Iterative Monte Carlo path integral methods for quantum dynamics

伊利诺伊大学厄巴纳-香槟分校的南希·马克里（Nancy Makri）获得了化学理论，模型和计算方法计划的奖项，用于研究量子簇和液体中动态过程的模拟方法的发展。 这种系统的完全量子力学计算提出了一个重大挑战，因为所需的数值工作量随着系统大小的增加而迅速增加。 Makri和她的研究小组正在开发一种迭代Monte Carlo（IMC）方法，该方法将迭代网格传播算法的精度与大都会Monte Carlo的优势缩放相结合。 从高温和半经典极限激发的晶格表示和网格采样技术的使用将进一步提高效率，同时保持IMC的完全量子力学性质。 IMC方法将首次实现量子团簇、流体和掺杂氦纳米液滴动力学的完全量子力学模拟，提供新的物理见解。 这项工作还将影响更广泛的科学界，为研究人员提供生成评估近似模拟方法所需的基准的能力。 Makri的工作还通过培养研究生和博士后研究人员产生了更广泛的影响。

Nancy Makri of the University of Illinois at Urbana-Champaign is supported by an award from the Chemical Theory, Models and Computational Methods program for research in the development of simulation methods for dynamical processes in quantum clusters and liquids. Fully quantum mechanical calculations of such systems present a major challenge because the numerical effort required increases very rapidly with system size. Makri and her research group are developing an iterative Monte Carlo (IMC) methodology that combines the precision of iterative grid-based propagation algorithms with the advantageous scaling of Metropolis Monte Carlo. The use of lattice representations and grid sampling techniques motivated from the high-temperature and semiclassical limit will further increase efficiency, while maintaining the fully quantum mechanical nature of IMC. The IMC methodology will enable for the first time fully quantum mechanical simulation of the dynamics of quantum clusters, fluids and doped helium nano-droplets, offering new physical insights. The work will also impact a broader scientific community by offering researchers the ability to generate much needed benchmarks for the assessment of approximate simulation methods. Makri's work is also having a further broader impact through the training of graduate students and postdoctoral researchers.