MAVIS: Enabling High-Precision Ground-Based Astrometry in the Visible Spectrum

TL;DR

This paper explores the capabilities of MAVIS, a high-precision visible-spectrum adaptive optics system on the VLT, focusing on improving ground-based astrometry through simulations and telemetry data integration.

Contribution

It introduces a novel simulation and analysis pipeline for MAVIS, demonstrating potential improvements in astrometric precision by incorporating telemetry data.

Findings

Telemetry data enhances astrometric accuracy

Simulation results show improved performance with MAVIS

New methods for ground-based high-precision astrometry

Abstract

MAVIS (the MCAO-Assisted Visible Imager and Spectrograph), planned for the VLT Adaptive Optics Facility, represents an innovative step in Multi-Conjugate Adaptive Optics (MCAO) systems, particularly in its operation at visible wavelengths and anticipated contributions to the field of astronomical astrometry. Recognizing the crucial role of high-precision astrometry in realizing science goals such as studying the dynamics of dense starfields, this study focuses on the challenges of advancing astrometry with MAVIS to its limits, as well as paving the way for further enhancement by incorporating telemetry data as part of the astrometric analysis. We employ MAVISIM, Superstar, and DAOPHOT to simulate both MAVIS imaging performance and provide a pathway to incorporate telemetry data for precise astrometry with MAVIS. Photometry analyses are conducted using the Superstar and DAOPHOT platforms, integrated into a specifically designed pipeline for astrometric analysis in MCAO settings. Combining these platforms, our research aims to elucidate the impact of utilizing telemetry data on improving astrometric precision, potentially establishing new methods for ground-based AO-assisted astrometric analysis. This endeavor not only sheds light on the capabilities of MAVIS but also paves the way for advancing astrometry in the era of next-generation MCAO-enabled giant telescopes.