Projet

Général

Profil

YoGA Ao features » Historique » Version 8

Julien Brule, 18/06/2012 14:32

1 1 Julien Brule
h1. YoGA Ao features
2
3
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).
4
5
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.
6
7 3 Julien Brule
[[YoGA_Ao_features#List_of_features]]
8 1 Julien Brule
9
h2. List of features
10 4 Julien Brule
11
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:
12
13
* Kolmogorov-type turbulence generation over an arbitrary number of layers with arbitrary properties.
14
* Shack-Hartmann wavefront sensing including Laser Guide Stars (LGS)
15
* Short and long exposure imaging under the turbulence
16
17
h3. Simulation geometry
18
19 6 Julien Brule
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.
20 4 Julien Brule
21
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.
22
23
To cope for these various requirements we can define 3 different pupils: 
24
25
* the large pupil (called ipupil) defined on the largest support (4kx4k in our previous example) more than half of which being 0
26
27
* the small pupil (spupil) defined only on the pupil size (2kx2k in our previous example) most of it being 1
28
29
* 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.
30
31
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.
32
33 6 Julien Brule
!https://dev-lesia.obspm.fr/projets/attachments/download/570/pupil.png!
34 1 Julien Brule
35 6 Julien Brule
All these pupils are contained in arrays accessible as internal keywords of the following geom structure available from the Yorick API : 
36
37
<pre>
38
<code class="c">
39
struct geom_struct
40
{
41
   long  ssize;       // linear size of full image (in pixels)
42
   float zenithangle; // observations zenith angle (in deg)
43
   // internal keywords
44
   long  pupdiam;     // linear size of total pupil (in pixels)
45
   float cent;        // central point of the simulation
46
   pointer _ipupil;   // total pupil (include full guard band)
47
   pointer _mpupil;   // medium pupil (part of the guard band)
48
   pointer _spupil;   // small pupil (without guard band)
49
   ...
50
};
51
52
</code>
53
</pre>
54
55
some keywords have not been reported. Please check yoga_ao_ystruct.i for more details.
56
57
In this structure pupdiam (the diameter in pixels of the pupil is considered as an internal keyword). Two other structures contain the rest of the configuration parameters : 
58
59
<pre>
60
<code class="c">
61
struct tel_struct
62
{
63
    float diam;        // telescope diameter (in meters)
64
    float cobs;        // central obstruction ratio
65
};
66
</code>
67
</pre>
68
69
<pre>
70
<code class="c">
71
struct loop_struct
72
{
73
    long  niter;      // number of iterations
74
    float ittime;     // iteration time (in sec)
75
};
76
</code>
77
</pre>
78
79
There is one high-level routines to init the geometry with only one parameter: the pupil diameter in pixels. 
80
81
<pre>
82
<code class="c">
83
func geom_init(pupdiam)
84
    /* DOCUMENT geom_init
85
      geom_init,pupdiam
86
      inits simulation geometry, depending on pupdiam
87
      the linear number of pixels in the pupil
88
    */
89
90
</code>
91
</pre>
92
93
94
95
96
97 1 Julien Brule
h3. Turbulence generation
98 6 Julien Brule
99 7 Julien Brule
The turbulence generation is done through the process of extruding infinite ribbons of Kolmogorov turbulence (see [[Model Description]]). An arbitrary number of turbulent layers can be defined at various altitude and various fraction of r0, wind speed and directions (in the range 0°-90°).
100
101 6 Julien Brule
<pre>
102
<code class="c">
103 7 Julien Brule
struct atmos_struct
104
{
105
    long    nscreens;    // number of turbulent layers
106
    float   r0;          // global r0 @ 0.5µm
107
    float   pupixsize;   // pupil piwel size (in meters)
108
    pointer dim_screens; // linear size of phase screens
109
    pointer alt;         // altitudes of each layer
110
    pointer winddir;     // wind directions of each layer
111
    pointer windspeed;   // wind speeds of each layer
112
    pointer frac;        // fraction of r0 for each layer
113
    pointer deltax;      // x translation speed (in pix / iteration) for each layer
114
    pointer deltay;      // y translation speed (in pix / iteration) for each layer
115
};
116
117
118 6 Julien Brule
</code>
119
</pre>
120
121 7 Julien Brule
The phase screens size is computed in agreement with the system components. The positions of the various targets (imaging targets or wavefront sensing guide stars) in the simulation define the required field of view and thus the size of the altitude phase screens.
122 6 Julien Brule
123 7 Julien Brule
To create a dynamic turbulence, the phase screens are extruded in columns and rows. The number of rows and columns extruded per iteration is computed using the specified wind speed and direction. Because extrusion is an integer operation (can't extrude a portion of a column), additional interpolation is required to provide an accurate model (with non integer phase shifts). In YoGA_Ao, a combination of integer extrusion and linear interpolation (in between four pixels) is used for each layer. The phase is integrated along specified directions across the multiple layers with the positions of light rays being re-evaluated for each iteration and screen ribbons being extruded when appropriate. This explains the need for a guard band around the ground layer phase screen as light rays can partly cross the pupil pixels depending on the iteration number.
