MaDICS

Webinaire mensuel Action Spécifique Numérique INSU

Feb 17 all-day

Date : 2025-02-17
Lieu : Zoom
Webinaire ASNUM (in English) 14:00 15:00

Adeline Paiement
Laboratoire d’Informatique et des Systèmes
Université de Toulon

Domain-informed analysis of (astro)physics data

Machine learning and deep learning methods are increasingly popular for analysing physics and astrophysics data. However, their use often faces some specific challenges, such as the low availability of annotated ground-truth data, or the interpretability of (learning) models and of their prediction results. In this talk, we will review some recent efforts in developing learning methods that address the specific challenges of (astro)physics data. These developments exploit knowledge of the physics problem and data to inform the design of learning models.

Notre site web : www.madics.fr
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Apr

Webinaire mensuel de l’Action Spécifique Numérique INSU

Apr 14 all-day

Date : 2025-04-14
Lieu : Webinaire 14/04/2025 14h

Format 45+15

https://univ-grenoble-alpes-fr.zoom.us/j/98838875999?pwd=eDVaQmp3bmdjMC8rbjJUa2d2c2xBUT09

Enhancing Globular Cluster simulations with deep-learning: a forward modelling approach

Paolo Bianchini
Observatoire astronomique de Strasbourg

Globular clusters (GCs) are ubiquitous stellar systems found in nearly all galaxies; however, their origin in the primordial universe remains unknown. Despite their apparent simplicity, GCs present several modelling challenges: due to their old ages, the repeated gravitational interactions between ~1 million stars strongly impact their evolution and need to be calculated directly. Therefore, an efficient multi-scale approach to resolve this so-called “million-body problem” is needed. In this talk, I will present my current efforts in modelling realistic GCs, with a particular focus on a forward-modelling approach to interpret current and future observations. I will first introduce a new suite of >20 realistic star-by-star N-body simulations, run with NBODY6+++GPU, incorporating physics from the scale of stars (e.g. stellar evolution) to the one of external host galaxy (external tidal field), and using a realistic number of stars (N = 250k–1.5M). These simulations allow us to carry a first comparison with present-day GC properties and help establish a link with their formation properties in the high-z universe. I will then demonstrate how deep-learning techniques —specifically convolutional neural networks trained on synthetic images— can maximize the scientific return of these computationally expensive simulations for a direct comparison with observations. In particular, I will highlight recent developments in the pi-DOC deep-learning algorithm, designed to measure the dynamical and morphological properties of GCs in both the Milky Way and Andromeda, from space telescope observations. These promising results suggest that detailed dynamical studies of GCs could soon be extended beyond the Local Group, providing new valuable insights into the formation and evolution of these ancient stellar systems.

Notre site web : www.madics.fr
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Categories: Conferences DatAstro

Apr

Wed

Unlocking Exascale: A First Look at JUPITER

Apr 30 all-day

Date : 2025-04-30
Lieu : Webinaire en ligne (durée 1h)

inscription ici : https://epicure-hpc.eu/2025/04/15/unlocking-exascale-a-first-look-at-jupiter/

The JUPITER Exascale supercomputer, Europe’s first Exascale system, will soon be ready for large-scale computations within the upcoming allocation period at the Jülich Supercomputing Centre. This webinar will provide an overview of JUPITER’s system architecture, technical specification, and pathways to gain access to the machine’s available compute resource. Furthermore, a brief overview of the performance comparison will be presented between the JUWELS Booster production system and JEDI, which is the preparatory system that has identical hardware configuration to JUPITER Booster. There will be a sharing of first-hand experience in porting a plasma physics simulation code to an ARM-architecture based system like JEDI/JUPITER, building software modules required by the application via Easybuild and profiling.

Speakers :

Jolanta Zjupa

Jolanta Zjupa is a research staff member at the Jülich Supercomputing Centre (JSC) in Germany, where she has been focusing on application optimisation, parallelisation, HPC support, and training since 2022. With a background in theoretical and computational astrophysics, she brings a unique perspective to her work in High-Performance Computing. Jolanta holds a PhD in Astrophysics from Universität Heidelberg and worked as a PostDoc at renowned institutions in France and Austria.

Junxian Chew

Junxian Chew is a research staff member of JSC in Germany since 2023. He currently focuses in HPC support, parallel I/O, training and porting applications. Having background in aerospace engineering then pivoting to HPC study of plasma physics in nuclear fusion topic, he brings a solution-oriented mindset to the field of computation physics in HPC environment. He holds a PhD in physics from Ruhr-Universitaet Bochum.

Notre site web : www.madics.fr
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Categories: Conferences DatAstro

May

Webinaire mensuel Action Spécifique Numérique INSU

May 19 all-day

Date : 2025-05-19
Lieu : En distanciel, à 14h
durée 1h

https://univ-grenoble-alpes-fr.zoom.us/j/98838875999?pwd=eDVaQmp3bmdjMC8rbjJUa2d2c2xBUT09

Emeric Bron (OBSPM)

Dissecting the physics and chemistry of UV irradiated molecular gas with the Meudon PDR code

The Meudon PDR code is a state-of-the-art reference code for the study of the physics and chemistry of the interstellar medium, and in particular the impact of radiative feedback from star formation on molecular clouds.
This webinar will present the wide range of coupled physical and chemical processes included in this model, the organization and perspectives of the code’s development as an ANO CC, as well as the ISMDB model database and associated analysis tools, distributed within the ANO5 Platform MIS & Jets. This will be illustrated with application examples.

