Yoga

h1. YoGA Ao features

The YoGA_Ao library contains routines to simulate the whole process of image formation through the atmosphere, a telescope and an adaptive optics (AO) system. Following [[ the YoGA Philosophy ]]  YoGA_Ao is designed around a double-sided API: a Yorick API (called hereafter high-level routines) and CUDA-C API accessible to the interpreter through Yorick wrappers (called hereafter advanced routines).

There are two ways to use YoGA_Ao, either through the GUI or through the command line possibly using predefined scripts. The following description is valid for both ways but is probably more relevant to command line users. The main difference between the GUI and the command line interface is the way the simulation parameters are imported. In the latter case, the simulation parameters are centralized into a parameter file (.par). Examples of .par files are given in the data/par directory and can be used as templates. The high-level API contains a dedicated routine to read the parameters from this file and import them in the simulation environment.

[[YoGA_Ao_features#List_of_features]]

h2. List of features

Each API comes with a set of structures concentrating the configuration parameters for the simulation as well as various data used for computation and diagnostics. For the Yorick API, the list of structures can be found in the file yoga_ao_ystruct.i. Concerning the CUDA-C API, please refer to the file yoga_ao.cpp. Available features include:

* Kolmogorov-type turbulence generation over an arbitrary number of layers with arbitrary properties.

* Shack-Hartmann wavefront sensing including Laser Guide Stars (LGS)

* Short and long exposure imaging under the turbulence

h3. Simulation geometry

The main parameter that drives most of the choices for the simulation geometry is the Fried parameter r0. Typically, for an adequate sampling, the equivalent size of the pixels we use to simulate the turbulent phase screens should be less than half r0. To ensure a good sampling, in YoGA_Ao, r0 is simulated on about 6 pixels. This ratio defines the size of the "quantum" pixels and thus the size of the phase screens to simulate (as compared to the telescope size). From this screen size, the full images size is defined,taking into account the sampling required for imaging.

As an example, in the case of an ELT, the linear size of the phase screen support (and thus of the pupil) is of the order of 1.5k to 2k pixels. This means that the linear size of the image will be at least 4k (for a minimum Shannon sampling). This is a very large number which will imply heavy computations.

To cope for these various requirements we can define 3 different pupils: 

* the large pupil (called ipupil) defined on the largest support (4kx4k in our previous example) more than half of which being 0

* the small pupil (spupil) defined only on the pupil size (2kx2k in our previous example) most of it being 1

* the medium pupil (mpupil) defined on a slightly larger support: typically 4 additional pixels as a guard band on each size. This guard band is useful for manipulations on phase screens like raytracing. This is also the actual size of the ground layer phase screen.

The image below helps to understand the various pupil sizes. White is the pupil, green is the support of spupil, blue the support of mpupil et black the support of ipupil.

!570!

h3. Turbulence generation

h3. Wavefront Sensing

h3. Image formation

h2. List of routines

h3. High-level routines

h3. Advanced routines