Multi-Conjugate Adaptive Optics
Introduction

Multi-Conjugate Adaptive Optics (MCAO)

MCAO team at ESO:

Norbert Hubin nhubin@eso.org

Rodolphe Conan rconan@eso.org

Miska Le Louarn lelouarn@eso.org

Enrico Marchetti emarchet@eso.org

Andrei Tokovinin (ex-member, now CTIO) atokovin@eso.org

Elise Viard (ex-member, now Padova) eviard@eso.org

MCAO and Tomography

Using several Guide Stars (GS), it is possible to reconstruct the 3-D atmospheric perturbations from the measurement of the wave-fronts. This concept is called turbulence tomography, similar in its principle to medical tomography. Several Wave-Front Sensors (WFS) are needed for tomography.

Why do we need turbulence tomography?

To get the information for wave-front correction from distant Natural Guide Stars (NGS)
To correct the cone effect when using Laser Guide Stars (LGS)
To drive several Deformable Mirrors (DMs)

When several DMs are driven by the signals derived from tomography, the size of the corrected Field of View (FoV) increases. This is called Multi-Conjugate Adaptive Optics (MCAO). The DMs are optically conjugated to different heights and perform a 3-D correction of turbulence.

Why do we need MCAO?

Correct a larger FoV to image large celestial objects and to use telescope time more efficiently
Obtain more uniform correction over the FoV, hence data of better quality
Improve the chance to find an NGS in a larger FoV (increase sky coverage)

Alternative approaches to MCAO

The scheme described in the previous sections is often called "classical MCAO" or "global MCAO", since all the measurements are combined in one reconstructor. It has been suggested by Ragazzoni et al. to proceed in a different manner. One could conjugate one wavefront sensor to each deformable mirror and optically coadd the light of many (natural) guide stars on the detector. The advantage of this so called "layer oriented approach" is that one needs only as many wavefront sensors as deformable mirrors. Many faint stars can be use at low cost, since the wavefront sensor is usually a very expensive part of an AO system. Also, since light is coadded onto the detector, very faint stars can also be sensed.

More information on this method, see a presentation of the general method, and a paper by R. Ragazzoni et al.

To investigate this method in practice, a layer-oriented wavefront sensing module is beng implemented into the MCAO demonstrator, MAD

Potential of MCAO

With classical Adaptive Optics (AO) turbulence can be corrected only partially for the two reasons: the amount of information on wave-front distortion is limited by the brightness of GS, and the spatial scale of the corrected corrugations is limited by the number of DM actuators. Hence, it is easier to correct in the infra-red than in the visible band.

With MCAO, some of these limits can be extended. Using bright LGS and correcting the cone effect by tomography opens the way to push AO into the visible band (however, the high-resolution DMs are not yet available to do this now).

With 2 or 3 DMs, the corrected FoV is widened 2-10 times compared to the classical AO and can reach few arcminutes in the K band. The FoV of MCAO is limited by the residual atmospheric anisoplanatism, arising both from incomplete tomographic information available from few GSs and from incomplete correction of the whole 3D turbulent volume with only few DMs.

Although MCAO is not a magic solution, it offers a much increased scientific potential to next-generation adaptive optics systems.

First page version create Nov 09, 2000 by A. Tokovinin

Multi-Conjugate Adaptive Optics
Introduction

Multi-Conjugate Adaptive Optics (MCAO)

MCAO team at ESO:

MCAO demonstrator

Theory and simulations

Papers

Collaborations

MCAO and Tomography

Alternative approaches to MCAO

Potential of MCAO

Multi-Conjugate Adaptive OpticsIntroduction

Multi-Conjugate Adaptive Optics (MCAO)

MCAO team at ESO:

MCAO demonstrator

Theory and simulations

Papers

Collaborations

MCAO and Tomography

Alternative approaches to MCAO

Potential of MCAO

Multi-Conjugate Adaptive Optics
Introduction