论文标题
激发态特异性变异蒙特卡洛的优化稳定性
Optimization stability in excited state-specific variational Monte Carlo
论文作者
论文摘要
我们研究了基于方差的特异性变异蒙特卡洛的优化稳定性问题，讨论了目标函数的作用，波函数ANSATZ的复杂性，抽样工作量的数量以及最小化算法的选择。使用小氰染料分子作为测试用例，我们使用线性方法的变体系统地进行最小化，既是独立的算法，又在与加速下降的混合组合中进行最小化。我们证明，在优化复杂的波动函数时，自适应步骤控制对于保持线性方法的稳定性至关重要，并且混合方法既具有更大的稳定性又具有最小化的性能。为了验证方差最小化的实用性，我们报告了氰染料中的激发能，这与基于国家平均能量的基于国家平均能量的变异蒙特卡洛（Monte Carlo）获得的基准量子化学值和结果非常吻合。
We investigate the issue of optimization stability in variance-based state-specific variational Monte Carlo, discussing the roles of the objective function, the complexity of wave function ansatz, the amount of sampling effort, and the choice of minimization algorithm. Using a small cyanine dye molecule as a test case, we systematically perform minimizations using variants of the linear method as both a standalone algorithm and in a hybrid combination with accelerated descent. We demonstrate that adaptive step control is crucial for maintaining the linear method's stability when optimizing complicated wave functions and that the hybrid method enjoys both greater stability and minimization performance. As a verification of variance minimization's practical utility, we report an excitation energy in the cyanine dye that is in good agreement with both benchmark quantum chemistry values and results obtained from state-averaged energy-based variational Monte Carlo.
