Strong electron correlations in quantum chemistry: new approaches from machine learning, quantum computing and time-dependent quantum control

量子化学中的强电子相关性：机器学习、量子计算和瞬态量子控制的新方法

• 批准号: RGPIN-2020-04306
• 负责人: DeBaerdemacker, Stijn
• 金额: $ 2.48万
• 依托单位: University of New Brunswick
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=747843
• 关键词: Strong; electron; correlations; quantum; chemistry

The ability to universally solve quantum many-body systems at high accuracy with low computational cost would have unprecedented consequences for human kind, allowing us to design and accurately compute sophisticated molecules with important applications in chemical, bio-medical, and material science on computer chips, rather than in expensive experimental laboratories. While we are not quite there yet, promising techniques are on the horizon to scale up current theoretical methods to more than a few atoms per molecule. In the past five years, the recently relocated quantum chemistry group at the University of New Brunswick (QuNB), and collaborators have proposed a computationally tractable Geminal theory: an electronic structure method for strongly correlated molecules based on the premises of Lewis electron pairs, rather than molecular orbitals. The Geminal project emerged from a fruitful cross fertilization between theoretical chemistry and mathematical/nuclear physics with ideas from integrability and the seniority scheme. Notwithstanding the strong quantum correlations encoded in the Geminal wavefunction ansatz, the method has a good computational scaling, so other research groups are currently investigating it for larger systems. While the mathematical formulation of Geminal theory is currently investigated in the framework of a Tier-2 Canada Research Chair, the present Discovery Grant proposal goes beyond traditional electronic structure methods by embracing newly emerged technologies with disrupting potential to the field. In three Work Packages (WP), we will explore, develop and establish WP1(GemQC): the power of Quantum Computing to design a fully correlated Geminal theory; WP2(ML-DMET): the connection between Machine Learning and Density Matrix Embedding Theory; WP3(e-FMD): Fermionic Molecular Dynamics as an intuitive classical picture of electron bonding and dynamics probed by attosecond laser fields. The proposed research program will provide excellent HQP training opportunities in both hard and soft skills for 3 PhD students, 2 MSc students and several undergraduate students. The hard skills that come with theoretical electronic structure theory are mathematical abstraction and numerical modeling, both skills that are in high demand in academia and industry. The embedding within a CRC research group will allow for high-quality training on important soft skills such as (international) collaboration and independence, with strong respect for Equity Diversity and Inclusion. Canada is a global leader in both the fundamentals and applications of Machine Learning and Quantum Computing, so this research program will enhance Canada's leading position, both by delivering new theoretical methods published in top-tier academic journals, open source (quantum) computer software packages that implement those methods, as the training of HQP in that area.

高精度以低计算成本以高精度解决量子多体系统的能力将对人类产生前所未有的后果，从而使我们能够设计并准确地计算出具有化学，生物医学和材料科学在计算机芯片上的重要应用的精致分子，而不是在昂贵的实验实验室中。虽然我们还没有到达，但有希望的技术即将到来，将当前的理论方法扩展到每个分子的几个原子。 在过去的五年中，新不伦瑞克大学（QUNB）的最近重新定位的量子化学组和合作者提出了一种可计算上的可易处理的双子理论：一种基于Lewis Electron Pairs Pairs的前提，是一种非常相关的分子的电子结构方法比分子轨道。 Geminal项目来自理论化学与数学/核物理学之间的富有成果的交叉施肥，并具有综合性和资历计划的思想。尽管在Geminal波函数ANSATZ中编码的很强的量子相关性，但该方法具有良好的计算缩放，因此其他研究小组目前正在为较大的系统研究它。 尽管目前在加拿大研究主席的框架中研究了Geminal理论的数学表述，但目前的Discovery Grant提案通过拥抱新出现的技术，远远超出了传统的电子结构方法，这些技术破坏了该领域的潜力。在三个工作包（WP）中，我们将探索，开发和建立WP1（GEMQC）：量子计算对设计完全相关的Geminal理论的力量； WP2（ML-DMET）：机器学习与密度矩阵嵌入理论之间的连接； WP3（E-FMD）：费米子分子动力学，作为Attsecond Laser Fields探测的电子键合的直观经典图片。 拟议的研究计划将为3名博士学位学生，2名MSC学生和几名本科生提供精力和软技能的HQP培训机会。理论电子结构理论带来的艰难技能是数学抽象和数值建模，这是学术界和行业需求很高的技能。 CRC研究小组中的嵌入将允许对重要的软技能（例如（国际）协作和独立性）进行高质量的培训，并强烈尊重公平多样性和包容性。 加拿大是机器学习和量子计算的基本原理和应用的全球领导者，因此该研究计划将通过提供在开放源代码（Quantum）计算机软件包中发表的新理论方法来增强加拿大的领先地位。该方法是在该领域对HQP的培训。