Speaker : Jean-Marc Huré (LAB)
Title: Figures d’équilibres sphéroidales des fluides multicouches.
J’exposerai les principaux éléments d’un formalisme vectoriel résolvant approximativement O(c) les configurations d’équilibre d’un fluide autogravitant hétérogène composé de L couches homogènes en rotation rigide et bordées par des sphéroides parfaits. Cette approche, basée sur un développement du potentiel gravitationnel sur le paramètre confocal c (plutôt que sur l’ellipticité e), permet des configurations très oblates, prolongeant ainsi les travaux classiques fin XIXe de l’école française. Ces solutions analytiques sont validées par les résultats numériques obtenus par la méthode SCF du champ auto-cohérent, et par l’établissement de l’équation du Viriel associée. Quelques perspectives ainsi qu’une application à la détermination de structures internes pour la planète Jupiter réalisant les principales observables seront présentées.
The slides will be in English, the seminar will be given in French.
Speaker : David Cornu (Obs de Paris)
Title: Winning the SKA Science Data Challenge 2 with a fast Deep Learning object detector
Abstract:
With its 1 TB simulated data cube of HI line emission, the SKA Science Data Challenge 2 (SDC2) is getting closer to the difficulty of real upcoming SKA observation analysis. Even if the type of task to perform in the SKA SDCs are rather classical (detection, classification, parameter extraction, etc.) modern datasets have become heavily demanding for classical approaches due to size and dimensionality. It is not a surprise then, that many astronomers started to focus their work on Machine Learning approaches that demonstrated their efficiency in similar applications. However, hyperspectral images from astronomical interferometers are in fact very different from images used to train state-of-the-art pattern recognition algorithms, especially in terms of noise level, contrast, object size, class imbalance, spectral dimensionality, etc. As a direct consequence, these methods do not perform as well as expected when directly applied to astronomical datasets. In this context, the MINERVA (MachINe lEarning for Radioastronomy at obserVatoire de PAris) project has assembled a team to participate in the SDC2 with the objective of developing innovative Machine Learning methods that better suit the needs of astronomical images.
In this presentation, I will describe the work we have made on implementing a modern YOLO (You Only Look Once) CNN object detector inside our custom framework CIANNA (Convolutional Interactive Artificial Neural Networks by/for Astrophysicists) and describe the modifications and tuning that allowed us to reach the first place of the SKA SDC2. I will start by discussing the strengths and weaknesses of this type of method in comparison to more widely adopted Region-Based CNN detectors (Faster R-CNN, Mask R-CNN, …). I will also review the motivation and the effect of the numerous changes we made on the method (data quantization, 3D convolution, layer architecture, detection layout to manage blending, objectness decomposition, IoU selection, additional parameter inference, …) in order to apply it to both SDC1 and SDC2, and identify what are the present limits as well as some tracks for further improvements. I will detail the computational efficiency of the method (with GPU acceleration) and discuss its scaling capabilities for upcoming challenges or datasets. Finally, we will comment on how this methodology could be used to analyze the actual data from SKA pathfinders or any other similar astronomical dataset and how it could be used to merge knowledge and information from multiple datasets at the same time.
Speaker : Martin Turbet
Title: Le modèle « générique » de climats planétaires et panorama de ses applications
Abstract: Le modèle générique de climats planétaires ou « Generic PCM » est un code communautaire, développé principalement et historiquement au LMD, et dont l’objectif est de simuler l’ensemble des processus physiques et chimiques opérant dans les atmosphères planétaires. Ses applications sont nombreuses : étude de la dynamique atmosphérique de Jupiter, Saturne et des géantes glacées, formation de brumes photochimiques sur Titan, évolution couplée de l’atmosphère et des glaces sur Pluton et Triton, paléoclimats de Mars, la Terre et Vénus, climats et observabilité des exoplanètes (des plus froides et petites aux plus grandes et chaudes), etc.
Après un bref aperçu du modèle et des briques qui le constituent, je vous présenterai un panorama de ses applications, avec une attention toute particulière sur les planètes et exoplanètes telluriques.
Speaker : Louis Amard
Title: The evolution of young low-mass stars : focus on rotation and activity
Abstract: Between its formation stage as an active accreting seed and today, the Sun underwent large structural changes as well as variation in magnetic activity, rotation rate and its relation to the surrounding environment. I will go through the different processes that are responsible for these changes and present our latest results on the subject. We will go from the early interaction between the star and its proto-planetary disc bathing in UV radiations emitted from the massive neighbours, to the internal mixing happening in the inner layers of solar-like stars and probed by asteroseismology. Finally, I will try to review the possible applications of this work to other types of stars at different stages of the evolution in the context of the current or future surveys.
Speaker : Olivia Venot (LISA)
Title: On the importance of chemical data for warm exoplanet atmospheres
Abstract: The very first data from JWST are finally arriving and show us the full potential of this telescope for the characterisation of exoplanet atmospheres. The interpretation of these data relies on atmospheric models, so it is of paramount importance that these models are reliable and robust. In this context I will show you the methodology applied to develop kinetic models adapted to the atmospheres of hot exoplanets, with physico-chemical data at high temperatures. I will also talk about the Hot Jupiter WASP-43b and the insights that JWST can give us into its atmosphere.