MULTI-SCALE CLEAN: A COMPARISON OF ITS PERFORMANCE AGAINST CLASSICAL CLEAN ON GALAXIES USING THINGS
- Research School of Astronomy and Astrophysics, Australian National University, Cotter Road, Weston Creek, ACT 2611 (Australia)
- Australia Telescope National Facility, P.O. Box 76, Epping NSW 1710 (Australia)
- Center for Astrophysics Research, University of Hertfordshire, College Lane Hatfield, AL10 9AB (United Kingdom)
- Max-Planck-Institut fuer Astronomie, Koenigstuhl 17, 69117 Heidelberg (Germany)
- Institute of Astronomy, University of Cambridge, Madingley Road, Cambridge CB3 0HA (United Kingdom)
A practical evaluation of the multi-scale CLEAN algorithm is presented. The data used in the comparisons are taken from The H I Nearby Galaxy Survey. The implementation of multi-scale CLEAN in the CASA software package is used, although comparisons are made against the very similar multi-resolution CLEAN algorithm implemented in AIPS. Both are compared against the classical CLEAN algorithm (as implemented in AIPS). The results of this comparison show that several of the well-known characteristics and issues of using classical CLEAN are significantly lessened (or eliminated completely) when using the multi-scale CLEAN algorithm. Importantly, multi-scale CLEAN significantly reduces the effects of the clean 'bowl' that is caused by missing short-spacings, and the 'pedestal' of low-level un-cleaned flux (which affects flux scales and resolution). Multi-scale CLEAN can clean down to the noise level without the divergence suffered by classical CLEAN. We discuss practical applications of the added contrast provided by multi-scale CLEAN using two selected astronomical examples: H I holes in the interstellar medium and anomalous gas structures outside the main galactic disk.
- OSTI ID:
- 21583087
- Journal Information:
- Astronomical Journal (New York, N.Y. Online), Vol. 136, Issue 6; Other Information: DOI: 10.1088/0004-6256/136/6/2897; ISSN 1538-3881
- Country of Publication:
- United States
- Language:
- English
Similar Records
Collaborative Research: Advancing Arctic Climate Projection Capability at Seasonal to Decadal Scales (Final Technical Report)
Systematic Assessment of Terrestrial Biogeochemistry in Coupled Climate-Carbon Models