Metadata-Version: 2.1
Name: astro-tiptop
Version: 1.3.0
Author-email: Fabio Rossi <fabio.rossi@inaf.it>
License: MIT License
Project-URL: repository, https://github.com/astro-tiptop/TIPTOP
Requires-Python: >=3.9
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: matplotlib
Requires-Dist: numpy
Requires-Dist: pyyaml
Requires-Dist: astro-p3>=1.2.3
Requires-Dist: mastsel>=1.2.4
Provides-Extra: docs
Requires-Dist: sphinx; extra == "docs"
Provides-Extra: gpu
Requires-Dist: mastsel[gpu]; extra == "gpu"
Provides-Extra: gui
Requires-Dist: ipywidgets; extra == "gui"

# TIPTOP

In order to be able to easily predict the AO performance, we have developed
this fast algorithm producing the expected Adaptive Optics (AO see
https://en.wikipedia.org/wiki/Adaptive_optics) Point Spread Function (PSF) for
any of the existing AO observing modes (Single-Conjugate-AO,
Laser-Tomographic-AO, Multi-Conjugate-AO, Ground-Layer-AO), 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 with GPU acceleration), and
efficiently explore the wide parameter space.

See the documentation here: https://tiptop.readthedocs.io
