Frequentist and Bayesian approaches to spectral line detection in astronomy

3237 

Contributed Abstract 

Poster 

Alexander Kuhn (1), Bonnabelle Zabelle (1), Sara Algeri (1), Galin Jones (1), Claudia Scarlata (1)

(1) University of Minnesota, Minneapolis, MN

Bonnabelle Zabelle  
University of Minnesota

Sara Algeri  
University of Minnesota

Galin Jones  
University of Minnesota

Claudia Scarlata  
University of Minnesota

Alexander Kuhn  
University of Minnesota

Alexander Kuhn  
N/A

The problem of detecting spectral lines is ubiquitous in several areas of astronomy, as they enable measurements of fundamental physical properties of astronomical objects such as distances, chemical compositions, and temperature. In the near future, the Euclid satellite will provide spectra from millions of galaxies for which distances need to be measured from emission lines (a specific kind of spectral line). Current approaches to detect spectral lines in the astronomy literature often lack the ability to control for the inflation of the probability of false discovery due to searching over multiple regions of the spectrum – a statistical phenomenon also referred to in high-energy physics as "the look-elsewhere effect". This project applies existing (frequentist) solutions that handle the look-elsewhere effect to the problem of detecting and identifying a single spectral line. Moreover, we propose a new Bayesian solution to address this problem, and provide a comparison of both procedures through simulation studies to assess their validity and usefulness.

Look-elsewhere effect|Bayesian methods|Astrostatistics | | |

Astrostatistics Interest Group

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