124
125
The overall turbulence generation is done on the GPU and rely on a C++ class:
126
127
128 6 Julien Brule
<pre>
129
<code class="c">
130 7 Julien Brule
class yoga_tscreen
131 6 Julien Brule
</code>
132
</pre>
133
134 7 Julien Brule
This object contains all the elements to generate an infinite length phase screen including the extrusion method. All the screens for a given atmospheric configuration are centralized in another class:
135 6 Julien Brule
136 7 Julien Brule
137
138 6 Julien Brule
<pre>
139
<code class="c">
140 7 Julien Brule
class yoga_atmos
141
142 6 Julien Brule
</code>
143
</pre>
144
145 7 Julien Brule
In this object phase screens can be added dynamically thanks to the use of a map of yoga_tscreen This has many advantages the first of which being the indexation: screens are indexed by altitude (float) and the use of iterators greatly simplifies the code.
146
147
The corresponding Yorick opaque object is: 
148
149 6 Julien Brule
<pre>
150
<code class="c">
151 7 Julien Brule
 static y_userobj_t yAtmos
152 6 Julien Brule
</code>
153
</pre>
154
155 7 Julien Brule
and there are several Yorick wrappers to manipulate this object:
156
157 6 Julien Brule
<pre>
158
<code class="c">
159 7 Julien Brule
extern yoga_atmos;
160
    /* DOCUMENT yoga_atmos
161
       obj = yoga_atmos(nscreens,r0,size,size2,alt,wspeed,wdir,deltax,deltay,pupil[,ndevice])
162
       creates an yAtmos object on the gpu
163
    */
164 6 Julien Brule
</code>
165
</pre>
166
167
168
<pre>
169
<code class="c">
170 7 Julien Brule
extern init_tscreen;
171
    /* DOCUMENT init_tscreen
172
       init_tscreen,yoga_atmos_obj,altitude,a,b,istencilx,istencily,seed
173
       loads on the gpu in an yAtmos object and for a given screen data needed for extrude
174
    */
175 6 Julien Brule
</code>
176
</pre>
177
178
179
<pre>
180
<code class="c">
181 7 Julien Brule
extern get_tscreen;
182
    /* DOCUMENT get_tscreen
183
       screen = get_tscreen(yoga_atmos_obj,altitude)
184
       returns the screen in an yAtmos object and for a given altitude
185
    */
186 6 Julien Brule
</code>
187
</pre>
188
189
<pre>
190
<code class="c">
191 7 Julien Brule
extern get_tscreen_update;
192
    /* DOCUMENT get_tscreen_update
193
       vect = get_tscreen_update(yoga_atmos_obj,altitude)
194
       returns only the update vector in an yAtmos object and for a given altitude
195
    */
196 6 Julien Brule
</code>
197
</pre>
198
199
<pre>
200
<code class="c">
201 7 Julien Brule
extern extrude_tscreen;
202
    /* DOCUMENT extrude_tscreen
203
       extrude_tscreen,yoga_atmos_obj,altitude[,dir]
204
       executes one col / row screen extrusion for a given altitude in an yAtmos object 
205
    */
206 6 Julien Brule
</code>
207
</pre>
208
209
210 7 Julien Brule
Additionally there is a high-level routine to initialize the whole structure on the GPU from Yorick:
211 6 Julien Brule
212 7 Julien Brule
<pre>
213
<code class="c">
214
func atmos_init(void)
215
    /* DOCUMENT atmos_init
216
       atmos_init
217
       inits a yAtmos object on the gpu
218
       no input parameters
219
       requires 2 externals + 2 optional : y_atmos and y_geom + y_target and y_wfs
220
       y_atmos  : a y_struct for the atmosphere
221
       y_geom   : a y_struct for the geometry of the simulation
222
       y_target : a y_struct for the targets
223
       y_wfs    : a y_struct for the sensors
224
       creates 1 external :
225
       g_atmos : a yAtmos object on the gpu
226
    */
227 6 Julien Brule
228 7 Julien Brule
</code>
229
</pre>
230 6 Julien Brule
231
232
233
234 1 Julien Brule
h3. Wavefront Sensing
235 6 Julien Brule
236 7 Julien Brule
Wavefront sensing is done in two steps: first compute the Shack-Hartmann sub-images including diffraction effect and noise and then from these images, compute the centroids. The overall model is described here [[Model Description]].
237 6 Julien Brule
238 7 Julien Brule
The pixel size requested by the user for the sub-apertures images are approximated following a rather robust approach to cope for any kind of dimensioning. We used an empirical coefficient to set the simulated subaps field of view (FoV) to 6 times the ratio of the observing wavelength over r_0 at this wavelength. This provides sufficient FoV to include most of the turbulent speckles. The same empirical coefficient is used to define de number of phase points per subaps as 6 times the ratio of the subaps diameter over r_0. This ensures a proper sampling of r_0. From this number of phase points we compute the size of the support in the Fourier domain. The "quantum pixel size" is then deduced from the ratio of the wavelength over r_0 over the size of the Fourier support. Then the pixel size actually simulated is obtained using the product of an integer number by this quantum pixel size as close as possible to the requested pixel size.
239
240
The wavefront sensor model description is stored in the following Yorick structure. 
241
242 6 Julien Brule
<pre>
243
<code class="c">
244 7 Julien Brule
struct wfs_struct
245
{
246
  long  nxsub;          // linear number of subaps
247
  long  npix;           // number of pixels per subap
248
  float pixsize;        // pixel size (in arcsec) for a subap
249
  float lambda;         // observation wavelength (in µm) for a subap
250
  float optthroughput;  // wfs global throughput
251
  float fracsub;        // minimal illumination fraction for valid subaps
252
  
