Multiple component decomposition from millimeter single-channel data
arXiv:1711.08456 · doi:10.3847/1538-4365/aaa83c
Abstract
We present an implementation of a blind source separation algorithm to remove foregrounds off millimeter surveys made by single-channel instruments. In order to make possible such a decomposition over single-wavelength data: we generate levels of artificial redundancy, then perform a blind decomposition, calibrate the resulting maps, and lastly measure physical information. We simulate the reduction pipeline using mock data: atmospheric fluctuations, extended astrophysical foregrounds, and point-like sources, but we apply the same methodology to the AzTEC/ASTE survey of the Great Observatories Origins Deep Survey-South (GOODS-S). In both applications, our technique robustly decomposes redundant maps into their underlying components, reducing flux bias, improving signal-to-noise, and minimizing information loss. In particular, the GOODS-S survey is decomposed into four independent physical components, one of them is the already known map of point sources, two are atmospheric and systematic foregrounds, and the fourth component is an extended emission that can be interpreted as the confusion background of faint sources.
Accepted in ApJS
References in corpus (7)
- AzTEC Millimetre Survey of the COSMOS Field: I. Data Reduction and Source Catalogue
- The AzTEC mm-Wavelength Camera
- ALMA Census of Faint 1.2 mm Sources Down to ~0.02 mJy: Extragalactic Background Light and Dust-Poor High-z Galaxies
- The NIKA2 instrument, a dual-band kilopixel KID array for millimetric astronomy
- Deep LMT/AzTEC millimeter observations of Epsilon Eridani and its surroundings
- Bayesian semi-blind component separation for foreground removal in interferometric 21-cm observations
- A blind method to detrend instrumental systematics in exoplanetary light-curves