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Transit timing variations of the sub-Saturn exoplanet HAT-P-12b
Journal article   Peer reviewed

Transit timing variations of the sub-Saturn exoplanet HAT-P-12b

Kaviya Parthasarathy, Hsin-Min Liu, Ing-Guey Jiang, Li-Chin Yeh, Napaporn A-thano, Supachai Awiphan, Wen-Chi Cheng, Devesh P. Sariya, Shraddha Biswas, Devendra Bisht, …
New astronomy, Vol.119, p.102390
10/2025

Abstract

Exoplanets: individual (HAT-P-12b) Planetary systems Techniques: photometric
We present Transit Timing Variations (TTVs) of HAT-P-12b, a low-density sub-Saturn mass planet orbiting a metal-poor K4 dwarf star. Using 14 years of observational data (2009–2022), our study incorporates 7 new ground-based photometric transit observations, three sectors of Transiting Exoplanet Survey Satellite (TESS) data, and 23 previously published light curves. A total of 46 light curves were analyzed using various analytical models, such as linear, orbital decay, apsidal precession, and sinusoidal models to investigate the presence of additional planets. The stellar tidal quality factor (Q⋆′∼ 28.4) is lower than the theoretical predictions, making the orbital decay model an unlikely explanation. The apsidal precession model with a χr2 of 4.2 revealed a slight orbital eccentricity (e = 0.0013) and a precession rate of 0.0045 rad/epoch. Frequency analysis using the Generalized Lomb–Scargle (GLS) periodogram identified a significant periodic signal at 0.00415 cycles/day (FAP = 5.1 × 10−6 %), suggesting the influence of an additional planetary companion. The sinusoidal model provides the lowest reduced chi-squared value (χr2) of 3.2. Sinusoidal fitting of the timing residuals estimated this companion to have a mass of approximately 0.02 MJ , assuming it is in a 2:1 Mean-Motion Resonance (MMR) with HAT-P-12b. Additionally, the Applegate mechanism, with an amplitude much smaller than the observed TTV amplitude of 156 s, confirms that stellar activity is not responsible for the observed variations. •Seven new ground-based photometric transit observations are presented.•The analysis uses 14-year of observational data from 2009 to 2022.•Possible explanations of transit timing variations are suggested.

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