CAFQA：一种用于变分量子算法的经典模拟引导方法
CAFQA: A classical simulation bootstrap for variational quantum algorithms
AI总结：
本文提出 CAFQA，通过经典模拟与 Bayesian Optimization 搜索仅含 Clifford 门的高精度 VQA 初始化，在分子 VQE 中显著提升精度、恢复相关能并加速收敛。
摘要：
本工作解决为变分量子算法（VQA）寻找良好 ansatz 初始化的问题，提出了 CAFQA，即 Clifford Ansatz For Quantum Accuracy。CAFQA ansatz 是一种仅由 Clifford 门构建的硬件高效电路。在该 ansatz 中，可调门的参数通过经典模拟在 Clifford 参数空间中进行高效搜索来选择。所得初始状态始终等同或优于传统经典初始化（例如 Hartree-Fock），并能够实现高精度 VQA 估计。CAFQA 非常适合经典计算，因为：a）仅含 Clifford 的量子电路可以在多项式时间内被经典精确模拟；b）离散 Clifford 空间可通过 Bayesian Optimization 高效搜索。对于分子基态能量估计（最多 18 个量子比特）的 Variational Quantum Eigensolver（VQE）任务，CAFQA 的 Clifford Ansatz 实现了接近 99% 的平均精度，并恢复了 Hartree-Fock 初始化中损失的分子相关能的最高 99.99%。在不同指标上，CAFQA 相比最先进方法实现了 6.4 倍和 56.8 倍的平均精度提升。该方法的可扩展性使得对具有挑战性的铬二聚体（Cr₂）分子进行初步基态能量估计成为可能。借助 CAFQA 的高精度初始化，即使对于小分子，VQA 的收敛也显示出 2.5 倍的加速。此外，对在 CAFQA 框架中允许有限数量非 Clifford（T）门的初步探索表明，在仅含 Clifford 的 CAFQA 精度相对受限的键长处，可以恢复多达 99.9% 的相关能，同时仍保持可经典模拟性。
英文摘要：
This work tackles the problem of finding a good ansatz initialization for Variational Quantum Algorithms (VQAs), by proposing CAFQA, a Clifford Ansatz For Quantum Accuracy. The CAFQA ansatz is a hardware-efficient circuit built with only Clifford gates. In this ansatz, the parameters for the tunable gates are chosen by searching efficiently through the Clifford parameter space via classical simulation. The resulting initial states always equal or outperform traditional classical initialization (e.g., Hartree-Fock), and enable high-accuracy VQA estimations. CAFQA is well-suited to classical computation because: a) Clifford-only quantum circuits can be exactly simulated classically in polynomial time, and b) the discrete Clifford space is searched efficiently via Bayesian Optimization. For the Variational Quantum Eigensolver (VQE) task of molecular ground state energy estimation (up to 18 qubits), CAFQA's Clifford Ansatz achieves a mean accuracy of nearly 99% and recovers as much as 99.99% of the molecular correlation energy that is lost in Hartree-Fock initialization. CAFQA achieves mean accuracy improvements of 6.4x and 56.8x, over the state-of-the-art, on different metrics. The scalability of the approach allows for preliminary ground state energy estimation of the challenging chromium dimer (Cr$_2$) molecule. With CAFQA's high-accuracy initialization, the convergence of VQAs is shown to accelerate by 2.5x, even for small molecules. Furthermore, preliminary exploration of allowing a limited number of non-Clifford (T) gates in the CAFQA framework, shows that as much as 99.9% of the correlation energy can be recovered at bond lengths for which Clifford-only CAFQA accuracy is relatively limited, while remaining classically simulable.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
