May 20, 2022 Presentation Open Access

Pou, Bartomeu; Smith, Jeffrey; Quinones, Eduardo; Martin, Mario; Gratadour, Damien

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    "description": "<p>Extreme Adaptive Optics (AO) systems are designed to provide high resolution and high contrast observing capabilities on the largest ground-based telescopes through exquisite phase reconstruction accuracy. In that context, the pyramid wavefront sensor (P-WFS) has shown promise to deliver the means to provide such accuracy due to its high sensitivity. However, traditional methods cannot leverage the highly non-linear P-WFS measurements to their full potential. We present a predictive control method based on Reinforcement Learning (RL) for AO control with a P-WFS. The proposed approach is data-driven, has no assumptions about the system&#39;s evolution, and is non-linear due to the usage of neural networks. First, we discuss the challenges of using an RL control method with a P-WFS and propose solutions. Then, we show that our method outperforms an optimized integrator controller. Finally, we discuss its possible path for an actual implementation.</p>", 
    "language": "eng", 
    "title": "A Non Linear Control Method with Reinforcement Learning for Adaptive Optics with Pyramid Sensors", 
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    "keywords": [
      "Adaptive Optics", 
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    "publication_date": "2022-05-20", 
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        "orcid": "0000-0001-8634-2316", 
        "affiliation": "Barcelona Supercomputing Center, Universitat Polit\u00e8cnica de Catalunya", 
        "name": "Pou, Bartomeu"
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      {
        "affiliation": "School of Computing, Australian National University", 
        "name": "Smith, Jeffrey"
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      {
        "affiliation": "Barcelona Supercomputing Center", 
        "name": "Quinones, Eduardo"
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      {
        "affiliation": "Universitat Polit\u00e8cnica de Catalunya", 
        "name": "Martin, Mario"
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        "affiliation": "LESIA , Observatoire de Paris, Universit\u00e9 PSL, CNRS, Sorbonne Universit\u00e9, Universit\u00e9 de Paris, Australian National University", 
        "name": "Gratadour, Damien"
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