CASCADe – Data reduction

CASCADe (Calibration of trAnsit Spectroscopy using CAusal Data) is a python code used to calibrated the spectroscopic data for transiting exoplanets and to extract the transit or emission spectrum of the exoplanet.

License/credits : GNU GPLv3, author Jeroen Bouwman, @MPIA

At present several thousand transiting exoplanet systems have been discovered. For relatively few systems, however, a spectro-photometric characterization of the planetary atmospheres could be performed due to the tiny photometric signatures of the atmospheres and the large systematic noise introduced by the used instruments or the earth atmosphere. Several methods have been developed to deal with instrument and atmospheric noise. These methods include high precision calibration and modeling of the instruments, modeling of the noise using methods like principle component analysis or Gaussian processes and the simultaneous observations of many reference stars.

Though significant progress has been made, most of these methods have drawbacks as they either have to make too many assumptions or do not fully utilize all information available in the data to negate the noise terms.

The CASCADe project implements a novel “data driven” method, pioneered by Schoelkopf et al (2016) utilizing the causal connections within a data set, and uses this to calibrate the spectral timeseries data of single transiting systems. The current code has been tested successfully to spectroscopic data obtained with the Spitzer and HST observatories.