On rappellera comment les tresses apparaissent dans différents contextes topologiques et algébriques. On passera ensuite aux tresses pures, ce qui nous donnera une première occasion de parler de groupes libres. On continuera avec des actions de groupes de tresses, en étudiant notamment sous plusieurs angles l'action fidèle sur les groupes libres. Cela nous permettra de restreindre l'application de Johnson $\tau1^{std}$ aux groupes de tresses ; on présentera les calculs de Kawazumi pour cette restriction. Si le temps le permet, on fera une digression sur les algèbres de battage quantiques, ce qui pourrait améliorer la compréhension des applications $gj$ qu'on a vues dans l'exposé de Friedrich (provenant de l'article de Hochschild-Serre).

Notes. Video.

Un certain nombre d'équations aux dérivées partielles stochastiques très singulières présentent des problèmes dans leur définition même. C'est le cas, entre autres, de l'équation de KPZ, mais aussi de l'équation de quantisation stochastique en dimension 3. Les méthodes classiques d'analyse ne permettent pas de définir cette équation, et il s'avère que pour lui donner un sens, il est nécessaire de soustraire un constante infinie et de considérer formellement un nouveau problème. La théorie des distributions paracontrolées, qui combine des idées de la théorie des chemins rugueux avec la décomposition de Paley-Littlewood et le paraproduit, est un bon cadre pour donner un sens à cette renormalisation, et résoudre (localement) cette équation.

Dans une première partie nous introduirons donc la notion de distributions paracontrolées, et dans une deuxième partie, nous montrerons comment cette théorie peut s'appliquer à l'équation de quantisation stochastique en dimension 3.

Notes / Préliminaires

We present a discretization strategy for compressible fluids systems for unstrutctured grids based a Lagrange-Remap approach that does not involve any moving mesh. We present the stability properties of this solver and present a natural semi-implicit extension of the method that allows to remain stable under a CFL condition involving only the material velocity. We present another modification of the solver that allows to provide an accurate and stable solver for simulation involving low-Mach regions in the flow. This work is a collaboration with Christophe CHALONS and Mathieu GIRARDIN.

Among the numerous practical application of Statistical Process Control (SPC) is the monitoring of the number of defecting (non-conforming) items that are produced from a manufacturing company or the number of the incidents of a disease in a specic area. The basic aim is to detect any kind of change (e.g., an increase in the number of non-conforming items) quickly and accurately. In such cases, the available data are usually discrete (counts) and for process monitoring, the ordinary control charts for attributes (e.g., np-, p-, c- and u-charts) are used in practice. The main assumption is that the data come from the Poisson or the binomial distribution.

Due to technological advancements and automation progress, many processes are now characterized by a low fraction of non-conforming items. That kind of processes are known as high-yield processes and it is very common to have an excessive number of samples with zero non-conforming items. Consequently, due to the inherent over-dispersion of data, the ordinary schemes for attributes cannot be eactively used because of the high false alarm rates and the low statistical power in the detection of changes in the parameters of the process.

In this talk, new control charts, which are suitable for the monitoring of high-yield processes, are proposed and studied. Instead of the ordinary Poisson and binomial distributions, we assume that a proper parametric model for the process is the zero-inaged Poisson (ZIP) or the zero-inated Binomial (ZIB) distribution. We provide the Markov chain methodology for the theoretical study of each chart as well as aspects of their statistical design. Also, numerical comparisons between the dievent control charting techniques are given. Finally, the practical application of the proposed techniques is discussed.
(joint work with Prof. Philippe Castagliola and Prof. Petros Maravelakis)

Chemotaxis is the phenomenon in which cells direct their motion according to a chemical present in their environment. Since experimental observations have shown that the motion of bacteria (e.g. Escherichia Coli) is due to the alternation of 'runs and tumbles', mathematical modelling thanks to a kinetic description has been proposed. The starting point of the study is the so-called Othmer-Dunbar-Alt model governing the dynamics of the distribution function of cells. From this system, macroscopic model can be derived after rescaling. When the taxis is small compared to the unbiased movement of cells, the scaling must be of diffusive type.