CRUSH: fast and scalable data reduction for imaging arrays

摘要

CRUSH is an approach to data analysis under noise interference, developed specifically for submillimeter imagingarrays. The method uses an iterated sequence of statistical estimators to separate source and noise signals. Itsfiltering properties are well-characterized and easily adjusted to preference. Implementations are well-suitedfor parallel processing and its computing requirements scale linearly with data size — rendering it an attractiveapproach for reducing the data volumes from future large arrays.