Notre site web : www.madics.fr
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Categories: Conferences DatAstro

May

Tue

Bayesian Deep Learning for Cosmology and Time Domain Astrophysics Workshop

May 20 – May 23 all-day

Date : 2025-05-20 => 2025-05-23
Lieu : APC, Université Paris Cité

Dear colleagues,

We are glad to announce the opening of the third edition of the workshop on Bayesian Deep Learning for Cosmology and Time Domain Astrophysics for registration. It will be held in Paris, France from May 20th to 23rd 2025.

The goal of this series of workshops is to bring together physicists and machine learning specialists to exchange recent results at the crossroads between cosmology, time-domain astrophysics and probabilistic machine learning frameworks to leverage uncertainties.

Reduced registration fees will be available for students, Please follow the indications on the registration website for grant applications.

The first day of the workshop will be structured as a school to introduce the Bayesian framework and probabilistic machine learning concepts. The rest of the workshop will alternate between keynote talks, topical presentations, interactive tutorials and poster sessions.

Call for contributions : open until May 1st

We welcome in particular contributions that target, or report on, the following non-exhaustive list of topics
• Applications of Bayesian Deep Learning in Cosmology and Time Domain Astrophysics
• Methodology for Model Uncertainty Quantification
• Anomaly and outlier detection
• Probabilistic ML frameworks and methodology
• Use of Bayesian deep learning outside of academia
• Ethical and environmental considerations of large-scale machine learning

Contributions do not necessarily need to be astrophysics-focused. Work on relevant ML methodology, or similar considerations in other scientific fields are welcome.

Confirmed keynote speakers and panelists :

Federica Bianco (remote), University of Delaware, LSST Rubin TVS collaboration
Alexandre Boucaud, APC
Samuel Farrens, Cosmostat AIM
François Lanusse, Cosmostat AIM
Konstantin Leyde, ICG Portsmouth
Anaïs Möller (remote), Swinburne University of Technology
Julien Peloton, IJCLab
Justine Zeghal, Université de Montréal, MILA

More information is available on the workshop website: https://astrodeep.net/workshop2025 and specific inquiries can be directed to workshop@astrodeep.net.

We look forward to welcoming you in Paris !

All the best,

The organizing committee
Eric Aubourg (CEA) – Alexandre Boucaud (CNRS) — Eric Chassande-Mottin (CNRS) —
François Lanusse (CNRS) – Cyrille Rosset (CNRS) — Cécile Roucelle (Université Paris Cité)

Notre site web : www.madics.fr
Suivez-nous sur Tweeter : @GDR_MADICS
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Categories: Conferences DatAstro

Jun

Réunion semestrielle de l’IVOA, Observatoire virtuel international

Jun 2 – Jun 6 all-day

Date : 2025-06-02 => 2025-06-06
Lieu : College Park (MD, USA), Hybride

les liens zoom seront disponibles sur les pages de la réunion.

Les groupes de travail et d’intérêt de l’IVOA se réunissent 2 fois par an pour travailler à l’élaboration des protocoles et standards d’interopérabilité en astronomie. L’Action Spécifique Observatoire Virtuel France (ASOV France) de l’INSU fédère la participation française.

La participation aux réunions est possible quelque soit la communauté d’appartenance

Notre site web : www.madics.fr
Suivez-nous sur Tweeter : @GDR_MADICS
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Categories: Conferences DatAstro

Webinaire mensuel de l’Action Spécifique Numérique INSU

Jun 2 all-day

Date : 2025-06-02
Lieu : En distanciel à 14h
format 45+15
Lien zoom :
https://univ-grenoble-alpes-fr.zoom.us/j/98838875999?pwd=eDVaQmp3bmdjMC8rbjJUa2d2c2xBUT09

The Era of Big Data in Radio Astronomy

Jeff Wagg (OCA)

Studying the faintest radio emitting objects in the Universe requires large single-dish telescopes, or multi-element interferometer arrays of either dishes or dipole antennas. The most ambitious of these is the international Square Kilometre Array Observatory (SKAO), consisting of two interferometers in Western Australia and the Karoo desert of South Africa. With a 50 year planned operational window, construction of these telescopes has begun, and is expected to be completed by the end of the decade. The data volume produced will approach an exabyte per year at full operations, necessitating a paradigm shift in the way we calibrate and image our data sets. In advance of the SKAO, pathfinder and precursor telescopes such as MeerKAT, LOFAR2.0, and ASKAP, are already generating large volumes of data and helping us to better prepare for, and understand the challenges.
I will summarize the science cases, design, and expected data processing for the SKAO telescopes. The data processing model incorporates a global SKA Regional Center Network (SRCNet) with nodes hosted by several host countries. In France, we are contributing to this development and I will summarize some of the work and also give a preview for how we expect to support the French community in the future. I will also describe a European Commission funded project called SPECTRUM, which involves researchers and data infrastructure providers from the European radio astronomy and high energy physics community. The ambitious goal of SPECTRUM is to produce a technical blueprint and strategic roadmap for exabyte scale computing in the era of SKAO and upgraded experiments at CERN.