DATE:

Friday, June 25, 2021

TIME:

3:30 PM

LOCATION:

Virtual Zoom Conference

SPEAKER:

Matthew Portman, PhD Candidate, Computational Science, San Diego State University

ABSTRACT:

Spiral galaxies, including our own Milky Way, comprise about 70% of galaxies observed in the local universe yet the formation of the characteristic arms and their visible structure are not fully understood beyond strict formalisms developed to describe their dynamics. Our work aims to provide objective, quantitative measures of their structure in order to provide further insight into their morphology due in part to the wide variety of spiral structures observed. To do this, we use Spiral Arc Finder and Reporter (SpArcFiRe), a computer vision algorithm which takes images of spiral galaxies and automatically extracts simple objective information about their structure and GALFIT, a parametric fitting algorithm which fits a multi-component light model to the observations fed in to automate the process. This approach allows us the flexibility to generalize the fitting procedure by focusing our approach on modeling features common to all spiral galaxies. In this talk, I will present the developments made towards automating this process as well as the methods we have examined to perform error detection and reduction at scale. I will furthermore discuss preliminary results from the first automated run performed on observations from the Sloan Digital Sky Survey and future work which must be done to ensure the efficacy of the algorithm at scale.

HOST:

Abraham Flores and the SDSU SIAM Student Chapter

VIDEO: