Poster + Paper
15 January 2021 TIPTOP: a new tool to efficiently predict your favorite AO PSF
Author Affiliations +
Conference Poster
Abstract
The Adaptive Optics (AO) performance significantly depends on the available Natural Guide Stars (NGSs) and a wide range of atmospheric conditions (seeing, Cn2, windspeed, . . . ). In order to be able to easily predict the AO performance, we have developed a fast algorithm - called TIPTOP - producing the expected AO Point Spread Function (PSF) for any of the existing AO observing modes (SCAO, LTAO, MCAO, GLAO), and any atmospheric conditions. This TIPTOP tool takes its roots in an analytical approach, where the simulations are done in the Fourier domain. This allows to reach a very fast computation time (few seconds per PSF), and efficiently explore the wide parameter space. TIPTOP has been developed in Python, taking advantage of previous work developed in different languages, and unifying them in a single framework. The TIPTOP app is available on GitHub at: https://github.com/FabioRossiArcetri/TIPTOP, and will serve as one of the bricks for the ELT Exposure Time Calculator.
© (2021) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Benoit Neichel, Olivier Beltramo-Martin, Cédric Plantet, Fabio Rossi, Guido Agapito, Thierry Fusco, Elena Carolo, Giulia Carlà, Michele Cirasuolo, and Remco Van Der Burg "TIPTOP: a new tool to efficiently predict your favorite AO PSF", Proc. SPIE 11448, Adaptive Optics Systems VII, 114482T (15 January 2021); https://doi.org/10.1117/12.2561533
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KEYWORDS
Adaptive optics

Point spread functions

Stars

Device simulation

Detection and tracking algorithms

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