发表机构
Purdue University; North Carolina State University; Oak Ridge National Laboratory（普渡大学; 北卡罗来纳州立大学; 橡树岭国家实验室）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
提出参数与拟设迁移策略（含AARTI方法），利用相关哈密顿量间的相似性，显著减少Li_xCoO_2等材料量子模拟的优化步骤，保持精度并提高可扩展性。
AI 中文摘要
量子计算为电子结构计算提供了一条有前景的途径，但实际的凝聚态应用通常需要求解由 $\mathbf{k}$ 点采样、成分变化、缺陷和系统尺寸变化所产生的大量相关哈密顿量族。在此，我们开发了在相关哈密顿量之间迁移变分信息以加速量子模拟的策略。对于相同嵌入尺寸的哈密顿量，优化后的变分参数在相关计算之间进行迁移。对于不同尺寸，我们引入了增强拟设复用用于目标初始化（AARTI），该方法迁移兼容的泡利生成器结构和优化的源参数，然后用目标特定的生成器增强拟设。我们的工作流程结合了密度泛函理论、Wannier 降维、嵌入紧束缚哈密顿量、变分量子算法和神经网络量子态，并使用 NVIDIA 的 CUDA-Q 平台实现量子电路模拟。以 Li$_x$CoO$_2$ 作为代表性电池正极材料，我们研究了涵盖多个脱锂水平、密集 $\mathbf{k}$ 点网格和增大尺寸的哈密顿量族。参数和拟设迁移显著减少了求解这些相关哈密顿量所需的优化步骤，同时保持了共同的目标精度，并在若干情况下降低了终端误差。计算得到的电子结构随脱锂的演化表现出与实验一致的显著非刚性带行为。这些结果建立了一个利用相关哈密顿量之间相似性的框架，以提高现实凝聚态系统量子工作流程的效率和可扩展性。
英文摘要
Quantum computing offers a promising route for electronic-structure calculations, but practical condensed-matter applications often require solving large families of related Hamiltonians arising from $\mathbf{k}$-point sampling, compositional variation, defects, and changes in system size. Here, we develop strategies for transferring variational information between related Hamiltonians to accelerate quantum simulations. For Hamiltonians of the same embedded size, optimized variational parameters are transferred between related calculations. For different sizes, we introduce Augmented Ansatz Reuse for Target Initialization (AARTI), which transfers compatible Pauli-generator structure and optimized source parameters, then augments the ansatz with target-specific generators. Our workflow combines density functional theory, Wannier downfolding, embedded tight-binding Hamiltonians, variational quantum algorithms, and neural-network quantum states, with quantum-circuit simulations implemented using NVIDIA's CUDA-Q platform. Using Li$_x$CoO$_2$ as a representative battery cathode material, we study Hamiltonian families spanning multiple delithiation levels, dense $\mathbf{k}$-point meshes, and increasing sizes. Parameter and ansatz transfer substantially reduce the optimization steps required to solve these related Hamiltonians while maintaining the common target accuracy, with lower terminal errors in several cases. The calculated electronic-structure evolution with delithiation exhibits pronounced non-rigid-band behavior consistent with experiment. These results establish a framework for exploiting similarity among related Hamiltonians to improve the efficiency and scalability of quantum workflows for realistic condensed-matter systems.
