Data Quality Analysis (DQA) for astronomical infrared maps and spectra acquired by NASAs Spitzer Space Telescope is one of the important functions performed in routine science operations at the Spitzer Science Center of the California Institute of Technology. A DQA software system has been implemented to display, analyze and grade Spitzer science data. This supports the project requirement that the science data be verified after calibration and before archiving and subsequent release to the astronomical community. This research paper briefly describes the automated pipeline data processing, the subsequent data quality analysis operations, and the software tools and infrastructure that support DQA operations.
In this paper the California Institute of Technology studies a broader class of paraunitary matrices, namely, the Distributed Antipodal Paraunitary (DAPU) matrices, of which Antipodal paraunitary (APU) matrices are special cases. Systematic methods for recursively generating certain types of DAPU matrices as well as a fast algorithm to implement them in a system are presented. Simulation results show that under the same distribution length, DAPU precoded systems with longer precoders have a better Bit Error Rate (BER) performance than those with APU precoders, especially in mid- and high-SNR region.