The advantage depends on the budget, however: in the infinite-shot limit the $\mathrm{H}_4$ 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.
Comments14 pages, 4 figures
