TESS Data for Asteroseismology: Light Curve Systematics Correction
Mikkel N. Lund, Rasmus Handberg, Derek L. Buzasi, Lindsey Carboneau,, Oliver J. Hall, Filipe Pereira, Daniel Huber, Daniel Hey, Timothy Van Reeth, and T'DA collaboration

TL;DR
This paper introduces two methods for correcting systematic noise in TESS light curves, enabling more accurate asteroseismology studies by providing analysis-ready data efficiently.
Contribution
The authors present two new co-trending algorithms for TESS light curves that effectively remove systematics across various stellar variability types.
Findings
Performance meets noise reduction expectations
Correction of a full sector can be completed within a few days
Pipeline is open-source and ready for community use
Abstract
Data from the Transiting Exoplanet Survey Satellite (TESS) has produced of order one million light curves at cadences of 120 s and especially 1800 s for every ~27-day observing sector during its two-year nominal mission. These data constitute a treasure trove for the study of stellar variability and exoplanets. However, to fully utilize the data in such studies a proper removal of systematic noise sources must be performed before any analysis. The TESS Data for Asteroseismology (T'DA) group is tasked with providing analysis-ready data for the TESS Asteroseismic Science Consortium, which covers the full spectrum of stellar variability types, including stellar oscillations and pulsations, spanning a wide range of variability timescales and amplitudes. We present here the two current implementations for co-trending of raw photometric light curves from TESS, which cover different regimes of…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
