Precise Transit Observation and Characterization of Exoplanets

Abstract:
Transit photometry and transit spectroscopy are two widely used powerful methods of detection and characterization of exoplanets as they give an insight into the orbital parameters, physical conditions as well as chemical compositions of exoplanets. One aspect of this talk will be focusing on the transit photometric observation of the close-in exoplanets. One of the major challenges faced in transit observation is to achieve high precision while deducing the transit parameters which in turn is essential for precise atmospheric characterization of the planets. We have made a few transit follow-up photometric observations with our 2m Himalayan Chandra Telescope, Hanle and 1.3m Jagadish Chandra Bhattacharyya Telescope, Kavalur leveraging their large apertures conducive for achieving high photometric signal-to-noise ratio (>200). In this talk, I will present how we have segregated the different fluctuations/noises on the basis of scale and temporal correlation. I will further highlight how we addressed them by preprocessing the transit light curves with wavelet denoising and applying Gaussian regression technique during modeling. These techniques along with our state-of-the-art algorithm for modeling have provided the physical parameters of the planets with more precise values (~2-10 times precision) than reported earlier. The other aspect of the talk will be to focus on the theoretical modeling of the transmission (transit) spectra of the hot Jupiters including the effect of scattering albedo. I will describe our self- consistent forward model that solves the complete 1-D radiative transfer equations pertinent to the case of transmission of light through the atmospheres of the hot Jupiters using the discrete space theory of radiative transfer inherited from a decades-old well-known Fortran model. I will demonstrate that the inclusion of both diffused reflection and transmission changes the calculated transmission depth of the hot Jupiters predominantly in the optical wavelength region, more significantly in case of a dusty or hazy atmosphere. Based on this forward model, we will construct better and faster retrieval models in future which can be used to model the upcoming observational data from missions such as JWST, ARIEL etc.