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CAREER: Tensor Factorization Methods for High-Level Electronic Structure Theory

职业：高级电子结构理论的张量分解方法

基本信息

批准号：
2143725
负责人：
Devin Matthews
金额：
$ 65万
依托单位：
Southern Methodist University
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2022
资助国家：
美国
起止时间：
2022-02-01 至 2027-01-31
项目状态：
未结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2143725&HistoricalAwards=false
关键词：
CAREER Tensor Factorization Methods Level

项目摘要

With support from the Chemical Theory, Models and Computational Methods program in the Division of Chemistry, Devin Matthews of Southern Methodist University will endeavor to advance the development of complex quantum chemical Couple Cluster methods to enable practitioners of theory to model with very high accuracy much larger molecular systems than has been possible heretofore. Novel state-of-the-art algorithms and GPU (Graphics Processing Unit)-implementations will enable these high-accuracy predictions of parameters such as molecular heats of formation, reaction barrier heights, bond dissociation, ionization, and electron attachment energies. These developments will have a widespread impact on chemical modelling and reliable benchmarks, e.g. through hierarchical reaction models and the Active Thermochemical Tables. The new “model chemistry” developed by Dr. Matthews and his group has the potential to impact a wide range of problems, including the development of novel renewable fuels, a better understanding of our effects on the atmosphere and our environment, and the formation of complex biological molecules in space and other harsh environments which led to the origins of life. The Matthews group will also endeavor to improve awareness of and diversity in theoretical and computational chemistry by directly involving undergraduates and high school students in cutting-edge research and incorporating computational chemistry into the undergraduate physical chemistry curriculum. The Matthews group will also implement an interactive “knowledge web” spanning diverse topics in quantum chemistry and related fields. This “Wikipedia for Quantum Chemistry” will help to improve and accelerate training of graduate students in the field as well as interested non-scientists.Dr. Matthews and his group will be working on enabling highly accurate coupled cluster calculations on larger molecules by developing reduced-scaling approximations of CCSDT (Coupled Cluster Single-Double-Triple) theory methods and CCSDT(Q), as well as analytic gradients thereof. Graph-based techniques and knowledge-based algorithmic search through the Design-by-Transformation methodology will be used to produce optimal working equations, and a high-quality implementation will be produced by utilizing automated code generation that targets high-level tensor contraction interfaces for CPUs (Central Processing Units) and potentially GPUs. To this will be added further optimizations such as coarse-grained parallelism, blocking, and loop fusion. The efficacy of this implementation in terms of computational efficiency, scaling, absolute and relative error characteristics, and error cancellation will be leveraged to create a new model chemistry suitable for accurate thermochemistry (at the ~1kJ/mol scale) of molecules with as many as 12 first- or second-row atoms. The Matthews group will developing this new protocol to study substituted Criegee intermediates and possible water-catalysis of Criegee decomposition as well as oxygenated fuel combustion intermediates relevant to renewable fuel development. Dr. Matthews’s group will also work to achieve a more diverse student base in theoretical and computational chemistry by directly involving undergraduates and high school students from diverse backgrounds in cutting-edge research and incorporating computational chemistry into the undergraduate physical chemistry curriculum.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

在化学系化学理论、模型和计算方法项目的支持下，南卫理公会大学的Devin Matthews将努力推进复杂量子化学偶对簇方法的发展，使理论从业者能够以非常高的精度模拟比迄今为止可能的更大的分子系统。新的先进算法和GPU（图形处理单元）实现将使这些参数的高精度预测成为可能，如分子形成热、反应势垒高度、键解离、电离和电子附着能。这些发展将对化学建模和可靠基准产生广泛影响，例如通过分层反应模型和活性热化学表。马修斯博士和他的团队开发的新“模型化学”有可能影响广泛的问题，包括开发新型可再生燃料，更好地了解我们对大气和环境的影响，以及在太空和其他导致生命起源的恶劣环境中形成复杂生物分子。马修斯小组还将通过直接让本科生和高中生参与前沿研究，并将计算化学纳入本科物理化学课程，努力提高理论和计算化学的认识和多样性。马修斯小组还将实施一个互动的“知识网络”，涵盖量子化学和相关领域的各种主题。这个“量子化学维基百科”将有助于提高和加快对该领域研究生以及感兴趣的非科学家的培训。Matthews和他的团队将通过开发CCSDT（耦合簇单-双-三）理论方法和CCSDT(Q)的减尺度近似，以及其分析梯度，致力于在大分子上实现高精度的耦合簇计算。基于图形的技术和基于知识的算法搜索将通过转换设计方法来产生最佳的工作方程，并通过利用针对cpu（中央处理单元）和潜在gpu的高级张量收缩接口的自动代码生成来产生高质量的实现。在此基础上还将添加进一步的优化，如粗粒度并行性、阻塞和循环融合。这种实现在计算效率、缩放、绝对和相对误差特性以及误差消除方面的有效性将被用来创建一种新的化学模型，适用于具有多达12个第一排或第二排原子的分子的精确热化学（在~1kJ/mol尺度下）。Matthews小组将开发这一新方案，以研究取代的Criegee中间体和可能的Criegee分解水催化以及与可再生燃料开发相关的含氧燃料燃烧中间体。马修斯博士的小组还将通过直接让来自不同背景的本科生和高中生参与前沿研究，并将计算化学纳入本科物理化学课程，努力使理论和计算化学的学生基础更加多样化。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。