STAMPS@CMU presents:

Discovering Exoplanets With Hermite-Gaussian Linear Regression

by Parker Holzer (Department of Statistics & Data Science, Yale University)

Online webinar September 11, 2020 at 1:30-2:30 PM EDT.
For connection information, join our mailing list here.

One growing focus in modern astronomy is the discovery of exoplanets through the radial velocity (or Doppler) method. This method aims to detect an oscillation in the motion of distant stars, indicating the presence of orbiting planetary companions. Since the radial velocity imposed on a star by an planetary companion is small, however, such a signal is often difficult to detect. By assuming the relative radial velocity is small and using Hermite-Gaussian functions, we show that the problem of detecting the signal of exoplanets can be formulated as simple (weighted) linear regression. We also demonstrate the new Hermite-Gaussian Radial Velocity (HGRV) method on recently collected data for the star 51 Pegasi. In this demonstration, as well as in simulation studies, the HGRV approach is found to outperform the traditional cross-correlation function approach.


I am a current Ph.D. student in the Department of Statistics & Data Science at Yale University. I got my undergraduate at the University of Utah as a double-major in Mathematics and Applied Physics. My research primarily centers on applying statistics to astronomy, with a current focus on exoplanet detection. I am married with a 1-year-old son and another son expected in January.