253
  //target kwrd
254
  float xpos;      // guide star x position on sky (in arcsec) 
255
  float ypos;      // guide star x position on sky (in arcsec) 
256
  float gsalt;     // altitude of guide star (in m) 0 if ngs 
257
  float gsmag;     // magnitude of guide star
258
  float zerop;     // detector zero point
259
  
260
  // lgs only
261
  float lgsreturnperwatt;  // return per watt factor (high season : 10 ph/cm2/s/W)
262
  float laserpower;        // laser power in W
263
  float lltx;              // x position (in meters) of llt
264
  float llty;              // y position (in meters) of llt
265
  string proftype;         // type of sodium profile "gauss", "exp", etc ...
266
  float beamsize;          // laser beam fwhm on-sky (in arcsec)
267
...
268
};
269
270 6 Julien Brule
</code>
271
</pre>
272
273
274
275 1 Julien Brule
h3. Image formation
276
277 6 Julien Brule
<pre>
278
<code class="c">
279 7 Julien Brule
struct target_struct
280
{
281
  long    ntargets;  // number of targets
282
  pointer lambda;    // observation wavelength for each target
283
  pointer xpos;      // x positions on sky (in arcsec) for each target
284
  pointer ypos;      // y positions on sky (in arcsec) for each target
285
  pointer mag;       // magnitude for each target
286
};
287 6 Julien Brule
</code>
288
</pre>
289
290
291
292
293
294 4 Julien Brule
h2. List of routines
295 8 Julien Brule
296 1 Julien Brule
h3. High-level routines
297 8 Julien Brule
298 1 Julien Brule
h3. Advanced routines
299 6 Julien Brule
300
301
<pre>
302
<code class="c">
303 7 Julien Brule
extern _GetMaxGflopsDeviceId  //get the ID of the best CUDA-capable device on your system
304 6 Julien Brule
</code>
305
</pre>