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Variational Principles in Quantum Monte Carlo: The Troubled Story of Variance Minimization

机译:Quantum Monte Carlo中的变分原理:方差最小化故事

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We investigate the use of different variational principles in quantum Monte Carlo, namely, energy and variance minimization, prompted by the interest in the robust and accurate estimation of electronic excited states. For two prototypical, challenging molecules, we readily reach the accuracy of the best available reference excitation energies using energy minimization in a state-specific or state-average fashion for states of different or equal symmetry, respectively. On the other hand, in variance minimization, where the use of suitable functionals is expected to target specific states regardless of the symmetry, we encounter severe problems for a variety of wave functions: as the variance converges, the energy drifts away from that of the selected state. This unexpected behavior is sometimes observed even when the target is the ground state and generally prevents the robust estimation of total and excitation energies. We analyze this problem using a very simple wave function and infer that the optimization finds little or no barrier to escape from a local minimum or local plateau, eventually converging to a lower-variance state instead of the target state. For the increasingly complex systems becoming in reach of quantum Monte Carlo simulations, variance minimization with current functionals appears to be an impractical route.
机译:我们调查了量子蒙特卡罗的不同变分原理,即能量和方差最小化的使用,兴趣促进了电子激发态的鲁棒和准确估计的兴趣。对于两个原型,具有挑战性的分子,我们分别使用能量最小化以不同或等于对称的状态的状态或状态平均方式使用能量最小化的最佳可用参考励磁能量的准确性。另一方面,在方差最小化,如果预期使用合适的功能,无论对称如何靶向特定的状态,我们都会遇到各种波函数的严重问题:随着方差收敛,能量远离差异选定的状态。即使目标是地面状态,有时也会观察到这种意外行为,并且通常防止对总和励磁能量的稳健估计。我们使用非常简单的波浪函数分析这个问题,并推断优化发现从局部最小或本地高原逃逸的障碍物很少或没有障碍,最终会聚到下方差状态而不是目标状态。对于越来越复杂的系统进入Quantum Monte Carlo模拟的系统,随着电流功能的差异最小化似乎是一个不切实际的路线。

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