RUI: Rapid Acquisition and Analysis of Complex Spectra with High-Speed Digitizers

这项由化学系化学测量和成像(CMI)项目颁发的本科生研究奖，由计算机和数据科学与工程(CDS&Amp；E)和行星天文学项目共同资助，支持佛罗里达新学院的Steven T.Shipman教授和他的学生开发新工具，帮助科学家分析来自行星大气的数据，包括我们自己的和太空中的大分子云。这些新的工具基于高速电子设备，使科学家能够收集比以前更多的关于他们的样本的信息。正在开发的软件利用这些高速数据收集器，并使用新的计算技术来处理涌入的数据。所有的工作都是由本科生和首席调查员一起完成的。新软件将公开共享。研究人员正在使用新的高速数字化仪和网格计算技术，在大约250到325K的温度范围内快速获取和分析与星际和大气化学相关的分子的旋转光谱。在这个温度范围内，由于大幅度运动和热填充激发的振动和构象状态的贡献，旋转光谱极其复杂。一种新的数字化仪的速度比目前的仪器快近8000倍，正在与温度相关测量和微波-微波双共振测量结合使用，以自动确定观测光谱中大量峰的较低态能量和能级连接性。正在开发的基于遗传算法和其他方法的软件将使用这些信息来极大地简化光谱分配过程。这些算法将被移植到网格计算平台上，以最大限度地利用它们的并行性，并进一步减少频谱分析时间。

This Research at Undergraduate Institutions (RUI) award from the Chemical Measurement and Imaging (CMI) Program in the Division of Chemistry, with co-funding from the Computer and Data-Enabled Science and Engineering (CDS&E) and Planetary Astronomy Programs, supports Professor Steven T. Shipman and his students at New College of Florida as they develop new tools that will help scientists analyze data from the atmospheres of planets, including our own and large clouds of molecules in space. The new tools are based on high-speed electronics that allow scientists to collect significantly more information about their samples than was previously possible. Software is being developed that takes advantage of these high-speed data-collectors and uses new computing techniques to process the influx of data. All the work is being performed by undergraduate students working with the principal investigator. The new software will be publicly shared.The investigators are using new high-speed digitizers along with grid computing techniques to rapidly acquire and analyze rotational spectra of molecules of relevance to interstellar and atmospheric chemistry at temperatures ranging from roughly 250 to 325 K. In this temperature range, rotational spectra are extremely complex due to contributions from large amplitude motion and thermally-populated excited vibrational and conformational states. A new digitizer with a nearly 8000x speed advantage over current instrumentation is being used in conjunction with temperature-dependent and microwave-microwave double resonance measurements to automatically determine lower state energies and energy level connectivities of a large number of peaks in observed spectra. Software that is being developed, based on genetic algorithms and other approaches, will use this information to greatly ease the spectral assignment process. These algorithms will be ported to a grid computing platform to take maximum advantage of their parallelism and to further reduce the spectral analysis time.