Minisymposia Abstracts
| Speaker: | Brent Ellerbroek TMT project Office |
| Title: | Progress in Atmospheric Tomography Methods for Extremely Large Telescopes over the Past Decade | Abstract: | TBA
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| Speaker: | Andreas Neubauer Johannes Kepler University |
| Title: | Cumulative wavefront reconstructor for the Shack-Hartmann sensor | Abstract: | TBA
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| Speaker: | Simone Esposito Osservatorio Astrofisico di Arcetri |
| Title: | Wavefront Reconstruction for the AO system FLAO of Large Binocular Telescope (LBT) | Abstract: |
TBA |
| Speaker: | Clementine Bechet ESO, Munich |
| Title: | Algorithms for fast wavefront reconstruction and model update : needs for next generation Adaptive Optics | Abstract: | The astrophysical objectives of the future Extremely Large
Telescopes (ELTs) will be achieved only with innovative Adaptive Optics (AO)
systems to compensate the wavefront distortions induced by the turbulence in
the atmosphere above the telescope. The challenge is to cope with a huge jump
in size and complexity of the future AO systems, such that the wavefront correct
ion requires to be done faster, better and in a smarter way than in the existing
systems.
The Fractal Iterative Method (FriM) has been developed to provide a fast
algorithm for Minimum-Variance reconstruction and control on ELTs. The principle
of the algorithm based on the "inverse approach" is presented, as well as its
performance results on European Southern Observatory end-to-end AO simulator.
We show successful tests of single conjugate AO, and ground-layer AO, as well
as first results of AO with tomography (MCAO). In that way, we emphasize remark
able benefits of our approach with respect to complexity, closed-loop configuration,
noise correlation in wavefront sensing, and tomography quality. In a second part, we extend the inverse approach to investigate the update of non-stationary model parameters involved in FriM, or any other AO control. The problem of system parameters identification in closed-loop AO is investigated here, which is critical for next generation AO. We introduce a novel iterative method in that purpose. First simulations results enhance the ability to retrieve internal model parameters directly from data, without introducing additional disturbance. |
| Speaker: | Ronny Ramlau Johannes Kepler University |
| Title: | Iterative Reconstructors for Multi Conjugate Adaptive Optics | Abstract: | TBA
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| Speaker: | Curtis Vogel The Optical Science Company |
| Title: | Modeling and parameter estimation for deformable mirrors used in ground-based astronomical adaptive optics | Abstract: | TBA
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| Speaker: | Francois-Xavier Dupe Laboratoire de Cosmologie et Statistiques |
| Title: | Recovering the galaxy density | Abstract: | TBA
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| Speaker: | Adrienne Leonard Pisa |
| Title: | Compressed Sensing for Weak Lensing | Abstract: | Weak gravitational lensing allows us to map the distribution of matter
in the universe by measuring the small distortions to galaxy images arising due to the gravitational
potential along the line of sight. The measured shear is effectively a convolution of the matter
overdensity with a broad radial kernel encoding geometrical information. Therefore, the weak lensing problem
can be modeled as an instance of compressed sensing, as we know that the matter overdensity is mostly
sparse in some wavelets domains. In this case, the sensing operator models an integration along each line of sight,
from low redshift (i.e. close distance) to high redshift (i.e. far away distance). Then, we exploit current results on
the compress sensing theory in order to build an efficient method for estimating the matter density along lines of
sight using most of the theoretical knowledge available. More precisely, the reconstruction problem is cast as a
constraints convex optimization problem, where we seek a sparse solution under data fidelity constraints. We also
characterize the solution and prove the convergence of the global scheme. The results show that we are able to reconstruct
the matter cluster in different redshifts without the smooth and shift issues that occur in the current state-of-art methods.
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Please address administrative questions to aipc@math.tamu.edu. Scientific questions should be addressed to the chair of the Scientific Program Committee: rundell AT math.tamu.edu