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M ulti- O bject C urvature wa V efront S ensor ( MOCVS )

M ulti- O bject C urvature wa V efront S ensor ( MOCVS ). B. Femenía (GTC, Spain) J. Castro (GTC, Spain) N. Devaney (Univ. Galway, Ireland) Leiden. April 26-29, 2005. Motivation. Benefit from optical co-addition from several NGS. How this works....(1/3). 1-Record defocused pupil images.

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M ulti- O bject C urvature wa V efront S ensor ( MOCVS )

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  1. Multi-Object Curvature waVefront Sensor (MOCVS) B. Femenía (GTC, Spain) J. Castro (GTC, Spain) N. Devaney (Univ. Galway, Ireland) Leiden. April 26-29, 2005

  2. Motivation Benefit from optical co-addition from several NGS.

  3. How this works....(1/3) 1-Record defocused pupil images

  4. How this works....(2/3) 2-Reconstruct on-axis defocused pupils. Assume prior knowledge of object distribution

  5. Cf standard curvature PDE How this works.... (3/3) 3-Solve PDE obtained by assuming ITE

  6. Wavefront Reconstruction Average result: SR=0.70 ± 0.12 Standard Case: SR=0.79 ± 0.13

  7. Useful for: • Layer Oriented MCAO • Ground Layer AO Benefits of MOCVS are: Light is split into 2 planes (3 planes in MCAO) Extremely simple to implement A side product is how to implement Curvature Wavefront sensing with CCDs without additional optics (i.e. Keystone lenslets).

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