Is this project an undergraduate, graduate, or faculty project?
Undergraduate
Project Type
group
Campus
Daytona Beach
Authors' Class Standing
Cassandra McGinley, Freshman Dr. Mariel Lares, Faculty Dr. Terry Oswalt, Faculty Dr. Derek Buzasi, Faculty
Lead Presenter's Name
Cassandra McGinley
Lead Presenter's College
DB College of Arts and Sciences
Faculty Mentor Name
Mariel Lares-Martiz
Abstract
The main goal of Gyrochronology is to determine stellar ages by understanding how stars slow down in their rotation as they age. In order to achieve such a goal, rotation periods must be determined with high precision. Various tools are available for determining stellar rotation periods, such as the AutoCorrelation Function (ACF), Lomb Scargle periodograms, or Classical Wavelet analysis. However, each method has strengths and weaknesses when applied to determining stellar rotation rates. One weakness of Classical Wavelet analysis is the relatively low precision with which periods are determined. A new algorithm for wavelet analysis, called Synchrosqueezing Wavelet Transform (SWT), claims to deliver more precise periods than the classical analysis. This poster presents the results of computing classical and SWT wavelet analysis rotation periods for a sample of 3912 stars that are components of wide binary systems. So far, the SWT results show a significant improvement in the precision of rotational periods, as expected. The SWT algorithm is likely to become part of the Gyrochronology team's pipeline for stellar rotation period determinations.
Support from NSF grants AST-1910396, AST-2108975 and NASA grants 80NSSC22K0622, 80NSSC21K0245, and NNX16AB76G is gratefully acknowledged.
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?
Yes, Collaborative Grant
Detecting Stellar Rotation with the Synchrosqueezing Wavelet Transform
The main goal of Gyrochronology is to determine stellar ages by understanding how stars slow down in their rotation as they age. In order to achieve such a goal, rotation periods must be determined with high precision. Various tools are available for determining stellar rotation periods, such as the AutoCorrelation Function (ACF), Lomb Scargle periodograms, or Classical Wavelet analysis. However, each method has strengths and weaknesses when applied to determining stellar rotation rates. One weakness of Classical Wavelet analysis is the relatively low precision with which periods are determined. A new algorithm for wavelet analysis, called Synchrosqueezing Wavelet Transform (SWT), claims to deliver more precise periods than the classical analysis. This poster presents the results of computing classical and SWT wavelet analysis rotation periods for a sample of 3912 stars that are components of wide binary systems. So far, the SWT results show a significant improvement in the precision of rotational periods, as expected. The SWT algorithm is likely to become part of the Gyrochronology team's pipeline for stellar rotation period determinations.
Support from NSF grants AST-1910396, AST-2108975 and NASA grants 80NSSC22K0622, 80NSSC21K0245, and NNX16AB76G is gratefully acknowledged.