Browsing by Author "Myers, Richard"

Now showing 1 - 3 of 3
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    Deformable mirror model for open-loop adaptive optics using multivariate adaptive regression splines
    (OPTICAL SOC AMER, 2010) Guzman, Dani; de Cos Juez, Francisco Javier; Sanchez Lasheras, Fernando; Myers, Richard; Young, Laura
    Open-loop adaptive optics is a technique in which the turbulent wavefront is measured before it hits the deformable mirror for correction. We present a technique to model a deformable mirror working in open-loop based on multivariate adaptive regression splines (MARS), a non-parametric regression technique. The model's input is the wavefront correction to apply to the mirror and its output is the set of voltages to shape the mirror. We performed experiments with an electrostrictive deformable mirror, achieving positioning errors of the order of 1.2% RMS of the peak-to-peak wavefront excursion. The technique does not depend on the physical parameters of the device; therefore it may be included in the control scheme of any type of deformable mirror. (C) 2010 Optical Society of America
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    Modeling a MEMS deformable mirror using non-parametric estimation techniques
    (OPTICAL SOC AMER, 2010) Guzman, Dani; de Cos Juez, Francisco Javier; Myers, Richard; Guesalaga, Andres; Sanchez Lasheras, Fernando
    Using non-parametric estimation techniques, we have modeled an area of 126 actuators of a micro-electro-mechanical deformable mirror with 1024 actuators. These techniques produce models applicable to open-loop adaptive optics, where the turbulent wavefront is measured before it hits the deformable mirror. The model's input is the wavefront correction to apply to the mirror and its output is the set of voltages to shape the mirror. Our experiments have achieved positioning errors of 3.1% rms of the peak-to-peak wavefront excursion. (C) 2010 Optical Society of America
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    Using artificial neural networks for open-loop tomography
    (OPTICAL SOC AMER, 2012) Osborn, James; De Cos Juez, Francisco Javier; Guzman, Dani; Butterley, Timothy; Myers, Richard; Guesalaga, Andres; Laine, Jesus
    Modern adaptive optics (AO) systems for large telescopes require tomographic techniques to reconstruct the phase aberrations induced by the turbulent atmosphere along a line of sight to a target which is angularly separated from the guide sources that are used to sample the atmosphere. Multi-object adaptive optics (MOAO) is one such technique. Here, we present a method which uses an artificial neural network (ANN) to reconstruct the target phase given off-axis references sources. We compare our ANN method with a standard least squares type matrix multiplication method and to the learn and apply method developed for the CANARY MOAO instrument. The ANN is trained with a large range of possible turbulent layer positions and therefore does not require any input of the optical turbulence profile. It is therefore less susceptible to changing conditions than some existing methods. We also exploit the non-linear response of the ANN to make it more robust to noisy centroid measurements than other linear techniques. (C) 2012 Optical Society of America