Algebraic and machine learning approach to hierarchical triple-star stability

no code implementations • 7 Jul 2022 • Pavan Vynatheya, Adrian S. Hamers, Rosemary A. Mardling, Earl P. Bellinger

We present two approaches to determine the dynamical stability of a hierarchical triple-star system.

BIG-bench Machine Learning

When a Period Is Not a Full Stop: Light Curve Structure Reveals Fundamental Parameters of Cepheid and RR Lyrae Stars

no code implementations • 25 Nov 2019 • Earl P. Bellinger, Shashi M. Kanbur, Anupam Bhardwaj, Marcella Marconi

We quantify which aspects of light curve structure are most important in determining fundamental parameters, and find for example that the second Fourier amplitude component of RR Lyrae light curves is even more important than period in determining the effective temperature of the star.

Fundamental Parameters of Main-Sequence Stars in an Instant with Machine Learning

1 code implementation • 6 Jul 2016 • Earl P. Bellinger, George C. Angelou, Saskia Hekker, Sarbani Basu, Warrick Ball, Elisabeth Guggenberger

Our method is open source and freely available for the community to use.

BIG-bench Machine Learning