Automatic identification of outliers in Hubble Space Telescope galaxy images
ABSTRACT Rare extragalactic objects can carry substantial information about the past, present, and future universe. Given the size of astronomical data bases in the information era, it can be assumed that very many outlier galaxies are included in existing and future astronomical data bases. However, manual search for these objects is impractical due to the required labour, and therefore the ability to detect such objects largely depends on computer algorithms. This paper describes an unsupervised machine learning algorithm for automatic detection of outlier galaxy images, and its application to several Hubble Space Telescope fields. The algorithm does not require training, and therefore is not dependent on the preparation of clean training sets. The application of the algorithm to a large collection of galaxies detected a variety of outlier galaxy images. The algorithm is not perfect in the sense that not all objects detected by the algorithm are indeed considered outliers, but it reduces the data set by two orders of magnitude to allow practical manual identification. The catalogue contains 147 objects that would be very difficult to identify without using automation.
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Award ID(s):
Publication Date:
NSF-PAR ID:
10268485
Journal Name:
Monthly Notices of the Royal Astronomical Society
Volume:
501
Issue:
4
Page Range or eLocation-ID:
5229 to 5238
ISSN:
0035-8711
This paper aims to quantify how the lowest halo mass that can be detected with galaxy-galaxy strong gravitational lensing depends on the quality of the observations and the characteristics of the observed lens systems. Using simulated data, we measure the lowest detectable NFW mass at each location of the lens plane, in the form of detailed sensitivity maps. In summary, we find that: (i) the lowest detectable mass Mlow decreases linearly as the signal-to-noise ratio (SNR) increases and the sensitive area is larger when we decrease the noise; (ii) a moderate increase in angular resolution (0.07″ versus 0.09″) and pixel scale (0.01″ versus 0.04″) improves the sensitivity by on average 0.25 dex in halo mass, with more significant improvement around the most sensitive regions; (iii) the sensitivity to low-mass objects is largest for bright and complex lensed galaxies located inside the caustic curves and lensed into larger Einstein rings (i.e rE ≥ 1.0″). We find that for the sensitive mock images considered in this work, the minimum mass that we can detect at the redshift of the lens lies between 1.5 × 108 and $3\times 10^{9}\, \mathrm{M}_{\odot }$. We derive analytic relations between Mlow, the SNR and resolution and discuss themore »