Quantum Monte Carlo in QM/MM

William a.小莱斯特加州大学伯克利分校的研究开发了一种混合量子蒙特卡罗（QMC）分子力学（MM）方法，并获得了理论和计算化学计划的奖励。 这种新的计算技术有望提供研究大型生物分子系统所需的可扩展性。 在这项工作中，化学上重要的活性区域，如活性位点，是由扩散蒙特卡罗方法建模，而周围的经典使用分子力学建模。 莱斯特和他的团队正在开发易于并行化的算法，以利用计算能力有望提高到千万亿次的优势。这项工作对其他科学领域产生了更广泛的影响，并通过莱斯特与杰克逊州立大学等一些历史黑人学院和大学（HBCU）的学生和教师的广泛合作，并通过他与全国黑人化学家和化学工程师促进组织（NOBCChE）的工作。 此外，在这项研究中开发的软件将可从PI的网站下载，进一步扩大研究界的使用。

William A. Lester, Jr. of the University of California Berkeley is supported by an award from the Theoretical and Computational Chemistry program for research to develp a hybrid quantum Monte Carlo (QMC) molecular mechanics (MM) method. This new computational technique is expected to provide the scalability needed to study large biomolecular systems. In this work, the chemically important active region, such as the active site, is modeled by a diffusion Monte Carlo method while the surroundings are modeled classically using molecular mechanics. Lester and his group are developing algorithms that are easily parallelizable to take advantage of the expected increase in computing power to petascale levels.The work is having a broader impact both on other areas of science and through Lester's extensive collaborations with students and faculty at a number of Historically Black Colleges and Universities (HBCUs) such as Jackson State University, and through his work with the National Organization for the Advancement of Black Chemists and Chemical Engineers (NOBCChE). In addition, the software developed in this research will be available for downloading from the PI's website, further broadening its use by the research community.