Toward on-sky adaptive optics control using reinforcement learning Model-based policy optimization for adaptive optics

Context. The direct imaging of potentially habitable exoplanets is one prime science case for the next generation of high contrast imaging instruments on ground-based, extremely large telescopes. To reach this demanding science goal, the instruments are equipped with eXtreme Adaptive Optics (XAO) systems which will control thousands of actuators at a framerate of kilohertz to several kilohertz. Most of the habitable exoplanets are located at small angular separations from their host stars, where the current control laws of XAO systems leave strong residuals. Aims. Current AO control strategies such as static matrix-based wavefront reconstruction and integrator control suffer from a temporal delay error and are sensitive to mis-registration, that is, to dynamic variations of the control system geometry. We aim to produce control methods that cope with these limitations, provide a significantly improved AO correction, and, therefore, reduce the residual flux in the coronagraphic point spread function (PSF). Methods. We extend previous work in reinforcement learning for AO. The improved method, called the Policy Optimization for Adaptive Optics (PO4AO), learns a dynamics model and optimizes a control neural network, called a policy. We introduce the method and study it through numerical simulations of XAO with Pyramid wavefront sensor (PWFS) for the 8-m and 40-m telescope aperture cases. We further implemented PO4AO and carried out experiments in a laboratory environment using Magellan Adaptive Optics eXtreme system (MagAO-X) at the Steward laboratory. Results. PO4AO provides the desired performance by improving the coronagraphic contrast in numerical simulations by factors of 3-5 within the control region of deformable mirror and PWFS, both in simulation and in the laboratory. The presented method is also quick to train, that is, on timescales of typically 5-10 s, and the inference time is sufficiently small (Peer reviewe

Toward on-sky adaptive optics control using reinforcement learning Model-based policy optimization for adaptive optics

Context. The direct imaging of potentially habitable exoplanets is one prime science case for the next generation of high contrast imaging instruments on ground-based, extremely large telescopes. To reach this demanding science goal, the instruments are equipped with eXtreme Adaptive Optics (XAO) systems which will control thousands of actuators at a framerate of kilohertz to several kilohertz. Most of the habitable exoplanets are located at small angular separations from their host stars, where the current control laws of XAO systems leave strong residuals. Aims. Current AO control strategies such as static matrix-based wavefront reconstruction and integrator control suffer from a temporal delay error and are sensitive to mis-registration, that is, to dynamic variations of the control system geometry. We aim to produce control methods that cope with these limitations, provide a significantly improved AO correction, and, therefore, reduce the residual flux in the coronagraphic point spread function (PSF). Methods. We extend previous work in reinforcement learning for AO. The improved method, called the Policy Optimization for Adaptive Optics (PO4AO), learns a dynamics model and optimizes a control neural network, called a policy. We introduce the method and study it through numerical simulations of XAO with Pyramid wavefront sensor (PWFS) for the 8-m and 40-m telescope aperture cases. We further implemented PO4AO and carried out experiments in a laboratory environment using Magellan Adaptive Optics eXtreme system (MagAO-X) at the Steward laboratory. Results. PO4AO provides the desired performance by improving the coronagraphic contrast in numerical simulations by factors of 3-5 within the control region of deformable mirror and PWFS, both in simulation and in the laboratory. The presented method is also quick to train, that is, on timescales of typically 5-10 s, and the inference time is sufficiently small (Peer reviewe

Innocence Versus Malevolence – Youth Crime in the News

In 2020 and 2021, the Finnish news media covered violent youth crime extensively. Not because it had increased significantly, but due to a handful of exceptional cases that shook Finnish society. Several brutal and severe cases that took place in a short period seemed to generate a media narrative around a new crime wave that posed a threat to Finnish society. The theoretical basis for this research focuses on the intersection of media studies, criminology, and sociology. Youth violence is often disproportionately covered in the news. Cases, in which adolescents commit violent crimes, are often written about in more depth and more extensively than those committed by adults since the pairing of the innocence of children with horrendous acts of violence manifests a more newsworthy phenomenon. However, since media portrayals have the power to shape public perceptions, they can create distorted views of the prevalence of crime and spark fear in audiences. This Master’s thesis aims to gain an understanding of the nature of news narratives around violent youth crime in Finland. This study takes on a qualitative and empirical approach. The underlying assumption behind the research is that the concept of youth violence is a social construction and that news narratives play a role in the discursive creation of the phenomenon. This Master’s thesis focuses on the Finnish news coverage of three cases of homicide that happened in 2020 and 2021. In each case the perpetrators were adolescents. The methodological approach of this thesis is a qualitative content analysis of coverage in 137 news articles found online. The research focuses on how adolescent offenders are described, and how the reasons and solutions to youth violence are portrayed in the news. The results of the thesis suggest that violent youth and the threat they pose to society are covered in the news media as a paradox; on the one hand, only evil sadists are capable of such violent acts, yet on the other hand, society has failed its children if they resort to violence. The discussion around youth violence is populated by a plethora of individual actors, such as perpetrators, their peers, child service workers, the police, politicians and ordinary citizens, and everyone plays a role in how the phenomenon of violent youth crime is discursively constructed in the news

The Mediterranean region under climate change

This book has been published by Allenvi (French National Alliance for Environmental Research) to coincide with the 22nd Conference of Parties to the United Nations Framework Convention on Climate Change (COP22) in Marrakesh. It is the outcome of work by academic researchers on both sides of the Mediterranean and provides a remarkable scientific review of the mechanisms of climate change and its impacts on the environment, the economy, health and Mediterranean societies. It will also be valuable in developing responses that draw on “scientific evidence” to address the issues of adaptation, resource conservation, solutions and risk prevention. Reflecting the full complexity of the Mediterranean environment, the book is a major scientific contribution to the climate issue, where various scientific considerations converge to break down the boundaries between disciplines