Morphological components analysis for circumstellar disks imaging

TL;DR

This paper introduces a morphological component analysis method that improves imaging of faint circumstellar disks and exoplanets by modeling their structures and the stellar light, enhancing post-processing in astronomical observations.

Contribution

The paper presents a novel MCA approach that simultaneously models disks and stellar light, enabling better extraction of faint astronomical signals from observational data.

Findings

Effective separation of disks and stellar light demonstrated in simulations

Method improves detection of faint exoplanets and disks

Numerical experiments validate the approach's potential

Abstract

Recent developments in astronomical observations enable direct imaging of circumstellar disks. Precise characterization of such extended structure is essential to our understanding of stellar systems. However, the faint intensity of the circumstellar disks compared to the brightness of the host star compels astronomers to use tailored observation strategies, in addition to state-of-the-art optical devices. Even then, extracting the signal of circumstellar disks heavily relies on post-processing techniques. In this work, we propose a morphological component analysis (MCA) approach that leverages low-complexity models of both the disks and the stellar light corrupting the data. In addition to disks, our method allows to image exoplanets. Our approach is tested through numerical experiments.