Dynamical Constraints of Galaxy Clusters via Spectroscopic Observations
Kremin, Anthony
2020
Abstract
Galaxy Clusters are the largest gravitationally bound objects in the Universe, residing at the boundary between the expansive push of dark energy in the vacuum and the attractive pull of dark matter the fills the halo in which a cluster resides. By leveraging the power of spectroscopy, I used the three-dimensional information it provides about galaxies within these clusters to infer dynamical properties about the galaxy cluster and the underlying dark matter halo. The dynamical state and dynamic mass inferences are valuable to future cosmological studies that aim to use the unique nature of galaxy clusters and the role they play in constraining the properties of dark energy and dark matter. In this work I focus on transforming galaxy spectra into line-of-sight velocities which, when paired with projected sky locations, allow me to probe the gravitational potential of the total cluster system. I designed, targeted, acquired, reduced, and analyzed 4427 galaxy spectra from 22 galaxy clusters, of which 3054 passed my strict quality cuts. Of those that passed the cuts, 1679 were identified as cluster members based on radial-velocity phase-space cuts. The data was acquired using the Michigan-Magellan Fiber System (M2FS) multi-fiber spectrograph on the 6.5m Magellan Clay telescope. The reductions were performed using a fully-featured pipeline that I created and that I describe in this work. I also summarize the resulting dataset using spatial, redshift, magnitude, and signal-to-noise information for individual galaxies, and show that there is good agreement when comparing my re-observed redshifts with those in the literature. To convey the amount of information contained in this dataset, I perform an analysis on one specifically selected massive cluster, Abell S1063, which was observed twice. I use two approaches for estimating cluster masses, the first is a velocity dispersion technique that takes the distribution of velocities, reduces it to a statistical measure of the width of the distribution, and maps that spread to a mass based on a model motivated in part by theory and calibrated with simulations. The second uses the velocity-radial distance information from the cluster center to identify the escape velocity edge of the cluster, which is observed as the velocity extrema in a given radial bin. This edge is directly related to the gravitational potential and can be used to infer the total mass of the system. I compare these techniques to one another and against other mass proxies and find that the velocity dispersion measurement differs from other estimates for the system, favoring a higher mass, while the escape velocity edge technique is in good agreement with other estimates. This is expected for a galaxy cluster with substructure, which previous studies have hypothesized for this system but could not verify. I am able to visually confirm the existence of clumps using galaxies as tracers, and quantify the substructure using the Dressler-Shectman statistic, where I found a significant result with p< 0.0001.Subjects
galaxy cluster spectroscopy dynamical mass estimate escape velocity edge
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