machine learning

Self-optimizing adaptive optics control with reinforcement learning for high-contrast imaging

Current and future high-contrast imaging instruments require extreme adaptive optics systems to reach contrasts necessary to directly imaged exoplanets. Telescope vibrations and the temporal error induced by the latency of the control loop limit the …

Self-optimizing adaptive optics control with reinforcement learning

Current and future high-contrast imaging instruments require extreme Adaptive Optics (XAO) systems to reach contrasts necessary to directly image exoplanets. Telescope vibrations and the temporal error induced by the latency of the control loop limit …

Use of neural networks in ground-based aerosol retrievals from multi-angle spectropolarimetric observations

In this paper, the use of a neural network algorithm for the retrieval of the aerosol properties from ground-based spectropolarimetric measurements is discussed. The neural network is able to retrieve the aerosol properties with an accuracy that is …