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BEGIN:VEVENT
DTSTART;TZID=Europe/Paris:20240930T140000
DTEND;TZID=Europe/Paris:20240930T150000
DTSTAMP:20260606T123455
CREATED:20240901T185354Z
LAST-MODIFIED:20241001T173736Z
UID:428-1727704800-1727708400@asnum.cnrs.fr
SUMMARY:Webinaire Vincent Reverdy
DESCRIPTION:Webinaire ASNUM \nVincent Reverdy \nLaboratoire d’Annecy de Physique des Particules \nThe Evolution and Standardization of C++ for the Future of Numerical Astrophysics \nVoir le Replay :  https://astrotube.obspm.fr/w/8p7178BkGcBDnMmpwBxrMW \n  \n  \nOver the last 15 years\, the C++ programming language has evolved significantly\, providing more constructs and features to users. But while a part of the numerical astrophysics community is transitioning to the language\, it is worth analyzing its evolution and where it is going. In the first part of the presentation\, I will discuss current and upcoming features that can be leveraged in the context of high-performance numerical astrophysics. I will present real-case examples of what is already possible\, and what can we expect for the near future. The second part of the presentation will be dedicated to the long term future. The adoption of a new language for a community like ours is a big step forward that is likely to have consequences in the decades to come given the lifetime of our codes. Some design choices that are made now\, may stay forever. In this context\, I will discuss the general evolution of the language in the light of what I have learned from 10 years of participation in the C++ standards committee. Finally\, I will conclude by trying to give a bigger picture on the interplay between programming language evolution and computational physics from both the standpoint of computer science and physics\, and what it means for the codes we are currently developing. \n 
URL:https://asnum.cnrs.fr/event/webinaire_vincent_reverdy/
CATEGORIES:Webinaires
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BEGIN:VEVENT
DTSTART;TZID=Europe/Paris:20240624T140000
DTEND;TZID=Europe/Paris:20240624T153000
DTSTAMP:20260606T123455
CREATED:20231220T101112Z
LAST-MODIFIED:20240110T163747Z
UID:258-1719237600-1719243000@asnum.cnrs.fr
SUMMARY:Webinaire Raphaël Loubère
DESCRIPTION:Webinaire ASNUM \nRaphaël Loubère \nInstitut de Mathématiques de Bordeaux
URL:https://asnum.cnrs.fr/event/webinaire-raphael-loubere/
CATEGORIES:Webinaires
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Paris:20240527T140000
DTEND;TZID=Europe/Paris:20240527T150000
DTSTAMP:20260606T123455
CREATED:20240515T213852Z
LAST-MODIFIED:20240902T133539Z
UID:401-1716818400-1716822000@asnum.cnrs.fr
SUMMARY:Webinaire Mainetti et al.
DESCRIPTION:Webinaire ASNum\nComputing for research in astroparticle physics and cosmology at CC-IN2P3\nGabriele Mainetti\, Quentin Le Boulc’h\, Nadia Lajili\, Rachid Lemrani Alaoui\, Fabio Hernandez\nVoir le Replay : https://astrotube.obspm.fr/w/nAQFEWjmerNLceuakgNLLr\n\nIN2P3 computing centre (CC-IN2P3) provides computing and data storage services to support the projects of IN2P3’s scientific programme\, including those addressing subjects in astroparticle physics and cosmology. We will present services the site offers illustrated by examples of a few projects currently taking data or in their final stages of preparation for entering their operations phase \n 
URL:https://asnum.cnrs.fr/event/webinaire-mainetti-et-al/
CATEGORIES:Webinaires
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Paris:20240408T140000
DTEND;TZID=Europe/Paris:20240408T153000
DTSTAMP:20260606T123455
CREATED:20240125T084353Z
LAST-MODIFIED:20240902T133036Z
UID:326-1712584800-1712590200@asnum.cnrs.fr
SUMMARY:Webinaire Wassim Tenachi
DESCRIPTION:Webinaire ASNUM\nWassim Tenachi\nAutomatically discovering analytical physical laws using deep reinforcement learning\nVoir le REPLAY : https://astrotube.obspm.fr/w/7fiKWF45p3fmzQsK8gkFnC\n\n\nObservatoire de Strasbourg \nSymbolic Regression is the study of algorithms that automate the search for analytic expressions that fit data. Using such approaches one can derive interpretable\, intelligible\, compact and inexpensive analytical models that tend to present excellent generalization capabilities – such models have the potential to complement neural networks in areas where these attributes are important. With new advances in deep learning there has been much renewed interest in such approaches\, yet efforts have not been focused on physics\, where we have important additional constraints.