Uncovering Mechanism in Closed Loop Molecular Learning

这个研究项目的重点是了解如何将强的、形状的超快激光脉冲用作光子试剂来控制基本的化学反应，如单分子解离。在无法先验计算最佳脉冲形状的情况下，实验利用学习算法来发现控制分子碎片的最佳形状激光脉冲。通过将最佳脉冲形状与从头算分子结构计算相结合，并仔细选择分子碎片作为脉冲形状函数的研究，有可能揭示控制的基本物理机制。这些努力的最终目标是在这些实验中利用对控制机制的理解，将学习控制发展成为一种有用的光谱工具，用于难以进入的分子相空间区域，并提高控制的范围和程度，从而使控制的有用应用（例如区分不同的化学物质和控制双分子反应化学）变得可行。该计划的更广泛影响包括研究生和本科生水平的学生培训，以及与当地高中的联系。该项目由数学和物理科学理事会物理系和化学系共同资助。

This research project focuses on the understanding of how intense, shaped ultrafast laser pulses can be used as photonic reagents for controlling basic chemical reactions such as unimolecular dissociation. The experiments make use of a learning algorithm to discover optimal shaped laser pulses for controlling molecular fragmentation in situations where it is impossible to calculate optimal pulse shapes a priori. By combining the optimal pulse shapes with ab initio molecular structure calculations and carefully chosen studies of the molecular fragmentation as a function of pulse shape, it is possible to uncover the basic physical mechanisms underlying control. The ultimate goals of the efforts are to use the understanding of control mechanisms in these experiments to develop learning control into a useful spectroscopic tool for hard to access regions of molecular phase space, and to improve the range and degree of control such that useful applications of control (such as discriminating between different chemical species and controlling bimolecular reaction chemistry) are viable. The broader impact of the program involves student training at both the graduate and undergraduate levels as well as outreach to the local high school.This project is jointly funded by the Division of Physics and the Division of Chemistry in the Mathematical and Physical Sciences Directorate.