Thank you very much everyone for your immense help on classifying all the subjects in this project! We will now analyze and share with you our exciting results soon!
Research
Galaxy Merging is a process in which two or more galaxies in the nearby vicinity interact due to gravitational forces and collide with each other to form a single, more massive system. See: A video of merging galaxies by ESA/NASA.
Galaxy mergers have a dramatic impact on the properties of the galaxies involved such as helping build the most-massive galaxies in the universe (such as the elliptical galaxy below). They are also thought to help a galaxy experience an intense "burst" of new star production (as in the "starburst" galaxy below) and provide fuel for the supermassive black holes at the center of galaxies (such as the active galactic nucleus below).
(image credits: Wikipedia, NASA/ESA).
The stage of merging can help us study specific changes to the galaxy properties. A common way that researchers have used is to measure the distance between two galaxy centers as a proxy for merger stage (see image below). However, such an approach requires that the redshift to both galaxies be known (which is not always the case) and situations when the two galaxies are very close to merging can be missed. An alternative approach is to use the disturbed morphological signatures (also called tidal features) as a proxy for merger staging.
Figure from Patton et al. 2013 showing the enhancement in new star production in galaxy-galaxy pairs as a function of distance to each other. The closer their separation is, the greater their star production is compared to individual galaxies.
Several of the characteristics of galaxies are useful to understand their formation and histories. These include star formation rates, stellar masses, and interstellar gas properties. One powerful tool for probing these key characteristics is the analysis of galaxy spectra, which can reveal key information about a galaxy. With this project, we will explore how galaxy mergers at different stages of interaction impact the various properties of galaxies. Modern surveys, such as the Sloan Digital Sky Survey (SDSS), have collected spectral data from hundreds of thousands of galaxies. In this project, we used a machine learning model that was trained using galaxy morphology classifications from the Galaxy Zoo project to help pre-select SDSS galaxies that are highly likely to be merging. Now, we need to get information about the stage the merger is in to better understand how galaxy interactions shape galaxy properties.
This project will result in a public catalog of SDSS galaxies with spectra classified by merger stage. Ultimately, this catalog will allow astronomers to recover crucial information on the magnitude of the changes galaxies go through during mergers, and on the overall timescales during which the properties of galaxies are altered by a merger. This will enable a comprehensive picture of the way galaxy mergers have shaped the galaxies we see today.