Wide-field wavefront sensing in Solar Adaptive Optics - its modeling and its effects on reconstruction Clémentine Béchet, Michel Tallon, Iciar Montilla, Maud Langlois Centre de Recherche Astrophysique de Lyon (CRAL) Instituto de Astrofisica de Canarias (IAC) May 2013, AO4ELT3 (Florence, Italy)

Outline 1.Context: AO for the 4-m diameter European Solar Telescope (EST) a)EST AO goals b)preliminary design 2.Wavefront sensing in solar AO a)reminder on solar AO wavefront sensing b)anisoplanatism in wide-field sensor data 1.A model for wide-field wavefront sensing a)for more realistic data simulation b)for reconstruction? 2.Conclusions & Future work

 Collaboration with Instituto Astrofisica de Canarias (I. Montilla)  Not a 30-m class telescope, just a 4-m one, but… –wide-field correction for high strehl at visible wavelengths –complexity close to TMT, GMT or E-ELT AO systems  construction > 1st light 2025  EST AO goals : ambitious! –correction abilities over a wide range of elevations (down to 15 degrees) –requirements over a corrected fov of 1’ diameter:  Strehl (500nm) > 30% for r0 = 7cm  Strehl (500nm) > 50% for r0 = 14cm  Strehl (500nm) > 60% for r0 = 20cm 1. Context : AO for the 4-m diameter European Solar Telescope (EST)

 EST AO system preliminary design –5 DMs to cover a wide range of elevations –1 on-axis (10”x10”) high-order Shack-Hartmann WFS –1 “over-the-field” (70”x70”) low-order Shack-Hartmann WFS –sensed fields of 10”x10” for both SH-WFS – kHz frame-rate for cross-correlating sensed fields  designed from an budget error and Fourier code analysis (Berkefeld & Soltau, 2010)  … but requires end-to-end simulations AOMCAO DMs heights0 km0, 2, 6, 10, 23 km DMs spacings8 cm (~1800 act.)8, 30, 30, 30, 30 cm (~ 4000 act.) sensing fields1 (10”x10”)19 (10”x10”) subap. size8 cm (~1800 in total)8 cm, 30cm (128 subaps. in total) 1. Context : AO for the 4-m diameter European Solar Telescope (EST)

 Why end-to-end simulations? –lessons learned from E-ELT phase A studies, of huge difficulties to provide an exhaustive and clear error budget, error term by error term, for tomography –experienced limitation of Fourier codes Octopus+FRiM-3D in closed-loop : E2E FRiM-3D reconstruction only: E2E Octopus+other reconstructor: E2E Fourier code from ONERA Le Louarn et al. SPIE 2012 ATLAS/LTAO E2E simulations to determine the impact of LGS constellation radius on Strehl Octopus : ESO E2E AO simulator 1. Context : AO for the 4-m diameter European Solar Telescope (EST)

 Why end-to-end simulations? –lessons learned from E-ELT phase A studies, of huge difficulties to provide an exhaustive and clear error budget, error term by error term, for tomography –experienced limitation of Fourier codes  need of a fast simulator for very large AO systems –Octopus (ESO end-to-end simulator for AO)  cluster of hundreds of slaves  diffractive model –FRiM-3D (CRAL developments)  sparse/fast modeling operators,  geometric models,  works even on an old laptop  started ESTAO E2E simulations (Montilla et al. SPIE 2012 and a poster this week) but needed new developments of FRiM-3D to adapt it to solar AO => focus of this talk: anisoplanatism in the AO wavefront sensing 1. Context : AO for the 4-m diameter European Solar Telescope (EST)

a)solar wavefront sensing in a nutshell –key approach = cross- correlating SH-WFS –fov of 5”x5” minimum (von der L ü he, 1983) to track gradients on granulation – more robust if fov larger than 8 ’’ x8 ’’ 2. Wavefront sensing in solar AO (VTT example, von der Lühe et al., 2005)

a)solar wavefront sensing in a nutshell –key approach = cross- correlating SH-WFS –fov of 5”x5” minimum (von der L ü he, 1983) to track gradients on granulation – more robust if fov larger than 8 ’’ x8 ’’  combination of high-order WFS and 19 sensed fields (~10”x10”) in 70”x70” low-order WFS  but 10” is usually larger than the isoplanatic patch (500nm) 2. Wavefront sensing in solar AO (VTT example, von der Lühe et al., 2005)

b)Anisoplanatism effect on data 2. Wavefront sensing in solar AO 3”x3” 50cm subap.  small & usually negligible fov in night-time AO

b)Anisoplanatism effect on data – cross-correlation over 10” fov = average gradient over the subap. and over the fov. –independent contribution of each layers –with increasing height, averaging over a wider layer area –loosing sensitivity of the on-axis wavefront distortions at high altitude 2. Wavefront sensing in solar AO 10”x10” 10cm subap.  wide-field solar AO sensing

