I use simulations to study galaxies and how their properties are influenced by their environment. I study galaxies and clusters in the IllustrisTNG simulations and run zoom-in simulations of individual halos using both the TNG and FIRE models.
Galaxies come in a vast range of sizes, colors, and morphologies. These are not distributed randomly through the universe, but it is much more likely to find, for example, red elliptical galaxies in galaxy clusters compared to the blue spiral galaxies that are common in the field. A major factor in the difference between cluster and field galaxies is the cluster environment, which is full of hot gas and has a much higher density of galaxies. However, it is not clear what the exact mechanisms are that cause all these changes and how the environment influences galaxy evolution. It is also not clear when a galaxy is affected by this environment.
Galactic environments and cluster galaxy evolution
An example of a scaling relation that changes for cluster galaxies compared to field galaxies. The stellar-to-halo mass ratio steadily increases with residence time.
I use IllustrisTNG to study how galaxies change as a function of cluster residence time, i.e. how long a galaxy has lived within a cluster. Particularly significant is how this affects commonly used scaling relations. Because we cannot interact directly with galaxies, we rely on calibrated relations between observable quantities like luminosity and quantities of interest like galaxy mass. However, the same relations do not hold for cluster galaxies and field galaxies. I showed that when a galaxy enters a cluster, it continues on an alternative evolutionary pathway compared to field galaxies, and this results in significant and predictable deviations from the standard scaling relations.
I also worked with a student to study how galaxy properties change depending on their proximity to a galaxy cluster. We used machine learning to classify galaxies in TNG-300 as either "cluster" or "field" galaxies and calculated the probability of a galaxy having cluster-like properties as a function of distance from their nearest galaxy cluster. We identified a transition region that varies depending on the type of galaxy property, such as stellar properties, dark matter properties, or dynamical properties. Each set of properties transitions at a different distance and over a broad spatial extent, indicating that different processes are affected differently in the cluster environment.
Splashback boundary measurements in IllustrisTNG
A visual of the dark matter splashback radius, R200,mean, and the splashback radius measured from a population of galaxies. Each point represents a galaxy and the background color corresponds to the density of galaxies.
The size of a dark matter halo is a fundamental property used in a range of studies from cosmology to galaxy evolution to the nature of dark matter. Given the web-like nature of cosmic structure, however, this is not a straightforward quantity to define. The splashback radius describes the boundary of a halo using the orbiting material, specifically the boundary that encloses the first orbits of infalling material. This quantity does not suffer from pseudoevolution like traditional overdensity definitions and reflects the dynamical nature of the halo.
The splashback radius can be measured by identifying the point of steepest slope in the dark matter density profile. A similar feature can be identified observationally using galaxy number density profiles of clusters in galaxy surveys. However, it is unclear how the dark matter measurement and galaxy measurement relate to each other. Cluster galaxies differ from field galaxies since the cluster environment strips them of gas, which quenches their star formation and alters their color. Making splashback measurements with different galaxy populations alters the calculated splashback radius. I use simulations to make splashback measurements with different galaxy populations for the same halos to understand how the measurement changes for different galaxy properties like mass or star formation rate. This allows us to determine the relationship between observational measurements and the underlying dark matter halo and the effect of the galaxy environment on galaxies as well as determine the extent of this environment. I also worked with two students to characterize the depth and width of the splashback feature and how we can use these quantities to probe a halo's history.