Dr. Carine Morel Profile

Dr. Carine Morel

Research Engineer at Lab d'Etudes Spatiales et d'Instrumentation en As

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Publications (8)

Proceedings Article | 13 July 2018 Presentation + Paper

Phase A AO system design and performance for MOSAIC at the ELT

Timothy Morris, Alastair Basden, Ariadna Calcines-Rosario, Kjetil Dohlen, Cornelis Dubbeldam, Kacem El Hadi, Ewan Fitzsimons, Thierry Fusco, Éric Gendron, François Hammer, Pascal Jagourel, David Jenkins, Carine Morel, Simon Morris, Gérard Rousset, Matthew Townson, Pascal Vola, Edward Younger

Proceedings Volume 10703, 1070316 (2018) https://doi.org/10.1117/12.2313562

KEYWORDS: Adaptive optics, Calibration, Control systems, Tomography, Deformable mirrors, Error analysis

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Proceedings Article | 5 October 2016 Paper

Validation of tomographic laser guide star uplink tip-tilt determination with CANARY

Andrew Reeves, Timothy Morris, Richards Myers, Alastair Basden, Eric Gendron, Carine Morel, James Osborn, Gerard Rousset, Fabrice Vidal

Proceedings Volume 9909, 99091Y (2016) https://doi.org/10.1117/12.2232395

KEYWORDS: Wavefront sensors, Adaptive optics, Tomography, Turbulence, Laser guide stars, Stars, Sensors, Matrices, Astronomy, Telescopes

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Proceedings Article | 27 July 2016 Paper

Turbulence profiling for adaptive optics tomographic reconstructors

Douglas Laidlaw, James Osborn, Richard Wilson, Timothy Morris, Timothy Butterley, Andrew Reeves, Matthew Townson, Éric Gendron, Fabrice Vidal, Carine Morel

Proceedings Volume 9909, 99093I (2016) https://doi.org/10.1117/12.2233323

KEYWORDS: Adaptive optics, Turbulence, Profiling, Tomography, Telescopes, Adaptive optics, Turbulence, Tomography, Profiling, Atmospheric optics, Matrices, Data analysis, Wavefronts, Signal to noise ratio

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Proceedings Article | 27 July 2016 Paper

Pseudo-analytic simulation of woofer-tweeter MOAO system: application to MOSAIC

Carine Morel, Éric Gendron, Damien Gratadour, Arnaud Sevin, Gérard Rousset

Proceedings Volume 9909, 990976 (2016) https://doi.org/10.1117/12.2232429

KEYWORDS: Tomography, Computer simulations, Reconstruction algorithms, Matrices, Actuators, Adaptive optics, Point spread functions, Computer simulations, Device simulation, Deformable mirrors, Sensors

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Proceedings Article | 26 July 2016 Paper

Adaptive optics for MOSAIC: design and performance of the wide(st)-field AO system for the E-ELT

Tim Morris, Alastair Basden, Tristan Buey, Fanny Chemla, Jean-Marc Conan, Ewan Fitzsimons, Thierry Fusco, Eric Gendron, Francois Hammer, Pascal Jagourel, Carine Morel, Richard Myers, Benoit Neichel, Cyril Petit, Myriam Rodrigues, Gérard Rousset

Proceedings Volume 9909, 99091I (2016) https://doi.org/10.1117/12.2232411

KEYWORDS: Adaptive optics, Tomography, Optical design, Spectrographs, Telescopes, Near infrared, Optical design, Wavefronts, Monte Carlo methods, Device simulation, Stars

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Proceedings Article | 26 July 2016 Paper

Final two-stage MOAO on-sky demonstration with CANARY

E. Gendron, T. Morris, A. Basden, F. Vidal, D. Atkinson, U. Bitenc, T. Buey, F. Chemla, M. Cohen, C. Dickson, N. Dipper, P. Feautrier, J.-L. Gach, D. Gratadour, D. Henry, J.-M. Huet, C. Morel, S. Morris, R. Myers, J. Osborn, D. Perret, A. Reeves, G. Rousset, A. Sevin, E. Stadler, G. Talbot, S. Todd, E. Younger

Proceedings Volume 9909, 99090C (2016) https://doi.org/10.1117/12.2231432

KEYWORDS: Adaptive optics, Tomography, Adaptive optics, Sensors, Telescopes, Mirrors, Deformable mirrors, Cameras, Stars, Actuators, Infrared cameras

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Proceedings Article | 7 August 2014 Paper

Robustness of tomographic reconstructors versus real atmospheric profiles in the ELT perspective

E. Gendron, C. Morel, J. Osborn, O. Martin, D. Gratadour, F. Vidal, M. Le Louarn, G. Rousset

Proceedings Volume 9148, 91484N (2014) https://doi.org/10.1117/12.2055809

KEYWORDS: Tomography, Wavefronts, Adaptive optics, Telescopes, Matrices, Point spread functions, Stars, Turbulence, Device simulation, Computer simulations

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Proceedings Article | 4 August 2014 Paper

A novel fast and accurate pseudo-analytical simulation approach for MOAO

É. Gendron, A. Charara, A. Abdelfattah, D. Gratadour, D. Keyes, H. Ltaief, C. Morel, F. Vidal, A. Sevin, G. Rousset

Proceedings Volume 9148, 91486L (2014) https://doi.org/10.1117/12.2055911

KEYWORDS: Tomography, Point spread functions, Matrices, Adaptive optics, Actuators, Computer simulations, Error analysis, Computing systems, Wavefronts, Device simulation

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Multi-object adaptive optics (MOAO) is a novel adaptive optics (AO) technique for wide-field multi-object spectrographs (MOS). MOAO aims at applying dedicated wavefront corrections to numerous separated tiny patches spread over a large field of view (FOV), limited only by that of the telescope. The control of each deformable mirror (DM) is done individually using a tomographic reconstruction of the phase based on measurements from a number of wavefront sensors (WFS) pointing at natural and artificial guide stars in the field. We have developed a novel hybrid, pseudo-analytical simulation scheme, somewhere in between the end-to- end and purely analytical approaches, that allows us to simulate in detail the tomographic problem as well as noise and aliasing with a high fidelity, and including fitting and bandwidth errors thanks to a Fourier-based code. Our tomographic approach is based on the computation of the minimum mean square error (MMSE) reconstructor, from which we derive numerically the covariance matrix of the tomographic error, including aliasing and propagated noise. We are then able to simulate the point-spread function (PSF) associated to this covariance matrix of the residuals, like in PSF reconstruction algorithms. The advantage of our approach is that we compute the same tomographic reconstructor that would be computed when operating the real instrument, so that our developments open the way for a future on-sky implementation of the tomographic control, plus the joint PSF and performance estimation. The main challenge resides in the computation of the tomographic reconstructor which involves the inversion of a large matrix (typically 40 000 × 40 000 elements). To perform this computation efficiently, we chose an optimized approach based on the use of GPUs as accelerators and using an optimized linear algebra library: MORSE providing a significant speedup against standard CPU oriented libraries such as Intel MKL. Because the covariance matrix is symmetric, several optimization schemes can be envisioned to speedup even further the computation. Optimizing the speed of the reconstructor computation is of major interest not only for the design study of MOAO instruments, but also for future routine operations of the system as the reconstructor has to be updated regularly to cope for atmospheric variability.

Showing 5 of 8 publications

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