Direct Imaging of Exoplanets Without Background Subtraction: Implications for ELTs

TL;DR

This paper proposes a novel method for direct exoplanet imaging that eliminates the need for background subtraction by leveraging atmospheric encoding of planetary signals in millisecond exposures, potentially enabling habitable planet detection with ELTs.

Contribution

It introduces a new statistical inference approach that uses atmospheric encoding to simultaneously estimate NCPAs and planetary images without background subtraction.

Findings

Method enables direct imaging without background subtraction.

Compatible with spectral and diurnal information sources.

Potential to improve habitable planet imaging with ELTs.

Abstract

The ultra-high contrast capability required to form images of other solar systems is arguably the highest-profile challenge in astronomy today. The current high-contrast imaging efforts all require background subtraction to separate the planetary image from the image of the host star. Background estimation is difficult due to the presence of non-common path aberrations (NCPAs) that change with time. The only major source of information that is not being utilized by current efforts is the random encoding of the planetary image and the NCPAs by the atmosphere on millisecond time-scales. Here, a method that utilizes this information in order to avoid background subtraction altogether is proposed. This new paradigm will allow simultaneous estimation of the time-dependent NCPAs and the planetary image via rigorous statistical inference procedures. These procedures are fully compatible with other information sources, such as diurnal field rotation and spectral diversity. Given the open-ended nature of the background subtraction issues, the ideas explained herein may well the key to imaging habitable planets with Extremely Large Telescopes (ELTs). Fully exploiting the information content of millisecond exposures will require significant design modifications of the ELT wavefront sensors and science camera systems, if ultra-high contrast imaging is to be priority.