通过密度矩阵嵌入框架中的基于样本的量子对角化模拟配体状分子
Quantum Simulation of Ligand-like Molecules through Sample-based Quantum Diagonalization in Density Matrix Embedding Framework
AI总结：
研究利用基于样本的量子对角化方法在密度矩阵嵌入理论框架中计算配体状分子的基态能量，探讨纠缠结构对模拟效率和精度的影响，并展示DMET-SQD框架在化学精度内获得与DMET-FCI基准一致的结果。
摘要：
扩展分子系统中电子相关性的准确处理仍使用经典电子结构方法具有计算挑战性。混合量子-经典算法提供了一种克服这些限制的潜在途径；然而，其在现有量子计算机上的实际部署需要减少问题规模并减轻硬件噪声的策略。本文研究了使用基于样本的量子对角化（SQD）在密度矩阵嵌入理论（DMET）框架中计算配体状分子的基态能量，重点研究低对称系统和具有多样的键合模式的系统，这些系统表现出子系统依赖的碎片-环境纠缠变化。这些纠缠变化直接影响浴轨道构造、杂质大小和嵌入哈密顿量的结构，对嵌入和量子采样提出了非平凡的挑战。通过结合DMET碎片化与基于SQD的减少配置空间构造，通过量子采样和迭代配置恢复，我们在IBM的Eagle R3超导量子硬件（IBM Sherbrooke）上进行了量子模拟，从而表明嵌入子系统的纠缠结构在确定模拟的效率和准确性方面起着核心作用。尽管这些复杂性，我们展示了DMET-SQD框架在强相关性下获得与DMET-FCI基准一致的基态能量，所有研究系统均达到化学精度（1~kcal/mol）。这些结果表明，基于SQD的量子模拟可以稳健地扩展到低对称、化学现实、行业相关分子，并突显了纠缠意识嵌入策略在可扩展量子电子结构计算中的重要性。
英文摘要：
The accurate treatment of electron correlation in extended molecular systems remains computationally challenging using classical electronic structure methods. Hybrid quantum-classical algorithms offer a potential route to overcome these limitations; however, their practical deployment on existing quantum computers requires strategies that both reduce problem size and mitigate hardware noise. In this work, we investigate ground-state energy calculations of ligand-like molecules using Sample-based Quantum Diagonalization (SQD) within the Density Matrix Embedding Theory (DMET) framework, focusing on low-symmetry systems with diverse bonding motifs that exhibit subsystem-dependent variations in fragment-environment entanglement. These entanglement-based variations directly influence bath orbital construction, impurity sizes, and the structure of the embedded Hamiltonians, posing nontrivial challenges for both embedding and quantum sampling. By combining DMET fragmentation with SQD-based construction of reduced configuration spaces through quantum sampling and iterative configuration recovery, we perform quantum simulations on IBM's Eagle R3 (IBM Sherbrooke) and IBM's Heron R3 (IBM Boston) superconducting quantum hardware thereby, showing that the entanglement structure across embedding subsystems plays a central role in determining the efficiency and accuracy of the simulations. Despite these complexities, we show that the DMET-SQD framework yields ground-state energies in strong agreement with DMET-FCI benchmarks, achieving chemical accuracy (1 kcal/mol) across all systems studied. These results demonstrate that SQD-based quantum simulations can be robustly extended to low-symmetry, chemically realistic, industry relevant molecules, and highlight the importance of entanglement-aware embedding strategies for scalable quantum electronic structure calculations.
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