Characterizing the performance of the NIRC2 vortex coronagraph at W.M. Keck Observatory

TL;DR

This study evaluates the NIRC2 vortex coronagraph's performance at Keck Observatory over three years, analyzing imaging data and developing models to predict detection limits, thereby enhancing high-contrast imaging strategies for exoplanet and disk observations.

Contribution

The paper provides a comprehensive performance characterization of the NIRC2 vortex coronagraph, including data-driven models to predict detection limits and insights into optimal observing strategies.

Findings

RDI outperforms ADI at small angular separations (<0.25") with typical PA rotation.

Power-law relation between PA rotation and angular separation for ADI vs. RDI performance.

Random forest models explain up to 80% of variance in ADI detection limits.

Abstract

The NIRC2 vortex coronagraph is an instrument on Keck II designed to directly image exoplanets and circumstellar disks at mid-infrared bands $L^\prime$ (3.4-4.1 $\mu$m) and $M_s$ (4.55-4.8 $\mu$m). We analyze imaging data and corresponding adaptive optics telemetry, observing conditions, and other metadata over a three year time period to characterize the performance of the instrument and predict the detection limits of future observations. We systematically process images from 359 observations of 304 unique stars to subtract residual starlight (i.e., the coronagraphic point spread function) of the target star using two methods: angular differential imaging (ADI) and reference star differential imaging (RDI). We find that for the typical parallactic angle (PA) rotation of our dataset ($\sim$10$^{\circ}$), RDI provides gains over ADI for angular separations smaller than 0.25$^{\prime\prime}$. Furthermore, we find a power-law relation between the angular separation from the host star and the minimum PA rotation required for ADI to outperform RDI, with a power-law index of -1.18$\pm$0.08. Finally, we use random forest models to estimate ADI and RDI post-processed detection limits a priori. These models, which we provide publicly on a website, explain 70%-80% of the variance in ADI detection limits and 30%-50% of the variance in RDI detection limits. Averaged over a range of angular separations, our models predict both ADI and RDI contrast to within a factor of 2. These results illuminate important factors in high-contrast imaging observations with the NIRC2 vortex coronagraph, help improve observing strategies, and inform future upgrades to the hardware.