Abstract

Mergers play an important role in the formation and evolution of galaxies by triggering starbursts, AGN activity, and morphological transitions from disks to ellipticals. They can also cause morphological disturbances in a galaxy’s appearance, such as double nuclei, tidal tails, and other asymmetries, which can appear before or after a merger has occurred. Therefore, one way to identify low redshift galaxy mergers is to search for these morphological signatures via quantitative morphological parameters, which quantify a galaxy’s light distribution (such as Sérsic profiles, or the CAS system, G and M20, and the MID statistics). However, for high redshift galaxies, these parameters can be affected by biases due to poor resolution and noisy images. The upcoming James Webb Space Telescope (JWST) will be able to probe higher redshifts than ever before for morphological studies with high spatial resolution. The Cosmic Evolution Early Release Science (CEERS) Survey will use JWST’s near-infrared camera to reveal detailed galaxy morphologies over a wide range of redshifts. In preparation for CEERS images, this works seeks to understand how well those common morphological statistics will be able to identify JWST mergers.

Multiwavelength Sérsic profile fitting program Galapagos-2 and the nonparametric morphology program statmorph were run on simulated JWST images from Illustris, which were modified to match the specifications of CEERS imaging. Using Illustris merger history catalogs, plots of different combinations of the rest-frame morphologies of the simulated galaxies, binned by redshift, were made as functions of merger timescales. These plots do not separate mergers from non-mergers as cleanly as previous studies have found, regardless of redshift or merger timescale. This indicates that a more sophisticated analysis method, such as principal component analysis, will be required in order to effectively isolate JWST mergers from other galaxies.

Library of Congress Subject Headings

James Webb Space Telescope (Spacecraft)--Computer simulation; Galaxy mergers--Identification; Image processing--Digital techniques; Optical pattern recognition

Publication Date

7-31-2019

Document Type

Thesis

Student Type

Graduate

Degree Name

Astrophysical Sciences and Technology (MS)

Department, Program, or Center

School of Physics and Astronomy (COS)

Advisor

Jeyhan Kartaltepe

Advisor/Committee Member

Andrew Robinson

Advisor/Committee Member

Joel Kastner

Campus

RIT – Main Campus

Plan Codes

ASTP-MS

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