Institut de Mathématiques de Toulouse

Les événements de la journée

5 événements

  • Séminaire Modélisation, Analyse et Calcul

    Mardi 18 décembre 2018 09:00-12:00 -

    Matinée d’équipe MIP

    Résumé :

    • 9h30-10h15 : Victor Hernandez Santamaria "Some controllability results for shadow systems »
    • 10h15-10h45 : Michèle Romanos " Mathematical modelling of embryo axis elongation »
    • 10h45-11h : pause café
    • 11h-11h30 : Kuntal Bhandari " Boundary controllability of 1D coupled-parabolic system « 
    • 11h30-12h15 : Clémentine Courtès "A high-order unconditional stable relaxation scheme based on Lattice-Boltzmann methods »

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  • Séminaire de Probabilités

    Mardi 18 décembre 2018 09:45-10:45 - Guillaume Cébron - IMT

    Liberté avec amalgamation pour des matrices invariantes par permutation

    Résumé : La théorie des probabilités libres est un outil robuste pour l’étude spectrale des grandes matrices aléatoires. En particulier, les matrices aléatoires unitairement invariantes sont asymptotiquement libres. L’objectif de cet exposé est de présenter une extension récente de ce phénomène : les matrices aléatoires invariantes par permutation sont asymptotiquement libres avec amalgamation sur l’espace des matrices diagonales. Travail en collaboration avec Au, Dahlqvist, Gabriel et Male.

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  • Séminaire de Statistique

    Mardi 18 décembre 2018 11:00-12:00 - Vincent Feuillard - Airbus

    A multivariate extreme value theory approach to anomaly clustering and visualization

    Lieu : Salle 106, Bat 1R1 - Motivated by a wide variety of applications from fraud detection to aviation safety management, unsupervised anomaly detection is the subject of much attention in the machine-learning literature. We developed novel statistical techniques for tackling anomaly detection borrowing concepts and tools from machine-learning and multivariate extreme value analysis both at the same time. Usually, anomaly detection algorithms declared extremes as anomaly, whereas all extremes values are not anomalies. We study the dependance structure of rare events in the context of high dimensional and propose an algorithm to detect this structure under a sparse assumption. This approach can reduce drastically the false alarm rate : anomalies then correspond to the observation of simultaneous very large/extreme values for groups of variables that have not been identified yet. A data-driven methodology for learning the sparse representation of extreme behaviours has been developed in Goix (2016). An advantage of this method lies in its straightforward interpretability. In addition, the representation of the dependance structure in the extremes thus designed induces a specific notion of (dis-)similarity among anomalies, that paves the way for elaborating visualization tools for operators in the spirit of those proposed for large graphs. We also describe how this approach applies to functional data collected for aircraft safety purposes after an appropriate preliminary filtering stage.

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  • Homotopie en Géométrie Algébrique

    Mardi 18 décembre 2018 14:00-15:00 - Lennart Meier - Univ. Utrecht

    Towards the Brauer group of TMF

    Résumé : The Picard group of the spectrum TMF of topological modular forms has been determined by Mathew and Stojanoska about four years ago. A more subtle invariant is the Brauer group of a ring spectrum. Complete calculations are very difficult for non-connective ring spectra although some progress has been made in the case of real K-theory by Gepner and Lawson.
    To attack the Brauer group of TMF, it is first necessary to compute the Brauer group
    of the moduli stack of elliptic curves. We will report on joint work with Antieau, which does exactly that over many base schemes. Moreover, we will report on joint work with Antieau and Stojanoska about the Brauer group of TMF itself.

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  • Séminaire Maths-Physique IMT-LPT

    Mardi 18 décembre 2018 14:00-15:00 - Carlos GONZALEZ-GUILLEN - UPM, Madrid

    On the spectral gap of random quantum channels

    Résumé : We prove a lower bound on the difference between the first and second singular values of quantum channels induced by random isometries, that is tight in the scaling of the number of Kraus operators. This allows us to give an upper bound on the difference between the first and second largest (in modulus) eigenvalues of random channels with same large input and output dimensions for finite number of Kraus operators k≥169. Moreover, we show that these random quantum channels are quantum expanders, answering a question posed by Hastings. As an application, we show that ground states of infinite 1D spin chains, which are well-approximated by matrix product states, fulfill a principle of maximum entropy.

    Lieu : Salle 106, Bâtiment 1R1

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