Enhanced detection limits in the SHINE F150 survey through the regime switching model

Optimizing thresholds and investigating environmental noise

¹ STAR Institute, Université de Liège, Allée du Six Août 19C, 4000 Liège, Belgium
² IPAG, Univ Grenoble Alpes, CNRS, Grenoble, France

^★ Corresponding author: This email address is being protected from spambots. You need JavaScript enabled to view it.

Received: 18 April 2025
Accepted: 4 December 2025

Abstract

Context. In high-contrast imaging, a novel detection algorithm for angular differential imaging (ADI) sequences has recently been introduced: the regime switching model (RSM). This advanced statistical tool enhances the distinction between planetary signals and bright speckles by simultaneously combining multiple ADI-based post-processing techniques.

Aims. In this study, we apply the RSM algorithm to analyze the F150 sample from the SHINE high-contrast imaging survey carried out with VLT/SPHERE, aiming to enhance detection limits and identify new exoplanet candidates. Additionally, we investigate how environmental conditions influence post-processed noise distributions and detection thresholds.

Methods. We generated detection maps and contrast curves for 213 observations in the F150 SHINE sample using the RSM algorithm. A clustering approach based on environmental parameters was used to group observations with similar noise characteristics. We propose two methods for defining radial detection thresholds in the RSM maps: fitting a lognormal distribution to the post-processed noise and maximizing the F1 score. We also assessed the performance of various combinations of post-processing techniques within the RSM framework to identify optimal configurations.

Results. This study demonstrates the utility of clustering based on observational parameters, effectively distinguishing features such as wind-driven halos and low-wind effects. Detection thresholds vary significantly across clusters, differing by up to a factor of ten, highlighting the importance of considering observational environments. Lognormal thresholds provide conservative, noise-aware limits, while F1 score-based thresholds offer observation-specific results, with both showing compatibility overall. RSM improves detection limits by an average factor of two at 1" and five at inner working angles compared to standard principal component analysis processing. This study reports more than 30 newly detected signals, including one promising candidate awaiting second-epoch confirmation.