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Browse Abstracts By Name > Ranka Trupti

GMT Natural Guide Star Adaptive Optics Integrated Modeling
Conan Rod  1@  , Rodrigo Romano, Christoph Dribusch, Konstantinos Vogiatzis, Megan Shabram, Brian Walls, Breann Sitarski, Antonin Bouchez, Fernando Quiros-Pacheco, Thompson Peter, Hugo Chiquito, King-Ming Lam, Dave Ashby, Trupti Ranka@
1 : Institut des sciences biologiques - CNRS Biologie
Centre National de la Recherche Scientifique - CNRS
CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE Campus Gérard Mégie 3 rue Michel-Ange 75794 PARIS CEDEX 16 - France -  France

The Giant Magellan Telescope Project relies on a comprehensive integrated modeling tool to evaluate Observatory
Performance Modes, ranging from Seeing Limited to Adaptive Optics. This STOP (Structural-Thermal-Optical
Performance) model includes the dynamics of each domain-specific model, accounting for time-varying disturbances
such as wind jitter, vibrations, and temperature fluctuations. However, creating such a model presents challenges
due to the wide range of scientific and engineering expertise required, as well as the large number of degrees
of freedom to handle. Adaptive Optics presents additional challenges due to its high sampling rate of 1kHz
or more, exacerbated by the need to simulate long science exposures under various operating conditions. This
paper will introduce the main components of the integrated model, including finite element, optical, control,
and computational fluid dynamics, as well as the stringent verification and experimental validation processes
that the model undergoes. The choice of computing framework that integrates domain-specific models into a
unified model is critical and will be described in detail. The development of the integrated model is driven by the
need to accurately estimate errors that affect the science instrument data products and mitigate technological
risks associated with the telescope. Examples will be given on how the error budgets and risk register are used
to set priorities for the integrated modeling simulations queue. The GMTO project has identified a set of Key
Performance Parameters (KPP) that summarize the expected performance for each Observatory Performance
Mode. These KPPs are statistical quantities derived from Monte-Carlo simulations of the Observatory under
various operating and environmental conditions. This paper will show how Monte-Carlo simulations have been
performed at the Observatory level for the Natural Guide Star Adaptive Optics OPM.


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