Measuring Rotation Periods from TESS in PLATO LOPS2 Fields

Target Selection Measuring Rotation Periods from TESS in PLATO LOPS2 Fields D.B. PALAKKATHARAPPIL¹, R.A. GARCÍA¹, L. BORG¹ ², A. HAMY³, A. PRIN³, S. MATHUR4 1. Université Paris-Saclay, Université Paris Cité, CEA, CNRS, AIM, F-91191, Gif-sur-Yvette, France, 2. INSA Lyon - Institut National des Sciences Appliquées, France 3. École Centrale-Supélec, Univesité Paris-Saclay 4. IAC - Instituto de Astrofísica de Canarias NASA's Transiting Exoplanet Survey Satellite (TESS, Ricker et al. 2015) has been conducting high-precision photometric observations for over seven years, covering more than 95% of the sky. By the end of Cycle 8, over 90% of this coverage will include observations from multiple sectors. The upcoming ESA PLAnetary Transits and Oscillations of stars (PLATO, Rauer et al. 2025) mission, scheduled for launch by the end of 2026, aims to detect terrestrial planets in the habitable zones of bright, Sun-like stars. PLATO will observe stars in the Southern Hemisphere (LOPS2) for a minimum of two years, overlapping with TESS's continuous viewing zone. By the time of PLATO's launch, TESS will have accumulated four years of data on this region, offering a unique opportunity to measure and catalogue stellar rotation periods in advance of the mission. •The MIT Quick Look Pipeline (QLP, Huang et al. 2020) provides light curves for ~21M TESS FFI images. •PLATO Stars Selection: •Cross-matched with LOPS2PICv2.10 •3200 K < Teff < 600 K •≥2 consecutive sectors •Variability ≥3σ above TESS noise •Final sample: ~32,000 stars. Kepler observed by TESS Stitching & Rotation Rotation in PLATO LOPS2 •Thousands of PLATO-field stars visually classified for rotation •Random forest trained on visual inspection: rotators vs. non-rotators •Validated on Kepler stars with known periods (Santos et al. 2019, 2021) •Figure 3 (left): TESS closest periods from different methods compared to reference show strong systematics (e.g., 14-day gap artifacts) with ~50% reliability. •Figure 3 (right): Applying the classifier removes stars with unreliable rotation and hence the systematics while increasing reliability to 81%. •32,000 stars studied with star-privateer and the new random forest classifier, yielding a preliminary sample of 9,000 reliable rotation periods. •The methodology allows to measure Prot up to 20 days with TESS campaigns of at least 2 continuous sectors. •Prot distribution is bimodal, consistent with the intermediate period gap linked to stalling of magnetic braking (Figure 4). •Perspectives: •To improve the yields of Prot>20 days with a better training Figure 2: (Top) Sector-wise normalized light curve from the TESS QLP. (Middle) Stitched light curve using Bayesian inference implemented in PYTADACS-R. (Bottom) Autocorrelation function (left) and wavelet transform (right) of the stitched light curve, revealing a rotation period of 43 days. Figure 1: Stacked histogram of selected stars with continuous QLP sectors, grouped and stacked by PLATO target priority classes Figure 4: Rotation period obtained with the automatic procedure versus effective temperature for the selected sample Figure 3: (Left) Closest rotation periods from TESS using multiple methods compared to Kepler rotation periods. The red color represent stars outside 10% error, stars with short rotation in green and stars with long rotation in yellow. (Right) Rotation periods from TESS after applying the random forest classification. Breton, S. N., Santos, A. R. G., Bugnet, L., et al. 2021, A&A, 647, A125 Huang C. X. et al., 2020, Res. Notes Am. Astron. Soc., 4, 204 Rauer, H., Catala, C., Aerts, C., et al. 2014, Exp. Astron., 38, 249 Ricker, G. R., Winn, J. N., Vanderspek, R., et al. 2015, J. Astron. Telesc. Instrum. Syst., 1, 014003 Santos, A. R. G., Garca, R. A., Mathur, S., et al. 2019, ApJS, 244, 21 Santos, A. R. G., Breton, S.N., Mathur, S., Garca, R.A., 2021, ApJS, 255, 17 We acknowledge the support from the GOLF and PLATO Centre National D’Études Spatiales grant. We acknowledge the use of TESS High Level Science Products (HLSP) produced by the Quick-Look Pipeline (QLP) at the TESS Science Office at MIT, which are publicly available from the Mikulski Archive for Space Telescopes (MAST). Funding for the TESS mission is provided by NASA's Science Mission directorate. •TESS light curves show 7/14-day gaps due to periodic data downlinks in 27-day sectors •Sector-wise normalization corrects background flux variations •Discontinuities hinder detection of long rotation periods (>14 days) •Long-period detection requires stitching across sectors •PYTADACS-R applies Bayesian inference for stitching •Stitching is sensitive to background, stray light, and edge effects •Stellar activity modulates amplitudes, often below TESS noise •Low-SNR or poorly calibrated light curves flagged as unreliable •Detection of periods near 14/27 days often correspond to TESS gaps •Rotation periods measured using star-privateer (Breton et al. 2024): •Autocorrelation, Wavelet, and Lomb-Scargle •Random forest classifies stars as reliable/unreliable rotators based on extracted features Prot ACF = 43 days Prot GWPS = 43 days RAW Stitched Preliminary Results TIC 25134598