Survey of correlation properties of polyatomic molecules vibrational energy levels using FT analysis

International audienceIn the last few years molecular spectroscopists have begun to study the highly excited vibrational levels of polyatomic molecules. In this high energy regime vibrational quantum numbers can no longer be intrinsically assigned (in contrast to vibrational levels at low energy). One can only characterize these levels by their correlation properties. The authors consider: short range correlations which are characterized by the next neighbor distribution, (NND). These correlations range from a Poisson (random or uncorrelated spectra) to a Wigner distribution (which shows 'level repulsion'); (ii) long range correlations are characterized by the$\mathrm{\Sigma ^{2}}$(L) and$\mathrm{\Delta _{3}}$(L) function. They describe the behavior which ranges from an uncorrelated spectra (Poisson statistic) to a spectra with 'spectral rigidity'

Learning redundant dictionaries with translation invariance property: the MoTIF algorithm

International audienceSparse approximation using redundant dictionaries is an efficient tool for many applications in the field of signal processing. The performances largely depend on the adaptation of the dictionary to the signal to decompose. As the statistical dependencies are most of the time not obvious in natural high- dimensional data, learning fundamental patterns is an alternative to analytical design of bases and has become a field of acute research. Most of the time, the underlying patterns of a class of signals can be found at any time, and in the design of a dictionary, this translation invariance property should be present. We present a new algorithm for learning short generating functions, each of them building a set of atoms corresponding to all its translations. The resulting dictionary is highly redundant and translation invariant

Fourier transform: A tool to measure statistical level properties in very complex spectra

International audienceWe show that the Fourier transform of very complex spectra gives a sound measurement of long-range statistical properties of levels even in cases of badly resolved, poorly correlated spectra. Examples of nuclear energy levels, highly excited acetylene vibrational levels, and singlet-triplet anticrossing spectra in methylglyoxal are displayed

Conférence nationalesur l'enseignement des mathématiques à l'école primaire et au collège: Recueil des interventions suscitées

Etats des lieux et analyses de l'enseignement des mathématiques en France, aujourd'hui

Plus d'autonomie protéique dans les élevages caprins grâce à la prairie multi-espèces : expérience du REDCap en Poitou-Charentes et Pays de la Loire

Depuis une quinzaine d’années, les élevages caprins de l’Ouest de la France s’intensifient, entraînant desachats croissants en intrants. Deux dispositifs de Recherche et Développement complémentaires visent àfavoriser la recherche d’autonomie alimentaire et protéique : Patuchev (Inra-UE FERLus) et le Réseaud’Expérimentation et de Développement Caprin-REDCap (BRILAC) (BONNES et al., 2012). Pour répondre à cetenjeu, l’utilisation de la prairie multi-espèces a été identifiée comme une priorité par les éleveurs et lestechniciens. Cependant, il manque encore actuellement des références régionales sur les prairies multiespècesvalorisées par les caprins. L’objectif est donc de proposer un (ou des) mélange(s) prairial(aux)adapté(s) aux chèvres, aux conditions pédoclimatiques régionales et aux différents systèmes fourragers

MoTIF : an Efficient Algorithm for Learning Translation Invariant Dictionaries

International audienceThe performances of approximation using redundant expansions rely on having dictionaries adapted to the signals. In natural high-dimensional data, the statistical dependencies are, most of the time, not obvious. Learning fundamental patterns is an alternative to analytical design of bases and is nowadays a popular problem in the field of approximation theory. In many situations, the basis elements are shift invariant, thus the learning should try to find the best matching filters. We present a new algorithm for learning iteratively generating functions that can be translated at all positions in the signal to generate a highly redundant dictionary

Archipel 2022 : Risques systémiques, trajectoires et leviers d'action transdisciplinaires: Vers l'émergence d'une communauté de recherche francophone transdisciplinaire sur les enjeux de l'Anthropocène

International audienc

Archipel 2022 : Risques systémiques, trajectoires et leviers d'action transdisciplinaires: Vers l'émergence d'une communauté de recherche francophone transdisciplinaire sur les enjeux de l'Anthropocène

International audienc