Van Benschoten William Z, Shepherd James J
Department of Chemistry, University of Iowa, Iowa City, Iowa 52242, USA.
J Chem Phys. 2022 May 14;156(18):184107. doi: 10.1063/5.0094290.
The density matrix quantum Monte Carlo (DMQMC) set of methods stochastically samples the exact N-body density matrix for interacting electrons at finite temperature. We introduce a simple modification to the interaction picture DMQMC (IP-DMQMC) method that overcomes the limitation of only sampling one inverse temperature point at a time, instead allowing for the sampling of a temperature range within a single calculation, thereby reducing the computational cost. At the target inverse temperature, instead of ending the simulation, we incorporate a change of picture away from the interaction picture. The resulting equations of motion have piecewise functions and use the interaction picture in the first phase of a simulation, followed by the application of the Bloch equation once the target inverse temperature is reached. We find that the performance of this method is similar to or better than the DMQMC and IP-DMQMC algorithms in a variety of molecular test systems.
密度矩阵量子蒙特卡罗（DMQMC）方法集在有限温度下对相互作用电子的精确N体密度矩阵进行随机抽样。我们对相互作用绘景DMQMC（IP-DMQMC）方法进行了简单修改，克服了一次仅抽样一个逆温度点的限制，而是允许在单次计算中对一个温度范围进行抽样，从而降低了计算成本。在目标逆温度下，我们不是结束模拟，而是引入一种远离相互作用绘景的绘景变换。由此产生的运动方程具有分段函数，并在模拟的第一阶段使用相互作用绘景，一旦达到目标逆温度，便应用布洛赫方程。我们发现，在各种分子测试系统中，该方法的性能与DMQMC和IP-DMQMC算法相当或更优。
