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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

Multi-Object Curvature waVefront Sensor (MOCVS)

B. Femenía (GTC, Spain)

J. Castro (GTC, Spain)

N. Devaney (Univ. Galway, Ireland)

Leiden. April 26-29, 2005


Motivation
Motivation

Benefit from optical co-addition from several NGS.


How this works 1 3
How this works....(1/3)

1-Record defocused pupil images


How this works 2 3
How this works....(2/3)

2-Reconstruct on-axis defocused pupils.

Assume prior knowledge of object distribution


How this works 3 3

Cf standard curvature PDE

How this works.... (3/3)

3-Solve PDE obtained by assuming ITE


Wavefront reconstruction
Wavefront Reconstruction

Average result:

SR=0.70 ± 0.12

Standard Case:

SR=0.79 ± 0.13


Useful for
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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