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Variable Stars in M31 Stellar Clusters using the Panchromatic Hubble Andromeda Treasury

Presentation #201.02 in the session Star Clusters and Associations — iPoster Session.

Published onJun 29, 2022
Variable Stars in M31 Stellar Clusters using the Panchromatic Hubble Andromeda Treasury

Stellar clusters provide a plethora of knowledge on various topics in astrophysics, including cluster and stellar evolution along with galactic evolution. Studying photometrically variable stars in clusters offers a window into the history of star formation and the nature of the parent cluster. By studying variables in clusters, we can infer ages of clusters based on the relative populations of cluster variables, such as Cepheids and RR lyrae. We can refine constraints on the uncertainties of pulsation models of cluster variables such as the pulsation-driven mass-loss rate to improve the discrepancies between theoretical mass estimates between stellar evolution and pulsation models. Our neighboring Andromeda galaxy (M31) is a wonderful testbed for stellar population studies. There is a long tradition of ground based studies of photometric variability in field stars in M31. However, the extreme crowding in star cluster images at M31’s distance makes it impossible to carry out such studies in ground based seeing and is challenging even with the superior resolution of Hubble Space Telescope (HST) images. We use difference imaging with HST to identify variable stars in star clusters in the disk of M31. This project explores the time domain aspect of the Panchromatic Hubble Andromeda Treasury (PHAT) survey using the visible light filters F475W and F814W, which are roughly equivalent to the Johnson/Cousins B and I bands, respectively. We access PHAT data via the NOIRLab datalab platform. We initially use the per exposure photometry of PHAT to search for stars that show evidence of variability. This allows us to identify 241 cluster variable candidates. To confirm these candidates, we use difference imaging (DI). Our DI pipeline optimizes the positional alignment, the relative photometric scale factor, and PSF shape between the pair of images that are being differenced. Positive and negative residuals that exceed a 10-σ threshold are used to identify variable stars. This difference imaging methodology is applicable to the hundreds of variable candidates in stellar clusters. Color-magnitude diagrams based on six-filter UV/visible light/near IR PHAT photometry is used to constrain the masses and evolutionary phases of cluster variable stars.

This research was funded in part by the NSF and NASA/STScI. JL and PT conducted their research under the auspices of the Science Internship Program (SIP) at the UC Santa Cruz.

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