Ab Initio molecular Dynamics with Quantum Nuclear Effects: Potential Surfaces and Gradients from on-the-fly Graph-Theory-Based Molecular Fragmentation Methods

具有量子核效应的从头算分子动力学：基于动态图论的分子断裂方法的势表面和梯度

• 批准号: 2102610
• 负责人: Srinivasan Iyengar
• 金额: $ 45万
• 依托单位: Indiana University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-06-01 至 2025-05-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2102610&HistoricalAwards=false
• 关键词: Ab; Initio; molecular; Dynamics; Quantum

Srinivasan S. Iyengar of Indiana University is supported by an award from the Chemical Theory, Models and Computational Methods program in the Division of Chemistry. Many problems at the forefront of energy, environmental and biological research demand the quantum mechanical treatment of electrons and nuclei, but the detailed quantum-mechanical description of such problems is much too complex even in today’s high performance computing environments. This is because the computational complexity in these problems grows exponentially with system size, which makes them intractable. Iyengar and his research group are developing new computational methods to address these issues. These methods are based on a mathematical idea called graph-theory that allows Iyengar and co-workers to partition a molecular system into regions that communicate through an idea called electron correlation. This is very similar to Google maps, where cities are connected through highways, and in the same way, in Iyengar’s formalism molecular domains are connected through similar roads and bridges that provide pathways for electrons to communicate through a concept called electron correlation. Unfortunately, while electron correlation allows electrons to communicate and has a critical role in all chemical processes, this concept is also responsible for the catastrophic computational complexity of obtaining accurate molecular properties. By creating such graph-theoretic methods, Iyengar will help to reduce the computational complexity of these problems, to allow state of art calculations. These methods are poised to have major impact on the study of a wide class of problems in fields ranging from enzymology to atmospheric chemistry to materials science, including the study of hydrogen transfer in polymer electrolyte fuel cells. In addition, the methods are also poised to allow innovative implementations on a mixed set of hybrid quantum and classical computing systems. The methods being developed by Iyengar are at the intersection of modern computational quantum chemistry and chemical physics. Hence students in the group have the opportunity to learn and develop new theoretical methods and apply these methods to important problems. The results, involving computer codes as well as novel scientific ideas are to be disseminated to the scientific community. Specifically, the computer programs developed by Iyengar will appear as part of the NSF-funded SEAGrid science gateway. Furthermore, as a member of the quantum science center at Indiana University, and as the director of the university-wide scientific computing program, Iyengar will be involved in the organization of summer workshops for middle- and high-school teachers from the local Bloomington, Indiana area to provide cross-disciplinary training in chemistry, physics and computer science. These workshops will focus on the quantum nature of matter, providing a unified treatment of problems in physics, chemistry and biochemistry; furthermore, modeling these problems is then to be done through connections to computational algorithms. Through involvement in the Holland Hudson Scholars Program (HHSP) and the Indiana Louis Stokes Alliance for Minority Participation (LSAMP) program, the PI will work to recruit students from under-represented groups. Ab initio molecular dynamics (AIMD) is appealing, since it does not need a priori fitted potentials. This allows application of AIMD as a self-contained black box. But this advantage is deeply affected by the cost of evaluating the electronic potential and forces. Hence, most applications of AIMD are limited to density functional theoretic (DFT) treatment. While there has been substantial progress in developing accurate DFT functionals, fundamental challenges remain. This proposal deals with the development and application of on-the-fly graph-theoretic techniques to compute accurate, low-scaling AIMD trajectories that are in agreement with post-Hartree-Fock electronic structure, but at the cost of DFT. These developments are applicable for both cluster studies as well as periodic condensed phase problems, such as reactions on surfaces. In addition, during a single AIMD step, the approach can integrate multiple electronic structure packages. Current capabilities include the ability to use Gaussian, ORCA, Psi4, Quantum Espresso and OpenMX within a single AIMD umbrella. There are three specific aims in this proposal: (1) to implement the team's graph theory-based approach in an asynchronous fashion on novel hybrid, interleaved, quantum/classical computing hardware. This will allow the steep scaling aspects of our method to be treated on quantum hardware, the lower scaling aspects and graph-theoretic decomposition of molecular structure on classical hardware and provide a new thrust for studying reactive chemical problems; (2) to study hydrogen transfer reactions on the surface of water. The systems studied are in the condensed phase, and of critical importance in atmospheric chemistry. The reactions considered deal with isoprene-based hydroxy-peroxy radicals, thought to be pivotal on hydroxyl radical concentrations in the atmosphere. (3) The graph theory-based approach will be used to construct multi-dimensional potential surfaces for hydrogen-transfer reactions to gauge quantum nuclear effects.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.

