Abstract Details

Name: Akriti Sinha
Affiliation: Indian Institute of Technology
Conference ID: ASI2020_340
Title : Multi-wavelength Study of Radio Deep Field: ELAIS N1
Authors and Co-Authors : Akriti Sinha, Arnab Chakraborty, Abhirup Datta
Abstract Type : Oral
Abstract Category : Extragalactic Astronomy
Abstract : Deep radio observations of the extragalactic sky are a powerful means to probe the properties of diverse source populations over a variety of environments to high redshift. Understanding low-frequency sky in depth is also crucial to model the extragalactic foregrounds to detect redshifted HI signal. At low-frequency, radio emission is also important for galaxy population studies, as the synchrotron emission is a clear indicator of activity for both star-forming galaxies (SFGs) and active galactic nuclei (AGN). Here, we have extensively studied the ELAIS N1 field using uGMRT at 300-500 MHz. This covers 1.8 sq. deg part of the sky with the central off-source rms of 15 microJy/beam. We present a radio source catalog consisting of 2528 sources and the Euclidian-normalized differential source counts using those sources. The differential source counts show a flattening below ~1mJy, which is attributed to increased population of star-forming galaxies and radio-quiet AGNs. We have also classified the sources as RL AGNs, RQ AGNs and SFGs using multi-wavelength diagnostics. We use radio and X-ray luminosity, optical spectroscopy, mid-infrared colors, and 24 micrometre and IR to radio flux ratios to search for the presence of an AGN. We study the correlation between star formation rates estimated from radio and IR luminosities for RQ AGNs and SFGs both to look for the contribution of radio emission from star-forming regions in RQ AGNs. We study the spectral properties of sources using high- and low-frequency radio catalogs of the field. We classify the sources as flat, peaked, upturned and inverted spectrum sources by plotting radio color-color plot. We also study the correlation between the spectral index and redshifts. This work demonstrates the improved capabilities of uGMRT.