TIPTOP: a new tool to efficiently predict your favorite AO PSF

TL;DR

TIPTOP is a fast, Python-based tool that predicts adaptive optics PSFs under various conditions, aiding in performance assessment and planning for AO systems.

Contribution

We developed TIPTOP, a rapid analytical algorithm for predicting AO PSFs across modes and atmospheric conditions, unifying previous methods in a single framework.

Findings

Produces PSF predictions in seconds per case

Applicable to all AO observing modes

Facilitates AO performance optimization

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.