A New Standard for Assessing the Performance of High Contrast Imaging Systems

TL;DR

The paper introduces a new performance metric called the 'performance map' for evaluating high contrast imaging systems, aiming to improve upon the traditional contrast curve by incorporating detection theory principles.

Contribution

It proposes a theoretically grounded, robust figure of merit—the performance map—that enhances comparison and assessment of high contrast imaging system performance.

Findings

Performance map integrates TPF, FPF, and detection thresholds.

Provides a theoretical basis and practical recipe for implementation.

Aims to standardize performance evaluation across the field.

Abstract

As planning for the next generation of high contrast imaging instruments (e.g. WFIRST, HabEx, and LUVOIR, TMT-PFI, EELT-EPICS) matures, and second-generation ground-based extreme adaptive optics facilities (e.g. VLT-SPHERE, Gemini-GPI) are halfway through their principal surveys, it is imperative that the performance of different designs, post-processing algorithms, observing strategies, and survey results be compared in a consistent, statistically robust framework. In this paper, we argue that the current industry standard for such comparisons -- the contrast curve -- falls short of this mandate. We propose a new figure of merit, the "performance map," that incorporates three fundamental concepts in signal detection theory: the true positive fraction (TPF), false positive fraction (FPF), and detection threshold. By supplying a theoretical basis and recipe for generating the performance map, we hope to encourage the widespread adoption of this new metric across subfields in exoplanet imaging.