activity
20202025
most citedexoplanet: Gradient-based probabilistic inference for exoplanet data & other astronomical time series

215 citations · 307 across the 5 of their papers we have counts for

collaborators

5 papers

astro-ph.SR2025★ 1 cited

Tidal Synchronization of TESS Eclipsing Binaries

Marshall Hobson-Ritz, Jessica Birky, Leah Peterson +7

Tidal synchronization plays a fundamental role in the evolution of binary star systems. However, key details such as the timescale of synchronization, efficiency of tidal dissipati…

astro-ph.EP2022★ 11 cited

Analytic Light Curve for Mutual Transits of Two Bodies Across a Limb-darkened Star

Tyler A. Gordon, Eric Agol

We present a solution for the light curve of two bodies mutually transiting a star with polynomial limb darkening. The term "mutual transit" in this work refers to a transit of the…

astro-ph.IM2021★ 215 cited

exoplanet: Gradient-based probabilistic inference for exoplanet data & other astronomical time series

Daniel Foreman-Mackey, Rodrigo Luger, Eric Agol +13

"exoplanet" is a toolkit for probabilistic modeling of astronomical time series data, with a focus on observations of exoplanets, using PyMC3 (Salvatier et al., 2016). PyMC3 is a f…

astro-ph.SR2021★ 53 cited

Stellar Rotation in the K2 Sample: Evidence for Modified Spindown

Tyler A. Gordon, James R. A. Davenport, Ruth Angus +5

We analyze light curves of 284,834 unique K2 targets using a Gaussian process model with a quasi-periodic kernel function. By crossmatching K2 stars to observations from Gaia Data…

astro-ph.IM2020★ 27 cited

A Fast, 2D Gaussian Process Method Based on Celerite: Applications to Transiting Exoplanet Discovery and Characterization

Tyler Gordon, Eric Agol, Daniel Foreman-Mackey

Gaussian processes (GPs) are commonly used as a model of stochastic variability in astrophysical time series. In particular, GPs are frequently employed to account for correlated s…