Sneh Pandya
Sneh Pandya
Home Institution
The University of Illinois at Urbana-Champaign
Year Participated
2020
Year in School
Undergraduate
REU Faculty Mentor
Xin Liu
Research Area Interest
Data and Information Systems
Biography & Research Abstract
Abstract:
The goal of this project is to introduce a new, interdisciplinary method in weighing supermassive black holes (SMBH). These SMBH’s are ubiquitously found in the center of galaxies. Also known as quasars, they are actively accreting hot gas and material and are extremely difficult to observe, let alone observe the necessary information to determine mass. There is currently no efficient method in accurately weighing supermassive black holes outside of our galaxy. Developing a catalog of quasar masses is important in understanding large scale structure evolution of galaxies, as well using them as “standard candles” in astronomy. The emergence of astroinformatics and continuous applications of computer science, and most notably deep learning (DL) in astronomy has motivated this project. The goal of this project is to develop an algorithm that weighs SMBH using quasar time series instead of atomic spectra. There are theoretical reasons to believe this relationship between time series data and black hole mass exist, and is pioneered by our mentor Prof. Xin Liu. The theorized non-linearity motivates the use of DL in this project. The questions addressed are whether current methods in DL can be used to make accurate black hole mass predictions of known data sets.
Bio:
I am a rising senior in the Grainger College of Engineering here at Illinois. I've been working with NCSA for a little over a year now, and have enjoyed learning about the endless applications of applied computing in science. On campus I'm a member of Sigma Nu Fraternity and part of the Galaxy and Black Hole Astrophysics Group under Xin Liu. After undergrad I'm hoping to get my Ph.D in Astrophysics or Applied Physics.