Tidally Excited Oscillations in Heartbeat Stars

I took part in the Summer Undergraduate Research Fellowships (SURF) program at the California Institute of Technology during the summer after my junior year, and continued my project throughout the Fall of my senior year. I worked with Prof. Jim Fuller at the Theoretical Astrophysics Including Relativity and Cosmology (TAPIR) group on characterizing tidally excited oscillations (TEOs) in heartbeat stars.

Heartbeat stars are a class of eccentric binary stars with light curves exhibiting a "heartbeat" signal resembling an EKG, and TEOs cause many heartbeat stars to oscillate throughout their orbits. We characterize 3 Kepler heartbeat stars (KIC 6117415, KIC 11494130, and KIC 5790807) by first creating a binary model of each system using a Markov Chain Monte Carlo algorithm emcee and a binary modeling package ellc. We account for the effects of gravity darkening, limb darkening, doppler boosting, and reflection in our models. To study the TEOs in these stars, we first perform a frequency analysis to identify observed TEOs and then determine the theoretical magnitude and frequency of TEOs predicted by dynamic tidal theory (chance resonance) following Fuller (2017). To aid in our theoretical predictions, we employ the MESA stellar evolution code and the GYRE stellar oscillation code. For cases where high amplitude observed TEOs cannot be accounted for by chance resonance, we explore whether a resonance locked mode can offer an explanation. Our work was published in Cheng, S., Fuller, J., Guo, Z., Lehman, H., & Hambleton, K. (2020). Detailed Characterization of Heartbeat Stars and their Tidally Excited Oscillations ApJ, 903(2), 122.

 
Light curve of heartbeat star KIC 11494130, showing tidally excited oscillations. This plot is from Cheng et al. 2020.

Light curve of heartbeat star KIC 11494130, showing tidally excited oscillations. This plot is from Cheng et al. 2020.

 
 

Dynamics of multi-body systems

Throughout my sophomore and junior years at UCLA, I worked with Prof. Smadar Naoz on studying the dynamical evolution of the binary M-dwarf star Parengo (Par) 1802 in the presence of a third companion. Par 1802 exhibits an unexpected temperature difference in its otherwise physically identical (to within 3%) stars, and we suggested that this temperature difference may be caused by the presence of a third star. We studied the three-body dynamical evolution of the system using the hierarchical three-body secular approximation up to the octupole-level of approximation, known as the Eccentric Kozai Lidov mechanism. We included pre-main sequence evolution, general relativistic precession, and tidal dissipation in our numerical Monte Carlo simulations. We predicted the orbital configuration of the third companion star and suggested that tight twin binaries with a significant temperature difference are a generic feature of secular interaction in hierarchical triple body systems. This work was published in Cheng, S., Vinson, A., & Naoz, S. (2019). Interacting young M-dwarfs in triple system - Par 1802 binary system case study MNRAS, 489(2), 2298-2306.

A plot from Cheng et al. 2019 showing a triple system in which the third star causes the stars in Par 1802 to cross their Roche limit and exchange mass, which leads to heating.

A plot from Cheng et al. 2019 showing a triple system in which the third star causes the stars in Par 1802 to cross their Roche limit and exchange mass, which leads to heating.

 

 

Improving signal-to-noise in the Gemini Planet Imager’s polarimeter

A zoomed-in view of the lenslets in the GPI polarimeter.

A zoomed-in view of the lenslets in the GPI polarimeter.


I have worked with Prof. Michael Fitzgerald on improving the signal-to-noise ratio in the Gemini Planet Imager (GPI) back-end science camera’s dual-channel polarimeter. We improved on the existing rudimentary model for extracting science measurements from raw detector data by creating a more sophisticated model that more closely fits each lenslet. Specifically, we developed a Gaussian-based simulator that models the detector data and refined our model by creating an offset scheme using microlenslet data that shifts and scales the model to optimize the model’s fit.