Matthias Samland ( Germany )
samland @ mpia.de
Methods for the Discovery and Characterization of Exoplanets using Direct Imaging
My main focus is researching better ways of using High-Contrast Imaging to discover and characterize planets, disks, and ultra cool dwarfs. Direct Imaging, as a relatively new field of research, still faces many challenging issues in signal extraction (e.g., non-gaussian/correlated uncertainties, systematics, low signal-to-noise). My work focuses on methods to get the most out of the data and understanding the properties of the extracted signal and uncertainties and how they affect the statistical inference of physical properties. Beside algorithms of data reduction, I am actively developing an MCMC-based python package (BACON: Baysian Atmospheric CharacterizatiON) for conveniently fitting atmospheric models of arbitrary dimensionality to photometric and spectroscopic data while taking into account
correlated noise. Involvement in the VLT/SPHERE instrument and working with SPHERE data is a big part of my work and tools developed for this instrument will become ever more important for future facilities like the E-ELT.
Supervisor: Wolfgang Brandner (MPIA )