b)Anisoplanatism effect on data – cross-correlation over 10” fov = average gradient over the subap. and over the fov. –independent contribution of each layers –with increasing height, averaging over a wider layer area –loosing sensitivity of the on- axis wavefront distortions at high height –same conditions as Marino 2012 (Haleakala profile, no strong layer in high altitude) simulated with FRiM-3D 2. Wavefront sensing in solar AO  4m-diameter, 10cm subaps.  reconstruction error only (noiseless) fitting

b)Anisoplanatism effect on data – cross-correlation over 10’’ fov = average gradient over the subap. and over the fov. –independent contribution of each layers –with increasing height, averaging over a wider layer area –loosing sensitivity of the on-axis wavefront distortions at high height –same conditions as Marino 2012 (Haleakala profile, no strong layer in high altitude) simulated with FRiM-3D 2. Wavefront sensing in solar AO  4m-diameter, 10cm subaps.  reconstruction error only (noiseless) fitting  We need to model the wide-field wavefront sensing in solar E2E simulations

a)for more realistic simulations by FRiM-3D – “small fov” model already from night-time AO – based on continuous interpolation functions to model the turbulent layers – “wide-field” solar model : includes the average over the fov F, introducing enough subdirections for sensing 3. A model for wide-field wavefront sensing contribution per layer ideally 0” new!

a)for more realistic simulations by FRiM-3D  anisoplanatism contribution to data, per layer : 3. A model for wide-field wavefront sensing

a)for more realistic simulations by FRiM-3D  anisoplanatism contribution to data, per layer :  for a complete profile, contribution of layers can be added in variance  for examples: –E-ELT profile (MAORY phase A) –Cerror Pachon median profile – Haleakala profile (Marino 2012) –wfs fov = 8” x 8” –r 0 = 15cm –zenith angle = 60 deg.  ~ 40nm rms 3. A model for wide-field wavefront sensing

b)for the reconstruction?  FRiM-3D can use various fast models of SH sensing in its minimum- variance reconstruction algorithm 3. A model for wide-field wavefront sensing

b)for the reconstruction?  FRiM-3D can use various fast models of SH sensing in its minimum- variance reconstruction algorithm “small-fov” “wide-fov” with n subdir = 4 10” only 1 reconstructed layer several reconstructed layers 3. A model for wide-field wavefront sensing

b)for the reconstruction?  FRiM-3D can use various fast models of SH sensing in its minimum- variance reconstruction algorithm “small-fov” “wide-fov” with n subdir = 4 10” only 1 reconstructed layer several reconstructed layers 3. A model for wide-field wavefront sensing is there a benefit in using S 4 in the reconstruction?

b)for the reconstruction? § toy case #1 : 1 simulated layer only 3. A model for wide-field wavefront sensing fitting

b)for the reconstruction? § toy case #1 : 1 simulated layer only 3. A model for wide-field wavefront sensing fitting

b)for the reconstruction? § toy case #1 : 1 simulated layer only 3. A model for wide-field wavefront sensing  probable benefit since S 4 allows to reconstruct layers in altitude… fitting

b)for the reconstruction? § toy case #2 : 1 simulated layer only 2 reconstructed layers: at 0 km and another height h 3. A model for wide-field wavefront sensing fitting

b)for the reconstruction? § toy case #2 : 1 simulated layer only 2 reconstructed layers: at 0 km and another height h 3. A model for wide-field wavefront sensing ??? fitting

b)for the reconstruction? § toy case #2 : 1 simulated layer only 2 reconstructed layers: at 0 km and another height h 3. A model for wide-field wavefront sensing ???  benefit from S 4 is strongly related to the priors! fitting

b)for the reconstruction? § Complete atmosphere reconstruction (Haleakala profile, Marino 2012) 3. A model for wide-field wavefront sensing  at the end of the day, no quantitative benefit from S 4 in single-sensor reconstruction  checked for various profiles, elevations, seeing, noise levels, …  the average of the data over the field of view definitely degrade the possible performance

4. Conclusions & future work  challenging AO system for the future European solar telescope  simulations of the system started in collaboration between CRAL and IAC  to understand new issues of solar AO ( e.g. anisoplanatism for SCAO)  to consolidate the error budget (anisoplanatism, 5 DMs, low-order sensing, high-order sensing)  simulator FRiM-3D, developed at CRAL, now allows to model the anisoplanatism in the wide-field data  anisoplanatism error can range from a few nm rms to 100 nm rms (for bad conditions)  the use of an approximated model with 4 subdirections in the reconstructor does not significantly reduces the drop of the SCAO Strehl due to the sensing anisoplanatism  anisoplanatism can now however be simulated in solar MCAO mode (on-going EST and Big Bear simulations with FRiM-3D), and we will evaluate how much it could be canceled by the tomographic correction Posters: I. Montilla et al. (ESTAO), M. Langlois et al. (Big Bear)