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1 Characterization of the T/T conditions at Gemini Using AO data Jean-Pierre Véran Lisa Poyneer AO4ELT Conference - Paris June 22 - 26, 2009.

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Presentation on theme: "1 Characterization of the T/T conditions at Gemini Using AO data Jean-Pierre Véran Lisa Poyneer AO4ELT Conference - Paris June 22 - 26, 2009."— Presentation transcript:

1 1 Characterization of the T/T conditions at Gemini Using AO data Jean-Pierre Véran Lisa Poyneer AO4ELT Conference - Paris June 22 - 26, 2009

2 2 Motivation Good AO correction requires T/T to be corrected to a residual << than the size of the diffraction limited spot: –For ELT, this corresponds to a few mas rms –This level of correction has never been achieved so far High contrast imagers on 8-meter class telescopes have similar requirements (coronograph) –GPI: requirement 5 mas rms (tip+tilt); goal: 3 mas rms (tip+tilt) T/T can have different sources, not very well characterized –Atmospheric turbulence –Telescope windshake –Vibrations originating from telescope systems and/or instruments Can we learn anything on the actual T/T conditions at Gemini from the various wave-front sensors currently in operation on the telescope ? Do we need to implement mitigation strategies: –Improved control algorithm ? –Dedicated T/T WFS at higher sampling rate ?

3 3 Total tilt: 116 mas rms T/T from atmospheric turbulence: easy, in theory Total residual tilt: 0.9 mas rms (simple integral controller)

4 4 WFS telemetry data from Gemini P2 and OIWFS data (200 Hz, open loop) –7 CBs from GN and 5 CBs from GS (March 2007) Altair data (1 kHz, closed loop) 61 CBs from Gemini North (2007-2008) Acquired during M1 tuning NICI data (1.3 kHz, closed loop) 46 usable CBs, mostly from one run (November 09) Closed loop data have to be turned into open-loop data –Use model of the AO rejection transfer function –Accurate knowledge of system calibration is required

5 5

6 6 Typical NICI PSD Dashed line: measured residual T/T Solid line: reconstructed incoming T/T Dotted lines: power -3 fit + noise level Reconstructed incoming T/T always decreases as a ~-3 power law, much slower than -17/3 Residuals after rejection of a GPI type system are still very high (> 10 mas rms) due to slow drop-off Is the -3 drop-off real or is it a Measurement artifact ?

7 7 Aliasing effect revealed by simulations White curves: Original incoming tilt (solid) -6 power law fit (dotted) Green curves: Incoming tilt reconstructed from telemetry (solid) power law fit (dotted): -4 (top) -6 (bottom) Measured residuals (dashed)

8 8 Modeling the aliasing effect At least 97% of the estimated GPI residual power is an artifact of spatial aliasing on NICI WFS True GPI residual rms is no more 15% than GPI residual computed from telemetry data

9 9 If all low frequency T/T is atmospheric turbulence T/T… Fit an inverse polynomial to reconstructed T/T in [10,50] Hz range. Apply GPI rejection transfer function and discount residual rms by 85% Average atmospheric T/T residual @ r0 = 0.145 cm is ~ 1.7 mas rms at 2 kHz CAVEAT: Aliasing might hide windshake Windshake is not affected by aliasing and Should not be discounted !!!

10 10 High frequency vibration background 279 Hz vibration gets amplified by a factor 2.16 (rms) by a 2 kHz GPI rejection transfer function (simple integral controller) 279 Hz vibration changes in amplitude: 2.1 mas rms +/- 0.8 mas rms Total GPI residual @ 2 kHz, r0=14.5cm 4.8 mas rms +/- 0.8 mas rms Total GPI residual @ 3 kHz, r0=14.5cm 1.6 mas rms +/- 0.4 mas rms

11 11 Vibration mitigation strategies Kalman filter, using the framework already in place in GPI for predictive control of the Fourier modes (T/T excluded) – L. Poyneer, B. Macintosh and J.-P. Véran, Fourier transform wavefront control with adaptive prediction of the atmosphere, J. Opt. Soc. Am. A, Vol. 24, pp. 2645, 2007. Formalism can be readily extended to handle vibrations –Vibrations considered as colored noise: L. Poyneer, et al., in preparation –Similar approach to: C. Petit, J. M. Conan, C. Kulcsar, H. F. Raynaud, and T. Fusco, First laboratory validation of vibration filtering with LQG control law for adaptive optics, Opt. Exp.16, 87–97, 2008. Effect is to tailor the rejection transfer function to: –Notch out vibrations if in science path –Ignore vibrations if in WFS path Other possible vibration mitigation strategies include: –Explicit notch filter built into the AO controller –Using local pure oscillators whose frequencies and phases are continuously updated by a phase-locked loop: Di Lieto et al., SPIE Marseille, 2008 Common path vibrations Non-common path vibration

12 12 Excess low/mid frequency T/T mitigation strategies Increase rejection by using a type II controller –Double integrator with a lead filter –Suitable for woofer-tweeter control. Current baseline for NFIRAOS See Wang et al., this conference See Véran et al., OSA San Jose conference Oct 09

13 13 Conclusions Spatial aliasing severely limits what we can learn about T/T conditions from AO WFS data –Also affects Shack-Hartmann WFS, although possibly less so Subtraction of a simple model of the aliasing is possible, but would hide windshake NICI telemetry data reveal several high frequency vibration lines that would severely limit GPI at 2 kHz –Mostly a ~ 2 mas rms vibration at 279 Hz –GPI would barely meet its 5 mas rms residual requirement –Such high frequency vibration is likely to come from within NICI Mitigation strategies exist: –Kalman filtering for vibrations –Type II controller for windshake


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