Automatic Inspection of Radio Astronomical Surveys (AIRAS)
Abstract
This research investigates the problem of analyzing radio astronomical surveys (RAS) to automatically identify groups of objects forming patterns that astronomers are interested to find. The visual inspection of RAS to find these interesting patterns requires a lot of time and effort to go through thousands of images in RAS. Moreover, the visual process can be infeasible in very crowded and noisy images. To tackle this problem, this research presents AIRAS: the first reported system for the automatic inspection of RAS.
AIRAS consists of two main stages; (i) STAGE 1: Object finding where all objects in RAS are found and presented in a graph-based representation called the astronomy graph (AG), and (ii) STAGE 2: Pattern querying and retrieval where astronomers specify the characteristics of interesting patterns in a query form. Afterwards, AIRAS finds patterns matching these characteristics in the AG and presents them to astronomers for further investigation.
Astronomers can use AIRAS to detect patterns known to be suspicious (i.e. they consist of false astronomical objects or artifacts). Among these patterns are the hexagonal pattern (HP) and the zigzag pattern (ZP). In the HP, objects form a hexagon shape with an object in the middle, similar to the shape of the front end of the Arecibo telescope horn. In the ZP, objects are aligned in an orientation with the horizontal axis similar to the scanning line of the radio telescope. These two patterns are used as case studies to evaluate AIRAS performance using images from the GALFACTS project; a project carried out at the University of Calgary in cooperation with several research institutes worldwide.
The experimental studies show that AIRAS is a promising system that finds patterns in
RAS in response to astronomers’ queries with an acceptable accuracy. Additionally, AIRAS can be extended to connect the patterns found with their physical signals to provide more insights about the nature of these patterns.
Description
Keywords
Astronomy and Astrophysics, Computer Science
Citation
Said, D. A. (2016). Automatic Inspection of Radio Astronomical Surveys (AIRAS) (Doctoral thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca. doi:10.11575/PRISM/25082