Highly efficient time-domain quantum chemistry algorithms

高效时域量子化学算法

• 批准号: EP/J013080/1
• 负责人: Ilya Kuprov
• 金额: $ 3.69万
• 依托单位: University of Oxford
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2011
• 资助国家: 英国
• 起止时间: 2011 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FJ013080%2F1
• 关键词: Highly; efficient; time; domain; quantum

The current state of Theoretical and Computational Chemistry is a paradox -- the fundamental equations governing physical reality in the chemical energy range (1-100 eV) are known completely, yet their exact solutions are in most cases far too complex to be computed: the best we can currently do, even with the largest modern supercomputers, is about the size of the benzene molecule.This basic computational problem is solved using physical approximations: calculating a given property to a given accuracy is often a much simpler task than obtaining the full molecular wavefunction. Computational Chemistry currently employs a large array of such approximations -- from the crudest (molecular dynamics) to medium accuracy (semi-empirics and density functional theory) to high accuracy (configuration interaction and high-order preturbation theory) to extreme precision (full configuration interaction). The primary parameter that makes an approximation computable is known as "scaling": polynomial (ideally linear) scaling makes an approximation computationally acceptable, whereas exponential scaling generally means that further theoretical work is required before meaningful calculations can be performed.This project will enable knowledge transfer between three sub-disciplines of Computational Chemistry -- time-domain electronic structure theory, spin dynamics and density matrix renormalization group (DMRG) -- that will bring some of the exponentially scaling computation stages down to polynomial scaling. Specifically, the latest DMRG algorithms will be adopted for dissipative spin dynamics (Cornell --> Oxford, Edinburgh), the state space restriction algorithms from spin dynamics will be adopted for time-domain electronic structure theory (Oxford, Edinburgh --> Stanford, Bristol) and the tensor factorization algorithms used in electronic structure theory will be applied to spin dynamics (Bristol, Cornell, Cardiff --> Edinburgh, Oxford). The six research groups (two US groups and four UK groups) involved in this project have extensive independent publication records on the subjects listed above, and view the possibility of joining forces on the computational scaling problem as a crucial opportunity in the ongoing effort towards improving the efficiency of Quantum Chemistry algorithms.Faster and more accurate simulation algorithms benefit all application areas of Quantum Chemistry -- computational drug design, biomolecular structure determination, MRI contrast agent design, metabolomics, magnetic resonance and optical spectroscopy, materials chemistry, etc. Our primary objective is to lift the (presently rather low) ceiling of what is possible to accurately compute using Quantum Chemistry techniques.

理论和计算化学的现状是一个悖论--在化学能范围内控制物理现实的基本方程（1-100 eV）是完全已知的，但它们的精确解在大多数情况下太复杂而无法计算：我们目前所能做的最好的，即使是最大的现代超级计算机，这个基本的计算问题是用物理近似法解决的：计算一个给定的性质到给定的精度通常比获得完整的分子波函数要简单得多。计算化学目前采用了大量这样的近似-从最粗糙的（分子动力学）到中等精度（半量子力学和密度泛函理论）到高精度（组态相互作用和高阶扰动理论）到极端精度（全组态相互作用）。使近似可计算的主要参数被称为“缩放”：多项式（理想的线性）标度使得近似值在计算上是可接受的，而指数标度通常意味着在进行有意义的计算之前需要进一步的理论工作。这个项目将使计算化学的三个分支学科之间的知识转移-时域电子结构理论，自旋动力学和密度矩阵重整化群（DMRG）--这将使一些指数级的计算阶段下降到多项式尺度。具体来说，最新的DMRG算法将被采用耗散自旋动力学（Cornell --> Oxford，Edinburgh），时域电子结构理论将采用自旋动力学的状态空间限制算法（牛津、爱丁堡-->斯坦福大学、布里斯托），电子结构理论中使用的张量因子分解算法将应用于自旋动力学（布里斯托、康奈尔、卡迪夫-->爱丁堡、牛津）。六个研究小组参与该项目的两个美国小组和四个英国小组在上述主题上有广泛的独立出版记录，并将在计算缩放问题上联手的可能性视为提高量子化学算法效率的持续努力的关键机会。更快，更准确的模拟算法有利于量子化学的所有应用领域-计算药物设计、生物分子结构测定、MRI造影剂设计、代谢组学、磁共振和光谱学、材料化学等。我们的主要目标是提升（目前相当低的）使用量子化学技术精确计算的可能性上限。

项目成果

A quantum mechanical NMR simulation algorithm for protein-scale spin systems

蛋白质尺度自旋系统的量子力学核磁共振模拟算法

• DOI: 10.48550/arxiv.1402.6139
• 发表时间: 2014
• 作者: Edwards L

Quantum mechanical NMR simulation algorithm for protein-size spin systems

• DOI: 10.1016/j.jmr.2014.04.002
• 发表时间: 2014-06-01
• 期刊: JOURNAL OF MAGNETIC RESONANCE
• 影响因子: 2.2
• 作者: Edwards, Luke J.;Savostyanov, D. V.;Kuprov, Ilya
• 通讯作者: Kuprov, Ilya

Exact NMR simulation of protein-size spin systems using tensor train formalism

使用张量序列形式对蛋白质大小的自旋系统进行精确 NMR 模拟

• DOI: 10.1103/physrevb.90.085139
• 发表时间: 2014
• 期刊: Physical Review B
• 影响因子: 3.7
• 作者: Savostyanov D