结合变分量子本征求解器的基于迭代投影的嵌入方案
Iterative Projection-Based Embedding Scheme Combined with Variational Quantum Eigensolver
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中文总结 AI 辅助
该研究提出结合VQE的迭代投影嵌入框架，通过子系统VQE处理与环境平均场细化的交替迭代实现自洽，在测试系统及CH₂NH复合系统中均收敛良好，能量与势能面表现优于传统一次性方法，适配量子-经典混合计算。
中文摘要 AI 辅助
量子嵌入方法为将量子化学计算扩展到大型多尺度系统提供了有前景的途径，其以高精度理论处理化学上重要的子系统，同时以可承受的级别描述周围环境。这些方法也与基于资源有限硬件的量子计算方法高度相关。在此，我们提出一种结合变分量子本征求解器（VQE）的基于迭代投影的嵌入框架，其中环境密度可对VQE描述的嵌入子系统的精细电子结构进行自洽响应。与传统的一次性方法（环境在初始轨道优化后保持冻结）不同，所提出的迭代方案在子系统的VQE级别处理和环境的平均场级别细化之间交替进行，直到达到相互自洽。首先使用几个小型测试系统检查该方案的收敛行为，随后通过一个夹在两个苯环之间的CH₂NH分子组成的复合系统展示其实际适用性，其中C=N二面角从0旋转至90度。在所有测试的几何结构中，迭代过程均在约10次迭代步骤内一致收敛，产生的能量低于传统一次性嵌入结果。收敛结果很好地再现了采用相同活性空间的全相关参考能量，且得到的关于二面角旋转的势能面也与参考势能面高度吻合。这些结果表明，我们的迭代嵌入框架在数值上是稳健的，在物理上是合理的，能对子系统间的关联进行自洽且可靠的处理。我们期望其公式化将与新兴的量子-经典混合计算范式特别兼容。
英文摘要
Quantum embedding methods offer a promising route to extend quantum chemical calculations to large multiscale systems by treating a chemically important subsystem at a high level of theory while describing its surrounding environment at an affordable level. The methods are also quite relevant for quantum computing approaches based on hardware with limited resources. Here, we present an iterative projection-based embedding framework combined with VQE, in which the environment density is allowed to respond self-consistently to the refined electronic structure of the embedded subsystem described by VQE. Unlike conventional one-shot approaches where the environment remains frozen after the initial orbital optimization, the proposed iterative scheme alternates between the VQE-level treatment of the subsystem and a mean-field-level refinement of the environment until mutual self-consistency is achieved. The convergence behavior of the scheme is first examined using several small test systems. Its practical applicability is then demonstrated with a composite system with a CH2NH molecule sandwiched by two benzene rings, with the C=N dihedral angle rotating from 0 to 90 deg. The iterative procedure consistently converges within ~10 iteration steps across all tested geometries, yielding energies below the conventional one-shot embedding results. The converged results well reproduce the fully correlated reference energy employing the same active space, and the resulting potential energy surface with respect to the dihedral rotation is also in good agreement with the reference one. These results demonstrate that our iterative embedding framework is numerically robust and physically sound, yielding a self-consistent and reliable treatment of inter-subsystem correlation. We expect that its formulation will be particularly compatible with the emerging paradigm of quantum-classical hybrid computing.
