Symmetry Projected Coupled Cluster Theory

威廉·马什·赖斯大学的古斯塔沃·斯库里亚得到了化学部化学理论、模型和计算方法计划的支持，该计划旨在为挑战分子开发准确和负担得起的计算方法。感兴趣的系统有几个电子，它们相互影响，导致许多状态具有相似的能量。这种类型的系统被称为“强关联”，可以显示出新的特性，这些特性有可能促进许多领域的技术进步。然而，这些系统在理论上很难描述，而且对于目前的计算方法来说往往很难处理。斯库塞里亚教授的团队正在开发一种新的方法，这种方法是准确的，可以应用于大型、现实的系统，同时为强关联系统提供更好的结果。研究人员正在努力继续开发新的方法，并将该方法应用于过渡金属簇合物和多环芳烃等重要系统，以便为与技术相关的系统提供有用的见解。斯库塞里亚博士参与了休斯顿地区的外展活动。具体地说，他正在与莱斯大学拉丁美洲研究生协会一起组织活动。他就学术界和工业界的就业机会提供非正式的建议。斯库塞里亚博士还参与了大米科学咖啡馆，在那里与普通公众讨论有关科学和技术的想法。强关联无处不在，在技术上也很重要，但不幸的是，除了少数几种计算方法外，无法准确地描述这种关联。处理强相关性的较有前景的方法之一是使用对称投影，即恢复破缺对称波函数的对称性保持分量。对称投影是一个黑箱，对称投影平均场方法可以应用于具有数十个甚至数百个强关联电子的系统。为了达到强关联系统的定量精度，Scueria小组正致力于将他们的对称投影平均场方法扩展到对称投影耦合团簇理论。该理论结合了对称投影描述强关联和耦合团簇理论描述弱关联的优点，成为黑箱多参考耦合团簇理论的一种形式。这种新的方法有可能在平等的基础上有效和可靠地处理弱相关性和强相关性，同时提供属性和其他期望值的直接计算。虽然Scueria小组继续发展和扩展对称投影耦合团簇理论，但他们目前应用的方法是显示自旋受挫和伴随的磁序的强关联系统，这应该为未来的技术发展提供有价值的见解。这一奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

Gustavo Scuseria of William Marsh Rice University is supported by an award from the Chemical Theory, Models and Computational Methods program in the Chemistry Division to develop accurate and affordable computational methods for challenging molecules. The systems of interest have several electrons that influence each other in ways that lead to many states with similar energies. Systems of this type are called "strongly-correlated" and can exhibit novel properties which have the potential to spur technological advancement in a number of fields. However, these systems are challenging to theoretically describe and are often intractable for current computational methods. Professor Scuseria's group is developing a new approach that is accurate and can be applied to large, realistic systems, all the while giving superior results for strongly correlated systems. The researchers are working both to continue to develop the new approach and to apply the method to important systems like transition-metal clusters and polycyclic aromatic hydrocarbons in order to provide useful insights into technologically-relevant systems. Dr. Scuseria is involved in outreach activities in the Houston area. Specifically he is organizing events with the Latin American Graduate Student Association at Rice University. He provides informal advice about job opportunities in academia as well as in industry. Dr. Scuseria is also involved in the Rice Science Cafe, where ideas about science and technology are discussed with the general public. Strong correlations are ubiquitous and technologically important, but unfortunately cannot be accurately described except by a handful of computational approaches. One of the more promising approaches for the treatment of strong correlation is the use of symmetry projection, i.e. recovering the symmetry-preserving component of a broken-symmetry wavefunction. Symmetry projection is black box, and symmetry projected mean-field methods can be applied to systems with dozens or even hundreds of strongly correlated electrons. In order to reach quantitative accuracy for strongly-correlated systems, the Scuseria group is working to extend their symmetry projected mean-field methods to symmetry projected coupled cluster theory. This theory combines the advantages of symmetry projection for the description of strong correlation on the one hand with coupled cluster theory for the description of weak correlation on the other, becoming a form of black-box multireference coupled cluster theory. The new approach has the potential to efficiently and reliably treat weak and strong correlations on equal footing while affording the straightforward computation of properties and other expectation values. While the Scuseria group continues to develop and extend symmetry projected coupled cluster theory, their current applications of the approach are strongly correlated systems which display spin frustration and accompanying magnetic order, which should provide valuable insights for future technological development.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.