Is this project an undergraduate, graduate, or faculty project?
Undergraduate
Project Type
group
Campus
Daytona Beach
Authors' Class Standing
Luca Guida, Senior Ryan Reynolds, Senior
Lead Presenter's Name
Luca Guida
Lead Presenter's College
DB College of Arts and Sciences
Faculty Mentor Name
Mariel Lares Martiz
Abstract
Gyrochronology postulates that the age of stars similar in mass to our Sun can be approximated based on their rotational period. With this in mind, determining accurate rotation periods using photometry data from missions such as Kepler, K2, and TESS is vital for accurate stellar age estimates. Blended light curves pose a particular problem: When conducting simple aperture photometry, neighboring targets can taint the resulting light curve. In most cases, this issue makes the data unusable for unambiguous determination of stellar rotation periods. In this poster, we outline our research project, which aims to provide a solution to the issue of blended light curves. The project consists of computing a grid of simulated blended light curves and comparing them to observed blended photometric data from Kepler, K2, and TESS. Simulations will be computed using Butterpy, a Python package that yields the light curve of a particular model of starspots evolving through the stellar surface. We expect to quantitatively match any simulation from the grid to any of the blended light curves in our sample. Success in the project results will significantly impact other fields of astronomy that also use photometric data by facilitating a new collection of previously unusable data.
Did this research project receive funding support (Spark, SURF, Research Abroad, Student Internal Grants, Collaborative, Climbing, or Ignite Grants) from the Office of Undergraduate Research?
No
Comparative study of simulated and observed blended light curves for unambiguous stellar rotation period determinations
Gyrochronology postulates that the age of stars similar in mass to our Sun can be approximated based on their rotational period. With this in mind, determining accurate rotation periods using photometry data from missions such as Kepler, K2, and TESS is vital for accurate stellar age estimates. Blended light curves pose a particular problem: When conducting simple aperture photometry, neighboring targets can taint the resulting light curve. In most cases, this issue makes the data unusable for unambiguous determination of stellar rotation periods. In this poster, we outline our research project, which aims to provide a solution to the issue of blended light curves. The project consists of computing a grid of simulated blended light curves and comparing them to observed blended photometric data from Kepler, K2, and TESS. Simulations will be computed using Butterpy, a Python package that yields the light curve of a particular model of starspots evolving through the stellar surface. We expect to quantitatively match any simulation from the grid to any of the blended light curves in our sample. Success in the project results will significantly impact other fields of astronomy that also use photometric data by facilitating a new collection of previously unusable data.