\n\nI will present Φ-SO\, a Physical Symbolic Optimization framework for recovering analytical symbolic expressions from physical data using deep reinforcement learning techniques and its two most innovative features:\n(1) Our system is built\, from the ground up\, to propose solutions where the physical units are consistent by construction. This is useful not only in eliminating physically impossible solutions\, but because it restricts enormously the freedom of the equation generator\, thus vastly improving performances.\n(2) I will present the ‘Class Symbolic Regression’ extension of our system. This is a first framework for automatically finding a single analytical functional form that accurately fits multiple datasets – each governed by its own (possibly) unique set of fitting parameters. This hierarchical framework leverages the common constraint that all the members of a single class of physical phenomena follow a common governing law.\n\nPapers:\nhttps://arxiv.org/abs/2303.03192 (SR with RL & dimensional analysis)\nhttps://arxiv.org/abs/2312.01816 (Class SR)\nCode and demo:\nhttps://github.com/WassimTenachi/PhySO
URL:https://asnum.cnrs.fr/event/webinaire_wtenachi/
CATEGORIES:Webinaires
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BEGIN:VEVENT
DTSTART;TZID=Europe/Paris:20240318T140000
DTEND;TZID=Europe/Paris:20240318T153000
DTSTAMP:20260606T123455
CREATED:20240110T142827Z
LAST-MODIFIED:20240902T133308Z
UID:284-1710770400-1710775800@asnum.cnrs.fr
SUMMARY:Webinaire Anne-Laure Ligozat
DESCRIPTION:Webinaire ASNUM \nThe environmental costs of computing\nAnne-Laure Ligozat \nLaboratoire Interdisciplinaire des Sciences du Numérique (LISN) \nVoir le Replay : https://astrotube.obspm.fr/w/5zUQJtnegayqoyd7hYf9mD \nThe use of digital services and equipment keeps increasing in all domains\, and in particular in scientific computing. These digital applications have environmental costs\, that have begun to be taken into account. But assessing the environmental impact of digital technology poses a number of difficulties\, requiring the adaptation of methodologies and access to data that is not always available. In this talk\, I will present what is currently known about the impact of digital technology\, and scientific computing in particular.
URL:https://asnum.cnrs.fr/event/webinaire_anne-laure_ligozat/
CATEGORIES:Webinaires
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BEGIN:VEVENT
DTSTART;TZID=Europe/Paris:20240205T160000
DTEND;TZID=Europe/Paris:20240205T173000
DTSTAMP:20260606T123455
CREATED:20231013T173133Z
LAST-MODIFIED:20240902T133229Z
UID:236-1707148800-1707154200@asnum.cnrs.fr
SUMMARY:Webinaire Paulo Alves (UCLA)
DESCRIPTION:Webinaire ASNum\nPaulo Alves \nUCLA\nDistilling reduced plasma physics models from the data of first-principles kinetic simulations\nVoir le Replay : https://astrotube.obspm.fr/w/rDjYRkQCuCkLaKzxXxnmEN\n\nAt the core of some of the most important problems in plasma physics—from controlled nuclear fusion to the acceleration of cosmic rays—is the challenge to describe nonlinear\, multiscale plasma dynamics. The development of reduced plasma models that balance between physical accuracy and computational complexity is critical to advancing theoretical comprehension and enabling holistic computational descriptions of these problems. In this talk\, I will discuss the possibility of using data-driven techniques to develop accurate reduced plasma models (in the form of partial differential equations) directly from the data of first-principles particle-in-cell simulations. In particular\, I will discuss 1) how data-driven model-discovery techniques based on sparse optimization can be used infer interpretable reduced plasma models\, 2) an effective strategy for robust model identification in the presence of the high data noise that is intrinsic to first-principles particle-based simulations\, and 3) strategies for embedding fundamental physics symmetries in the model-discovery methodology. I will demonstrate the potential of this approach by recovering the fundamental hierarchy of plasma physics models—from the Vlasov equation to single-fluid magnetohydrodynamics. I will end with an outlook on how this data-driven methodology offers a promising route to accelerate the development of reduced theoretical models of complex nonlinear plasma phenomena and to design computationally efficient algorithms for multiscale plasma simulations.
