Kavli Affiliate: Michael M. Fausnaugh
| First 5 Authors: Hugh Roxburgh, Ryan Ridden-Harper, Andrew Moore, Clarinda Montilla, Brayden Leicester
| Summary:
We present TESSELLATE, a dedicated pipeline for performing an untargeted
search documenting all variable phenomena captured by the TESS space telescope.
Building on the TESSreduce difference imaging pipeline, TESSELLATE extracts
calibrated and reduced photometric data for every full frame image in the TESS
archive. Using this data, we systematically identify transient, variable and
non-sidereal signals across timescales ranging from minutes to weeks. The high
cadence and wide field of view of TESS enables us to conduct a comprehensive
search of the entire sky to a depth of ~17 $m_i$. Based on the volumetric rates
for known fast transients, we expect there to be numerous Fast Blue Optical
Transients and Gamma Ray Burst afterglows present in the existing TESS dataset.
Beyond transients, TESSELLATE can also identify new variable stars and
exoplanet candidates, and recover known asteroids. We classify events using
machine learning techniques and the work of citizen scientists via the
Zooniverse Cosmic Cataclysms project. Finally, we introduce the TESSELLATE Sky
Survey: a complete, open catalog of the variable sky observed by TESS.
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