The evolution of galaxy morphology from redshift z=6 to 3: Mock JWST observations of galaxies in the ASTRID simulation - Patrick LaChance; Rupert Croft; Yueying Ni; Nianyi Chen; Tiziana Di Matteo; Simeon Bird (The Open Journal of Astrophysics)
We present mock JWST observations for more than 250,000 different galaxies from the Astrid simulation with $3 ≤ z ≤ 6$. The mock observations are made using the BPASS stellar SED model, and a simple dust model. They are then viewed through NIRCam filters, convolved with a PSF, have noise added, and are drizzled together to emulate the Cosmic Evolution Early Release Science (CEERS) survey. We analyse this dataset by computing a number of morphological measures and find our catalog to have comparable statistics to similar mock catalogs, and the first release of CEERS data. We find that most of the Sersic indices of galaxies in our redshift range are lower than observed, with most having n less than one. Additionally, we observe the sizes of galaxies of all masses to increase from redshift z=6 to redshift z=3 consistent with other results. The number of galaxies in our catalog allows us to examine how relationships like the mass-size relation evolve with redshift, and compare the accuracy of a variety of traditional galaxy classification techniques (Sersic fit, Asymmetry-Concentration, and Gini-$M_{20}$) within our redshift range. We find the mass-size relation to be nearly flat at redshift z=6, and consistently increases as redshift decreases, and find the galaxy classification methods have minimal correlation with each other in our redshift range. We also investigate the impact that different stages of our imaging pipeline have on these morphological measures to determine how robust mock catalogs are to different choices at each step. Finally, we test the addition of incorporating light from AGNs into our pipeline and find that while the population of galaxies that have significant AGN luminosity is low, those galaxies do tend to have higher Sersic indices once the AGN luminosity is added, rectifying some of the systematic bias towards lower Sersic indices present in our dataset.