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

Mojtaba Taheri; Jesse Cranney; Antonino Marasco; Stephanie Monty; Davide Massari; Guido Agapito; Giovanni Cresci; Richard M. McDermid; Francois Rigaut; Benoit Neichel; David Brodrick; Cédric Plantet

doi:10.1117/12.3020335

arXiv · 2410.12106

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

Mojtaba Taheri·Jesse Cranney·Antonino Marasco·Stephanie Monty·Davide Massari·Guido Agapito·Giovanni Cresci·Richard M. McDermid·Francois Rigaut·Benoit Neichel·David Brodrick·Cédric Plantet

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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.

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Mojtaba Taheri, Jesse Cranney, Antonino Marasco, Stephanie Monty, Davide Massari, Guido Agapito, Giovanni Cresci, Richard M. McDermid, Francois Rigaut, Benoit Neichel, David Brodrick, Cédric Plantet. 2024-10-15. MAVIS: Enabling High-Precision Ground-Based Astrometry in the Visible Spectrum. https://doi.org/10.1117/12.3020335

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