Carlos González Gutiérrez, Jesús Daniel Santos Rodríguez , Ramón Ángel Fernández Díaz , José Luis Calvo Rolle , Nieves Roqueñí Gutiérrez , Francisco Javier de Cos Juez
The next generation of adaptive optics (AO) systems require tomographic techniques in order to correct for atmospheric turbulence along lines of sight separated from the guide stars. Multi-object adaptive optics(MOAO) is one such technique. Here we present an improved version of CARMEN, a tomographic reconstructor based on machine learning, using a dedicated neural network framework as Torch. We can observe a significant improvement on the training an execution times of the neural network, thanks to the use of the GPU.
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