activity
19982022
most citedSeven temperate terrestrial planets around the nearby ultracool dwarf star TRAPPIST-1

1.6k citations · 4.4k across the 33 of their papers we have counts for

collaborators

34 papers

astro-ph.EP2022★ 22 cited

Transit timing variations of AU Microscopii b and c

Gy. M. Szabó, Z. Garai, A. Brandeker +76

Here we report large-amplitude transit timing variations (TTVs) for AU\,Microcopii b and c as detected in combined TESS (2018, 2020) and CHEOPS (2020, 2021) transit observations. A…

astro-ph.IM2021★ 1 cited

Warm Spitzer IRAC Photometry: dependencies on observing mode and exposure time

Jessica E. Krick, Patrick J. Lowrance, Sean Carey +7

We investigate differences in Spitzer/IRAC 3.6 and 4.5micron photometry that depend on observing strategy. Using archival calibration data we perform an in-depth examination of the…

astro-ph.SR2021★ 16 cited

Spitzer IRAC observations of JWST calibration stars

Jessica E. Krick, Patrick Lowrance, Sean Carey +10

We present infrared photometry of all 36 potential JWST calibrators for which there is archival Spitzer IRAC data. This photometry can then be used to inform stellar models necessa…

astro-ph.SR2020★ 171 cited

The Field Substellar Mass Function Based on the Full-sky 20-pc Census of 525 L, T, and Y Dwarfs

J. Davy Kirkpatrick, Christopher R. Gelino, Jacqueline K. Faherty +49

We present final Spitzer trigonometric parallaxes for 361 L, T, and Y dwarfs. We combine these with prior studies to build a list of 525 known L, T, and Y dwarfs within 20 pc of th…

astro-ph.EP2020

Refining the transit timing and photometric analysis of TRAPPIST-1: Masses, radii, densities, dynamics, and ephemerides

Eric Agol, Caroline Dorn, Simon L. Grimm +32

We have collected transit times for the TRAPPIST-1 system with the Spitzer Space Telescope over four years. We add to these ground-based, HST and K2 transit time measurements, and…

astro-ph.IM2020

Random Forests applied to High Precision Photometry Analysis with Spitzer IRAC

Jessica Krick, Jonathan Fraine, Jim Ingalls +1

We present a new method employing machine learning techniques for measuring astrophysical features by correcting systematics in IRAC high precision photometry using Random Forests.…