Abstract We present a framework for using linear programming to solve a challenging problem in surface science, the elucidation of the structure and composition of adsorbed molecules from a mixture, using simulated data from polarized Raman experiments. In the past, methods applied in order to interpret such spectroscopic information were combinatorial approaches that are limited in scalability or accuracy. Quantum mechanical electronic structure calculations yield the optical response of a single molecule, from which spectra of a mixture can be determined by appropriate weighting. Furthermore, spectral obtained in different beam polarizations provide projections of the signal in the laboratory frame. We demonstrate that linear programming is an ideal tool for utilizing all of this information in order to provide the sought structural picture.

中文翻译：

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线性规划应用于偏振拉曼光谱以阐明表面分子结构

摘要 我们提出了一个框架，用于使用线性规划来解决表面科学中的一个具有挑战性的问题，即使用极化拉曼实验的模拟数据阐明混合物中吸附分子的结构和组成。过去，用于解释此类光谱信息的方法是在可扩展性或准确性方面受到限制的组合方法。量子力学电子结构计算产生单个分子的光学响应，从中可以通过适当的加权确定混合物的光谱。此外，在不同光束偏振中获得的光谱提供了实验室框架中信号的投影。我们证明线性规划是利用所有这些信息以提供所寻求的结构图的理想工具。