The ability of C/C composites to maintain high mechanical properties up to very high temperatures (above 3000 K), combined with their low densities, justifies their use in extreme conditions, especially in aerospace and defense applications. However, due to the very large anisotropy of their constituents, their partial crystalline order, and the difficulty to perform experiments under the...
Material properties, particularly mechanical ones, are intrinsically multiscale, emerging from the material's structure ranging from the atomic to the continuum structure. Multiscale modelling and simulation based on the assumption of a separation of scales in the architectures of nanomaterials appears as a promising alternative to trial-and-error experiments for material design. The current...
We address the problem of the training of a machine learning potential (MLP) for the atomistic study of rare events. By training a MLP only on a few dozens of agnostic out of equilibrium ab initio trajectories shot from the top of the barrier, we are able to recover free energies close to ab initio accuracy. As well as showing that it is possible to recover transition rates and...
With the rapid development of miniaturized devices in spintronics, the dynamics of nanomagnets is of both theoretical and practical interest. The equations of motion for a magnetic moment that figure out the average magnetization embedded in a medium, are differential equations, but contain time derivatives on both sides, that cannot be-in general-recast in a form that is useful for usual...
L’expérience JUNO (Jiangmen Underground Neutrino Observatory), en cours de construction en Chine, sera l’un des plus grands détecteurs de neutrinos de prochaine génération. Si son champ d'investigation est multiple, l’un des ses principaux buts concerne la hiérarchie de masse des neutrinos, inconnue à ce jour. Sa détermination s’appuie grandement sur la mesure du spectre en énergie...
The Phase-II upgrade of the LHC will increase its instantaneous luminosity by a factor of 7 leading to the High Luminosity LHC (HL-LHC). At the HL-LHC, the number of proton-proton collisions in one bunch crossing (called pileup) increases significantly, putting more stringent requirements on the LHC detectors electronics and real-time data processing capabilities.
The ATLAS Liquid Argon...
Le calcul neuromorphique est un champ récent de l’intelligence artificielle visant à diminuer la consommation énergétique des tâches cognitives résolues en s’inspirant de l’architecture du cerveau humain. Dans ce contexte, les nano-oscillateurs à transfert de spin ont récemment fait l’objet d’une grande attention, notamment en raison de leur utilisation potentielle en tant que neurones...
Variational quantum algorithms are emerging as promising tools to tackle complex problems ranging from quantum chemistry to combinatorial optimization. These algorithms optimize the continuous parameters of a variational quantum circuit as to extremize a cost function encoding the task at hand. The optimization is achieved through gradient descent methods. Such models can suffer from the...
ChatGPT, a Large Language Model based chatbot with astonishing capabilities, has become very popular on social networks in particular. But beyond amazing success and dismal failure anecdotes, to what extent can ChatGPT (or Bing) be used realistically in the physicist's daily life?
The experiments of twenty particle physicists have been collected as user stories. They are summarised in this...
Le boson de Higgs a été découvert auprès du collisionneur LHC au CERN en 2012. Afin de mieux comprendre les propriétés du boson de Higgs et l’origine ultime de la matière les chercheurs ont maintenant besoin de beaucoup plus de données. La phase dite de haute luminosité (HiLumi-LHC) va démarrer en 2029 et doit permettre de multiplier par 10 le taux de production de bosons de Higgs afin...
X-ray nanotomography is a well-established technique with many applications in material science and biology. The spatial resolution of classical CT can be enhanced when using ptychographic projections [1] measured at different angles to reconstruct a 3D volume.
X-ray Ptychography [2][3] is a coherent diffraction imaging technique based on the acquisition of multiple diffraction patterns...
Machine Learning (ML) algorithms are currently a leading choice for Data Analysis applications in various fields: from industry to science and medicine. Following the general trend, different ML methods (Boosted Decision Trees, Neural Networks) have already been successfully used for data reconstruction and analysis in the CMS experiment. More sophisticated algorithms are becoming available,...