URL:https://asnum.cnrs.fr/event/webinaire-paulo-alves-ucla/
CATEGORIES:Webinaires
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Paris:20231218T140000
DTEND;TZID=Europe/Paris:20231218T160000
DTSTAMP:20260606T123455
CREATED:20231006T153956Z
LAST-MODIFIED:20240902T133157Z
UID:219-1702908000-1702915200@asnum.cnrs.fr
SUMMARY:Webinaire Emmanuel Bertin (CEA)
DESCRIPTION:Webinaire ASNum \nEmmanuel Bertin (CEA)  \nNew prospects on Wide-Field imaging with Deep Learning \nVoir le Replay : https://astrotube.obspm.fr/w/hhAktLriqnVtHj7vCm85Qy \nSince the 19th century\, wide-field imaging has significantly advanced numerous fields of Astrophysics\, spanning from the study of solar system bodies to observational cosmology. Further advances in detector technology and processing power now enable the exploration of the time domain at increasingly high frame rates.\nThrough concrete examples\, I will show with how Deep Learning and GPU processing offer promising solutions to address contemporary challenges in wide-field imaging and time-domain astronomy
URL:https://asnum.cnrs.fr/event/webinaire-emmanuel-bertin-cea/
CATEGORIES:Webinaires
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Paris:20231120T140000
DTEND;TZID=Europe/Paris:20231120T160000
DTSTAMP:20260606T123455
CREATED:20231006T153914Z
LAST-MODIFIED:20231220T101308Z
UID:217-1700488800-1700496000@asnum.cnrs.fr
SUMMARY:Webinaire Geoffroy Lesur (IPAG)
DESCRIPTION:Webinaire ASNum \nGeoffroy Lesur (IPAG) \nIDEFIX \nIdefix is a Godunov MHD finite volume code designed to run on accelerated supercomputers using the C++ Kokkos framework. In this webinar\, I will discuss our motivations for creating a new code (in contrast to porting an existing one) and the path we followed. As the code is now public and is becoming more widely used\, I will also illustrate the difficulties physicists encounter when using codes of this kind\, and how to address them to maximize the transition of our communities to the new generation of accelerated machines.
URL:https://asnum.cnrs.fr/event/webinaire-geoffroy-lesur-ipag/
CATEGORIES:Webinaires
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Paris:20231016T140000
DTEND;TZID=Europe/Paris:20231016T160000
DTSTAMP:20260606T123455
CREATED:20231006T152533Z
LAST-MODIFIED:20240902T133129Z
UID:209-1697464800-1697472000@asnum.cnrs.fr
SUMMARY:Webinaire Jérémy Blaizot (CRAL) & Joakim Rosdahl (CRAL)
DESCRIPTION:Webinaire ASNum \nJérémy Blaizot (CRAL) & Joakim Rosdahl (CRAL) \nAstrophysics from star formation to cosmology scales with RAMSES across the globe \nVoir le replay : https://astrotube.obspm.fr/w/mSLVsFyJtNpsXrqA1sFgEt \n  \nRAMSES is a publicly available adaptive mesh refinement code used for a multitude of astrophysics problems over the last two decades by a growing community across the globe\, and is one of the main codes used for cosmological simulations of galaxy formation. In this presentation\, we begin by giving an overview of the history of the RAMSES code and its usage in a variety of science-cases ranging from sub-parsec to giga-parsec scales. We will then present and explain the newly established RAMSES SNO (Service National d’Observation)\, which will allow us to develop a service to the RAMSES community and make the code even more user-friendly for aspiring and established astrophysicists alike.
URL:https://asnum.cnrs.fr/event/web102023blaizot/
CATEGORIES:Webinaires
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