Untangling Variables in Gaia DR3 Público

Abstract

Although the GAIA database is an incredibly useful tool to assess baseline variability, the low and uneven cadence across different Gaia sectors makes it very difficult to distinguish between objects with similar lightcurve features. Using previously verified W. Ursa Majoris and RRc Lyra stars, we develop a classification pipeline using minima depth variation in the lightcurve to distinguish between genuine RR Lyrae and eclipsing binaries. We assess a set of 72 variables with poor or incomplete lightcurves in Gaia using TESS archival data, and identify 12 objects as genuine RR Lyrae based on their minima variation and secondary lightcurve features. We further verify the lightcurves of three variables using observational data from the Emory observatory, reinforcing the efficacy of our classification pipeline.

Table of Contents

Chapter 1: Background ------------1

I: RRc Lyrae ------------2

II: W. Ursa Majoris Eclipsing Binaries ------------3

III: Astronomical Databases and Previous Research ------------5

Gaia

TESS

Combining Gaia and TESS for Time Domain Photometry

Chapter 2: Initial Classification and TESS Analysis ------------8

I: Identification of Candidates ------------8

II: The Lightkurve Pipeline ------------8

Data Reduction and Cleaning

Minima Classification

Chapter 3: Observational Studies ------------24

I: Identification of Candidates ------------24

II: Data Collection ------------25

III: Calibration ------------26

IV: Processing ------------28

VI: Visualization and Analysis ------------29

LAMOST J073756.25+311646.5

ASAS J074316+1705

LAMOST/ATO J106.1517+08.6631

Chapter 4: Discussion and Future Research ------------38

References ------------41

Tables ------------43

Figures ------------50

Appendix 1: Smoothing Lightcurve Data ------------52

Appendix 2: The Lightkurve RRc Pipeline ------------56

Appendix 3: PLD Correction ------------58

About this Honors Thesis

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School	Emory College
Department	Physics
Degree	B.S.
Submission	Honors Thesis
Language	English
Research Field	Physics, Astronomy and Astrophysics
Palavra-chave	RR Lyrae Classification Eclipsing Binary Star RR Lyra Variable
Committee Chair / Thesis Advisor	Dr. Alissa Bans, Emory University
Committee Members	Dr. Merida Batiste, Emory University Dr. Erin Bonning, Emory University

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