Calibrating Quasars for Cosmology

Drexel University, Philadelphia PA

Investigators

Abstract

Cosmology can be described as the study of the history, future, structure, and geometry of the Universe and is a foundation of astronomical research. Astronomers' current best understanding of cosmology comes from using a certain type of exploding stars (supernovae) to "map" the Universe. However, a fundamental tenet of science is that results should be tested and confirmed with independent methods. This investigation thus seeks to determine if another type of astronomical object can be used to test current theories. These objects are black holes that lurk in the cores of all massive galaxies, some of which are actively "feeding" today and are called "quasars". Ultimately the goal is to attempt to determine if a sub-class of quasars can be used in the same way as supernovae to map the geometry of the universe. In this process a graduate student will be trained in modern data science methods and both the student and PI will support education and public outreach, through activities involving Drexel's Lynch Observatory, engaging with elementary and middle-school classrooms, and actively working to increase inclusion and diversity at both Drexel University and in the science community in general. This project has potential for advancing science because known quasars vastly outnumber the supernovae that are currently the foundation of cosmology and the quasars "live" longer in addition to having been discovered across cosmic time. What one might hope to learn from them would provide independent constraints on existing methods. This project will undertake a novel method for leveraging machine learning to improve and expand upon the use of quasars for cosmology. The work involves calibrating two relationships that can be applied to up to 500,000 known quasars and can be accomplished using existing public data from the Sloan Digital Sky Survey. The project is designed as a 1-year high-risk, high potential reward exploratory investigation that the proposing team is uniquely positioned to carry out. The results of this investigation will be broadly distributed, by making code and data products available not only through the science literature, but also common data-sharing platforms and outreach activities. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.