印第安纳大学的 Srinivasan S. Iyengar 获得了化学系化学理论、模型和计算方法项目的奖项支持。能源、环境和生物研究前沿的许多问题需要对电子和原子核进行量子力学处理，但即使在当今的高性能计算环境中，此类问题的详细量子力学描述也过于复杂。这是因为这些问题的计算复杂性随着系统规模的增加呈指数增长，这使得它们变得棘手。艾扬格和他的研究小组正在开发新的计算方法来解决这些问题。这些方法基于一种称为图论的数学思想，该思想允许艾扬格和同事将分子系统划分为通过称为电子关联的思想进行通信的区域。这与谷歌地图非常相似，其中城市通过高速公路连接起来，同样，在艾扬格的形式主义中，分子域通过类似的道路和桥梁连接起来，这些道路和桥梁为电子通过电子关联的概念进行通信提供了路径。不幸的是，虽然电子关联允许电子通信并在所有化学过程中发挥关键作用，但这个概念也导致了获得准确分子特性的灾难性计算复杂性。通过创建此类图论方法，艾扬格将有助于降低这些问题的计算复杂性，从而实现最先进的计算。这些方法将对从酶学到大气化学再到材料科学等领域的一系列问题的研究产生重大影响，包括聚合物电解质燃料电池中氢转移的研究。此外，这些方法还准备允许在混合量子和经典计算系统的混合集上进行创新实现。艾扬格正在开发的方法处于现代计算量子化学和化学物理学的交叉点。因此，小组中的学生有机会学习和发展新的理论方法，并将这些方法应用于重要问题。涉及计算机代码以及新颖的科学思想的结果将向科学界传播。具体来说，艾扬格开发的计算机程序将作为 NSF 资助的 SEAGrid 科学网关的一部分出现。此外，作为印第安纳大学量子科学中心的成员以及全校科学计算项目的负责人，艾扬格将参与为印第安纳州布卢明顿当地初高中教师组织暑期研讨会，提供化学、物理和计算机科学的跨学科培训。这些研讨会将重点关注物质的量子本质，提供物理、化学和生物化学问题的统一处理；此外，这些问题的建模将通过与计算算法的连接来完成。通过参与荷兰哈德逊学者计划 (HHSP) 和印第安纳路易斯斯托克斯少数族裔参与联盟 (LSAMP) 计划，PI 将致力于从代表性不足的群体中招收学生。从头算分子动力学（AIMD）很有吸引力，因为它不需要先验拟合势。这允许 AIMD 作为独立的黑匣子应用。但这种优势深受评估电子势和力的成本的影响。因此，AIMD 的大多数应用仅限于密度泛函理论（DFT）处理。尽管在开发精确的 DFT 泛函方面取得了实质性进展，但根本性的挑战仍然存在。该提案涉及动态图论技术的开发和应用，以计算精确的、低尺度的 AIMD 轨迹，这些轨迹与 Hartree-Fock 后的电子结构一致，但以 DFT 为代价。这些进展既适用于簇研究，也适用于周期性凝聚相问题，例如表面反应。此外，在单个 AIMD 步骤中，该方法可以集成多个电子结构封装。当前的功能包括能够在单个 AIMD 保护伞中使用 Gaussian、ORCA、Psi4、Quantum Espresso 和 OpenMX。该提案有三个具体目标：（1）在新颖的混合、交错、量子/经典计算硬件上以异步方式实现团队基于图论的方法。这将使我们的方法的陡峭尺度方面能够在量子硬件上得到处理，较低尺度方面以及分子结构的图论分解能够在经典硬件上得到处理，并为研究反应化学问题提供新的推动力； (2)研究水表面氢转移反应。研究的系统处于凝聚相，在大气化学中至关重要。所考虑的反应涉及基于异戊二烯的羟基过氧自由基，该反应被认为对大气中的羟基自由基浓度至关重要。 (3) 基于图论的方法将用于构建氢转移反应的多维势面，以测量量子核效应。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，认为值得支持。

项目成果

Analogy between Boltzmann Machines and Feynman Path Integrals

• DOI: 10.1021/acs.jctc.3c00187
• 发表时间: 2023-04-26
• 期刊: JOURNAL OF CHEMICAL THEORY AND COMPUTATION
• 影响因子: 5.5
• 作者: Iyengar, Srinivasan S.;Kais, Sabre
• 通讯作者: Kais, Sabre

Quantum Computing with Dartboards

使用飞镖进行量子计算

• DOI: 10.1021/acs.jpca.3c04262
• 发表时间: 2023
• 期刊: The Journal of Physical Chemistry A
• 作者: Ganti, Ishaan;Iyengar, Srinivasan S.
• 通讯作者: Iyengar, Srinivasan S.