Mathematically-driven algorithms for quantum molecular dynamics

分子中的光诱导动力学在可再生能源技术中起着关键作用，例如用于癌症的光动力学或光动力学疗法。对分子结构演化的精确定量描述是数学和实验上的挑战。现有的实验数据提供了一个有限的图片的动态由于极短的时间尺度和设备的限制。因此，精确的数学模型成为一个重要的补充工具。本研究的目的是开发新的数学模型，提高计算复杂性和准确性之间的权衡。传统的方法往往缺乏数学严谨性，导致不可靠的模拟或仅适用于某些情况。学生将受益于两位领域专家主管的数学和理论化学专业知识。该项目将受益于与来自世界各地的数学家和实验家的密切合作。这将提供实验数据来测试我们的模型的准确性，并作为一个补充的反馈机制，影响我们的研究方向。这项研究有可能对这些方法的开发者和用户产生重大影响，并使我们能够解决包括光捕获绿色能源等领域的重要悬而未决的问题。

Light-induced dynamics in molecules plays a key role in renewable energy technologies such as photovoltaics or photodynamic therapies for cancer. An accurate quantitative description of the evolution of the molecular structure is both a mathematical and experimental challenge. Available experimental data provides a limited picture of the dynamics due to the extremely short time scales and apparatus limitations. Consequently, accurate mathematical models become a crucial complementary tool.The objective of the research is to develop new mathematical models that improve the trade-off between computational complexity and accuracy. Traditional approaches often lack a mathematical rigour leading to unreliable simulations or applicable to only certain instances. The student benefits from the Mathematical and Theoretical Chemistry expertises of two field experts supervisors.The project will benefit from a close collaboration with Mathematicians and experimentalists from across the world. The will provide experimental data to test the accuracy of our models and serve as a complementary feedback mechanism influencing the direction of our research.The research has the potential to have significant impact on developers and users of these approaches, as well as allowing us to tackle important outstanding questions in areas including light-harvesting for green energy.