Resolving Wolf-Rayet Binary Stars Using Tess Photoemetry
Faculty Mentor Name
Noel Richardson
Format Preference
Poster
Abstract
As of September 2024, there are 679 known Wolf-Rayet star systems, and their data have been compiled into an open access catalogue. Inclusion in the catalogue requires spectroscopic confirmation of the properties of WRs for the stars. Many are bright enough to have been observed with the Transiting Exoplanets Survey Satellite (TESS) mission, launched by NASA in 2018. For most of the star systems observed by TESS, not much information has yet been collected regarding their light curves and Fourier transformations. The light curves of a WR binary star system can tell us many things, such as the periodicity and if the system is eclipsing. The project hopes to provide further insight on many of these important attributes of most of these WR star systems so that future astronomers can have more accurate standards for what is typical for a WR system and what is not. After extracting the light curves, a machine learning pipeline will be created, which will attempt to cluster and characterize the stars in many different ways.
Resolving Wolf-Rayet Binary Stars Using Tess Photoemetry
As of September 2024, there are 679 known Wolf-Rayet star systems, and their data have been compiled into an open access catalogue. Inclusion in the catalogue requires spectroscopic confirmation of the properties of WRs for the stars. Many are bright enough to have been observed with the Transiting Exoplanets Survey Satellite (TESS) mission, launched by NASA in 2018. For most of the star systems observed by TESS, not much information has yet been collected regarding their light curves and Fourier transformations. The light curves of a WR binary star system can tell us many things, such as the periodicity and if the system is eclipsing. The project hopes to provide further insight on many of these important attributes of most of these WR star systems so that future astronomers can have more accurate standards for what is typical for a WR system and what is not. After extracting the light curves, a machine learning pipeline will be created, which will attempt to cluster and characterize the stars in many different ways.