The advent of chirped-pulse Fourier transform microwave spectroscopy has dramatically increased the acquisition rate of high-resolution data. However, this data is only useful when it can be translated into molecule-specific information, and ultimately chemical knowledge. To adapt to this high data rate regime, new data analysis tools, which do not result in commensurate increases in time, are needed. Several methods, both computational and experimental, have been developed to simplify and automate the assignment of microwave spectra, and such tools can also make microwave spectroscopy far more approachable and usable for non-experts. Computationally efficient spectral assignment is a particularly promising avenue to enable rapid and nearly exhaustive spectral identification. Towards this end, we have recently developed an efficient, high-speed program for the prediction and fitting of rotational spectra. This program is built on a simple framework that is applicable to a wide variety of molecules. We present this program, discuss its performance, and demonstrate its use in fitting broadband spectra at centimeter wavelengths.

chi脉冲傅立叶变换微波光谱技术的出现极大地提高了高分辨率数据的采集率。但是，只有在可以将其转换为分子特有的信息以及最终转化为化学知识时，此数据才有用。为了适应这种高数据速率机制，需要新的数据分析工具，它们不会导致相应的时间增加。已经开发了几种方法，包括计算方法和实验方法，以简化和自动分配微波光谱，并且这种工具还可以使微波光谱学变得更加平易近人，并且对于非专家而言也可以使用。计算有效的频谱分配是实现快速，几乎详尽的频谱识别的特别有前途的途径。为此，我们最近开发了一种高效，用于预测和拟合旋转光谱的高速程序。该程序建立在适用于多种分子的简单框架上。我们介绍该程序，讨论其性能，并演示其在厘米波长处适合宽带光谱的用途。