PAMS Seminar: "Identifying Large-scale Structures Using Dust-obscured Galaxies (DOGs) as Signposts 9-10 Billion Light-years Away" by Ripon Saha

Ripon Saha
Department of Physics & Astronomy
University of Missouri-Kansas City

Mr. Saha is a PhD student at UMKC.

Note! This seminar has been moved to Zoom. See the PAMS Seminar page for link.

Abstract:
Galaxy clusters are the most massive collapsed structures in the universe. During cluster formation, the largest aggregation of gas, galaxies, and dark matter passes through an intermediate phase called the protocluster. Over the past decades, many studies have identified distant clusters and protoclusters due to advanced observational strategies. However, the protocluster-to-cluster transformation is still unclear, mainly due to the lack of large samples of early-stage clusters and late-stage protoclusters. Our research has identified a large selection of nearly 300 galaxy cluster candidates at redshift 1.3 < z < 1.8 (9-10 billion light-years away) during the formation epoch of the galaxy clusters. The candidates are identified using a sample of Ultra-Luminous Infrared Galaxies called the Dust-Obscured Galaxies (DOGs) as signposts in the Spitzer Deep Wide-Field Survey (SDWFS) in Boötes. A two-point correlation function analysis demonstrates that the sample has a mass scale of the galaxy clusters. Using a more multi-wavelength SDWFS catalog, this study has also uncovered a supercluster structure at z = 1.75 (10 billion light-years away). This supercluster is a bound structure hosting dozens of clusters of galaxies, including the most massive galaxy cluster (IDCS J1426.5+3508) found to date at z > 1.5. Finally, we develop and implement a novel machine learning technique to determine the photometric redshift (photo-z) of the distant galaxies using a TensorFlow-based deep learning network. The results will ultimately be used by a cluster-search project called the Massive and Distant Clusters of WISE Survey-II (MaDCoWS-II).

Free