Astroseminar - Cam Morgan, Darshak Patel and Alice Chen - IN PERSON

Wednesday, May 15, 2024 11:30 am - 12:30 pm EDT (GMT -04:00)

Cam Morgan

Title:Decoding quenching in the Virgo cluster and infalling groups with spatially resolved star formation

Abstract: The Virgo cluster presents a unique opportunity to disentangle the roles of environmental quenching mechanisms such as ram-pressure stripping and starvation given its proximity and ongoing formation. By combining spatially resolved Hα and optical imaging from the Virgo Environmental Survey Tracing Ionised Gas Emission (VESTIGE) and the Next Generation Virgo Survey (NGVS) we are able to study the morphology of star forming regions in galaxies across the entire Virgo cluster region in unprecedented detail. Our results show how a combination of non-parametric morphology indicators with physically motivated techniques for measuring disk sizes and burstiness in star forming regions helps to observationally constrain ram-pressure stripping and starvation. Using toy models of these quenching mechanisms to reproduce observed trends, we find that a ‘delay-then-rapid’ or ‘slow-then-rapid’ quenching model best explains the evolutionary sequence of galaxies in the main Virgo cluster, where starvation is important early on and ram-pressure stripping ‘finishes the job.’ In addition, we find that pre-processing in smaller group structures prior to infall is a vitally important aspect that must be included to understand quenching in clusters. By comprehensively decoding the evolutionary sequences of galaxies in dense environments in the local universe, we are providing key insights for studies of galaxy evolution at high redshift with upcoming instruments such as the Roman space telescope and CASTOR.

Darshak Patel

Title: Early UNIONS Results: Dependence of Halo Mass on Galaxy Size at Fixed Stellar Mass, Colour, and Redshift

Abstract: It is often assumed that there is a tight correlation between the stellar mass and the dark-matter-dominated halo mass of galaxies. There is , however, significant scatter in this relation, which implies that galaxy formation physics is not completely understood. We investigate the dependence of halo mass on galaxy size at fixed stellar mass, redshift and colour using weak gravitational lensing. The analysis done in our work, compared to those done previously, utilizes the much larger surveys: DESI Legacy Survey for the foreground lens galaxies and the Ultraviolet Near Infrared Optical Northern Survey (UNIONS) for the background “source” galaxies. Using galaxy-galaxy lensing measurements to obtain excess surface mass density profiles, we find significant evidence of a dependence of halo mass on galaxy size, at fixed stellar mass, redshift, and colour. We will present these findings and discuss galaxy formation models that can explain them.

Alice Chen

Title: Predicting Halo Location on Non-linear Scales using Galaxies and Neighbouring Halos

Abstract: Many astronomical objects in our universe are too faint to be directly detectable even by the most advanced telescopes. An obvious example is dark matter, but can also extend to low luminosity dwarf galaxies, rogue planets, white dwarfs, neutron stars, and black holes.  While their faintness make these objects difficult to observe, their locations are highly important when studying astrophysical phenomena - one recent and well publicized case is the location of mergers of binary compact objects, detected by gravitational waves, a.k.a. dark sirens, that can be used to measure the Hubble constant.  As a result, here, we use a machine learning algorithm known as symbolic regression to model dark object positions as a function of their separation distances to their closest two “bright” neighbours, and the distances of the bright objects between each other. The objects we use in our analysis include galaxies and halos - we investigate whether or not it is possible to locate other dark objects depending on their vicinity to bright ones. We find that symbolic regression can model a probability density function to predict object positions - this function depends on separation distances for objects in Illustris(-TNG) galaxy formation simulations. This could potentially open the avenue for finding dark objects based on direct observables.