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Table 2

Transit light curve model parameters and priors.

Description Parameter Units Prior
Global parameters

Zero epoch T0 (BJD) N(a)
Orbital period P (days) N(a)
Stellar density Ρ (g cm−3) U (5, 35)
Impact parameter b U (0, 1)
Apparent area ratio U (0.022, 0.082)
Apparent area ratio U (0.022, 0.082)(b)
Robust area ratio U (0.022, 0.952)
Host temperature Teff,h (K) N (3200, 160)
Cont. temperature Teff,c (K) U (2500, 12000)
Passband-dependent parameters(c)

Power-2 h1 in TESS h1,TESS N (0.78,0.008)
Power-2 h2 in TESS h2,TESS
N (0.69, 0.124)
Power-2 h1 in g h1,g
N (0.64, 0.014)
Power-2 h2 in g h2,g N (0.61, 0.070)
Power-2 h1 in r h1,r N (0.65, 0.015)
Power-2 h2 in r h2,r N (0.56, 0.079)
Power-2 h1 in i h1,i N (0.74, 0.012)
Power-2 h2 in i h2,i N (0.68, 0.131)
Power-2 h1 in zs N (0.79, 0.011)
Power-2 h2 in zs N (0.71, 0.155)
Light-curve-dependent parameters

Log10 white noise log10 σ U (−4,0)(d)
Baseline coefficient Si N (e)

Notes. The global parameters are independent of the passband or light curve, the passband-dependent parameters are repeated for each passband, and the light-curve-dependent parameters are repeated for each separate light curve. Ν(μ, σ) stands for a normal prior with a mean μ and standard deviation σ, 4U(a, b) stands for a uniform distribution from a to b, and ‘Cont. temperature’ stands for the effective temperature of the contaminating star. (a)The zero epoch is given a normal prior N(2459255.694, 0.015) and the period is given a normal prior N(2.3262, 0.0002). (b)The TESS transits are given a separate apparent radius ratio that effectively makes the TESS contamination independent of the contamination in the ground-based observations. (c)The limb darkening coefficients correspond to the transformed power-2 limb darkening law coefficients (Maxted 2018) and have normal priors calculated using LDTK. (d)The average log10 white noise parameters for each light curve have uninformative uniform priors. (e)The linear baseline model coefficients have loose normal priors based on the light curve variability. We do not write them here explicitly, but they can be found from the 02_joint_analysis.ipynb notebook in the project's GitHub repository.

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