| Abstract : | To understand the formation and evolution of habitable extrasolar planets and to search for life outside our solar system ultimately, it is paramount to look for Earth-like exoplanets in our neighbourhood. However, due to the smaller size of the planets, their observed transit is comparable to noise coming from various sources. Therefore, informed detrending of the light curve is a key step in teasing out the faint signature of small Earth-like planets in transit. In this research work, we aim to understand and characterise the noise originating from stellar jitter and systematics in the white light curves of M-Dwarfs within the 50 light years of solar neighbourhood. To this end, we are using Gaussian processes to model the surface activity and systematics. Spherical Harmonics are used to model the stellar surface. Along with this, Bayesian Inference is being used to get the posterior distribution of the parameters governing the stellar surface models. To validate our method, we have generated synthetic data through forward modelling of the stellar light curves by adding systematics generated by sampling functions from prior distribution to stellar models. This is followed by fitting GP to the data to remove systematics and obtain the posterior distribution of various stellar surface parameters. After successful implementation of our model, we use it on the ground-based data of 50 Project EDEN targets and detrend them off stellar activity and systematics.
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