STIM map: detection map for exoplanets imaging beyond asymptotic Gaussian residual speckle noise

Abstract

Direct imaging of exoplanets is a challenging task as it requires to reach a high contrast at very close separation to the star. Today, the main limitation in the high-contrast images is the quasi-static speckles that are created by residual instrumental aberrations. They have the same angular size as planetary companions and are often brighter, hence hindering our capability to detect exoplanets. Dedicated observation strategies and signal processing techniques are necessary to disentangle these speckles from planetary signals. The output of these methods is a detection map in which the value of each pixel is related to a probability of presence of a planetary signal. The detection map found in the literature relies on the assumption that the residual noise is Gaussian. However, this is known to lead to higher false positive rates, especially close to the star. In this paper, we re-visit the notion of detection map by analyzing the speckle noise distribution, namely the Modified Rician distribution. We use non-asymptotic analysis of the sum of random variables to show that the tail of the distribution of the residual noise decays as an exponential distribution, hence explaining the high false detection rate obtained with the Gaussian assumption. From this analysis, we introduce a novel time domain detection map and we demonstrate its capabilities and the relevance of our approach through experiments on real data. We also provide an empirical rule to determine detection threshold providing a good trade off between true positive and false positive rates for exoplanet detection.

A faint companion around CrA-9: protoplanet or obscured binary?

“…It is also tentatively seen using PCA-ASDI, although self-subtraction of azimuthally extended structures due to angular differential imaging may account for the differences between the two images. PCA-SDI and PCA-ASDI images obtained with different pc subtracted are provided in Appendix E. We also computed a standardized trajectory intensity mean map (STIM map; Pairet et al 2019), using the residual cube after subtraction of the PCA-SDI model (as in Christiaens et al 2019a). The STIM map does not reveal the spiral feature conspicuously, as the inverse STIM map (i.e.…”

Exoplanet detection in starshade images

“…Moreover, this covariance is not derived from the Gaussian equation together with the signal intensity, and thus the result is not guaranteed to be MLE. Pairet et al 28 (STIM map) proposed STIM map, which used a modified Rician distribution, which is a heavy tail distribution compared to Gaussian, to model the speckles. Dahlqvist et al 29 (RSM map) used a Markov process to model the same pixel throughout the different images.…”

Exoplanet imaging data challenge: benchmarking the various image processing methods for exoplanet detection

“…Unknown stands for a reference-less submission we received. STIM fullframe is the Standardized Trajectory Intensity Mean (STIM) detection map 35 computed from a fullframe PCA subtraction. STIM annuli is the STIM detection map computed from an annular PCA subtraction.…”