New Numerical Solutions for Density Functional Theory

密度泛函理论的新数值解

• 批准号: 7159465
• 负责人: JING KONG
• 金额: $ 32.75万
• 依托单位: Q-CHEM, INC.
• 依托单位国家: 美国
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-03-01 至 2008-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7159465
• 关键词: bacteriorhodopsins; bioenergetics; biophysics; computer simulation; data collection methodology /evaluation; density; mathematical model; model design /development; molecular dynamics; quantum chemistry; statistics /biometry

DESCRIPTION (provided by applicant): First principle (ab initio) quantum chemistry methods are widely used for computational studies in biology, chemistry and material science. Among the various quantum chemistry models, density functional theory (DFT) offers a good balance between computational cost and accuracy and accordingly is the most widely used method in many scientific fields, including biological research. However, despite the remarkable advances in DFT in the past decade, the application of DFT to treat large biological systems or molecular dynamics is still limited by computational cost. Accordingly, the goal of the research proposed here is to increase the efficiency of DFT calculations by several fold through the implementation of novel algorithms. There are two major time-consuming parts in a DFT calculation, namely computation of the Coulomb and the exchange-correlation (XC) contributions. In the Phase I of this project, we implemented the Fourier Transform Coulomb method for the evaluation of the Coulomb contribution, and developed a new algorithm called multiresolution XC (mrXC), for the evaluation of XC contribution to the DFT energy with local functionals. The results show that FTC accelerates Coulomb calculation by up to a factor of 4.5 over the most efficient Coulomb algorithms. The mrXC method speeds up the calculation of XC contribution by as much as a factor of 5. In the Phase II of the project, we will develop and implement FTC and mrXC for the most widely used components of DFT calculations, including energy and gradients with respect to nuclear motions for both ground and excited states. Efforts will also be made to further improve the efficiency. Formulism will also be developed at the level of general-gradient approximation, the mostly widely used type of DFT functional. In order to demonstrate the utility of DFT algorithms developed here, we will carry out a state-of-the-art computational study of the mechanism of light-induced structural change in bacteriorhodopsin. These improvements will significantly increase Q-Chem users? productivity and greatly extend the complexity of molecular systems that can be studied using DFT. Furthermore, it will bring DFT much closer to our goal of being able to replace the less accurate but computationally less demanding models currently used today in molecular dynamics or Monte Carlo simulations of proteins and other large molecular systems. This project aims to improve the efficiency of the density-functional theory (DFT) calculations. DFT is at the core of molecular modeling and is applied widely in biological research/development and in drug discovery. The improved DFT will significantly increase researchers' productivity and extend its application scope.

描述（由申请人提供）：第一原理（从头算）量子化学方法广泛用于生物学、化学和材料科学的计算研究。在各种量子化学模型中，密度泛函理论（DFT）在计算成本和准确性之间提供了良好的平衡，因此是包括生物研究在内的许多科学领域中使用最广泛的方法。然而，尽管DFT在过去十年中取得了显着的进步，但DFT在处理大型生物系统或分子动力学方面的应用仍然受到计算成本的限制。因此，本文提出的研究目标是通过实施新颖算法将 DFT 计算效率提高数倍。 DFT 计算中有两个主要耗时的部分，即库仑贡献和交换相关（XC）贡献的计算。在该项目的第一阶段，我们实现了傅里叶变换库仑法来评估库仑贡献，并开发了一种称为多分辨率XC（mrXC）的新算法，用于评估XC对具有局域泛函的DFT能量的贡献。结果表明，与最高效的库仑算法相比，FTC 将库仑计算速度提高了 4.5 倍。 mrXC 方法将 XC 贡献的计算速度提高了 5 倍。在项目的第二阶段，我们将为 DFT 计算中使用最广泛的组件开发和实现 FTC 和 mrXC，包括能量和梯度尊重基态和激发态的核运动。还将努力进一步提高效率。公式主义也将在一般梯度近似的水平上得到发展，这是最广泛使用的 DFT 泛函类型。为了证明这里开发的 DFT 算法的实用性，我们将对细菌视紫红质光诱导结构变化的机制进行最先进的计算研究。这些改进会显着增加 Q-Chem 用户吗？生产力并极大地扩展了可以使用 DFT 研究的分子系统的复杂性。此外，它将使 DFT 更接近我们的目标，即能够取代目前在分子动力学或蛋白质和其他大型分子系统的蒙特卡罗模拟中使用的精度较低但计算要求较低的模型。该项目旨在提高密度泛函理论（DFT）计算的效率。 DFT 是分子建模的核心，广泛应用于生物研究/开发和药物发现。改进后的DFT将显着提高研究人员的生产力并扩展其应用范围。