标题： 基于样本量子对角化和局部嵌入的电池材料表面反应模拟 显示英文标题

标题： Surface Reaction Simulations for Battery Materials through Sample-Based Quantum Diagonalization and Local Embedding

摘要： 精确的量子化学计算对于理解电子结构至关重要，但由于电子相关效应，精确求解多体薛定谔方程仍然不切实际。尽管密度泛函理论（DFT）被广泛使用，但其固有的近似限制了其捕捉强相关效应的能力，特别是在表面反应中。量子计算提供了一种有前景的替代方案，尤其是在局部电子相互作用方面。在本工作中，我们将量子嵌入方法应用于锂电池电极表面的氧还原反应的研究。我们采用活性空间选择策略，使用密度差分析来识别关键轨道，这些轨道随后通过耦合簇自然轨道进行细化。这些轨道使用基于样本的量子对角化（SQD）及其扩展版本（Ext-SQD）进行处理，利用局部单位簇Jastrow（LUCJ）假设在量子硬件上高效准备状态。Ext-SQD通过将激发算符纳入经典量子选定组态相互作用中使用的量子计算电子构型，显著优于标准SQD。我们的方法在基态能量计算方面优于耦合簇单重和双重（CCSD）计算。结果经完整活性空间组态相互作用（CASCI）验证，当计算可行时，以及热浴组态相互作用（HCI），为$\mathrm{Li}$-$\mathrm{O_2}$表面反应提供了新的见解，突显了量子计算在材料发现和反应建模中的潜力。 显示英文摘要

摘要： Accurate quantum chemistry calculations are essential for understanding electronic structures, yet exactly solving the many-body Schr\"odinger equation remains impractical due to electron correlation effects. While Density Functional Theory (DFT) is widely used, its inherent approximations limit its ability to capture strong correlation effects, particularly in surface reactions. Quantum computing offers a promising alternative, especially for localized electron interactions. In this work, we apply a quantum embedding approach to study the Oxygen Reduction Reaction at Lithium battery electrode surfaces. We employ an active space selection strategy, using Density Difference Analysis to identify key orbitals, which are subsequently refined with coupled-cluster natural orbitals. These are treated using Sample-Based Quantum Diagonalization (SQD) and its extended version (Ext-SQD), leveraging the Local Unitary Cluster Jastrow (LUCJ) ansatz for efficient state preparation on quantum hardware. Ext-SQD significantly improves upon standard SQD by incorporating excitation operators into the quantum-computed electron configurations used in classical Quantum Selected Configuration Interaction. Our approach demonstrates improved accuracy over Coupled Cluster Singles and Doubles (CCSD) calculations over ground state energies. The results, validated against Complete Active Space Configuration Interaction (CASCI), whenever computationally feasible, and Heat-Bath Configuration Interaction (HCI), provide new insights into $\mathrm{Li}$-$\mathrm{O_2}$ surface reactions, underscoring the potential of quantum computing in materials discovery and reaction modeling.