Advanced quantum chemical methods for strong correlation and beyond

先进的量子化学方法可实现强相关性及其他功能

• 批准号: 1650436
• 负责人: Garnet Chan
• 金额: $ 4.87万
• 依托单位: California Institute of Technology
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-07-01 至 2017-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1650436&HistoricalAwards=false
• 关键词: Advanced; quantum; chemical; methods; strong

Garnet Chan of Princeton University is supported by the Chemical Theory, Models and Computational Methods program in the Chemistry division to develop new quantum chemical methods for "hard" problems in quantum chemistry. The main directions of the research are (1) extending the density matrix renormalization group and related methodologies to tackle the electronic structure of multi-centre transition metal sites as found in bioinorganic systems, (2) developing new approaches to strong correlation based on higher dimensional tensor networks, and (3) exploring the use of correlated wavefunction methodologies for problems of quantum spin dynamics in electron spin and nuclear magnetic resonance.Beyond the dissemination of science, algorithms, and code associated with this research, the broader impacts of this proposal are focused on the development of educational modules for quantum mechanics through the NETLOGO environment, and the establishment of an online "Ask a Scientist" resource for chemistry and other sciences.

普林斯顿大学的Garnet Chan得到了化学系化学理论，模型和计算方法项目的支持，为量子化学中的“困难”问题开发新的量子化学方法。 研究的主要方向是：（1）扩展密度矩阵重整化群和相关方法，以解决生物无机体系中发现的多中心过渡金属位点的电子结构，（2）开发基于高维张量网络的强相关新方法，以及（3）探索用关联波函数方法解决电子自旋和核磁共振中的量子自旋动力学问题。除了传播科学，算法，和与这项研究相关的代码，这项建议的更广泛的影响集中在通过NETWORK环境开发量子力学的教育模块，并建立一个在线的“问科学家”化学和其他科学资源。