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# Documents  Olla, Stefano | enregistrements trouvés : 18

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## On the weak invariance principle and its quenched version under projective criteria Merlevède, Florence | CIRM

Post-edited

Research talks;Probability and Statistics

In this talk, we shall first review some projective criteria under which the central limit theorem holds. The projective criteria considered will be the Heyde criterion, the Hannan criterion, the Maxwell-Woodroofe condition and the Dedecker-Rio's condition. We shall also investigate under which projective criteria the reinforced versions of the CLT such as the weak invariance principle or the quenched CLT (and its functional form) still hold.

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## Pathwise regularisation by noise in PDEs Gubinelli, Massimiliano | CIRM H

Post-edited

Research talks;Partial Differential Equations;Probability and Statistics

We discuss some examples of the "good" effects of "very bad", "irregular" functions. In particular we will look at non-linear differential (partial or ordinary) equations perturbed by noise. By defining a suitable notion of "irregular" noise we are able to show, in a quantitative way, that the more the noise is irregular the more the properties of the equation are better. Some examples includes: ODE perturbed by additive noise, linear stochastic transport equations and non-linear modulated dispersive PDEs. It is possible to show that the sample paths of Brownian motion or fractional Brownian motion and related processes have almost surely this kind of irregularity. (joint work with R. Catellier and K. Chouk) We discuss some examples of the "good" effects of "very bad", "irregular" functions. In particular we will look at non-linear differential (partial or ordinary) equations perturbed by noise. By defining a suitable notion of "irregular" noise we are able to show, in a quantitative way, that the more the noise is irregular the more the properties of the equation are better. Some examples includes: ODE perturbed by additive noise, linear ...

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## Collective dynamics in life sciences - Lecture 1. Collective dynamics and self-organization in biological systems: challenges and some examples Degond, Pierre | CIRM H

Post-edited

Research School;Partial Differential Equations;Mathematical Physics;Mathematics in Science and Technology

Lecture 1. Collective dynamics and self-organization in biological systems : challenges and some examples.

Lecture 2. The Vicsek model as a paradigm for self-organization : from particles to fluid via kinetic descriptions

Lecture 3. Phase transitions in the Vicsek model : mathematical analyses in the kinetic framework.

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## Entropy methods for the Boltzmann equation :lectures from a special semester at the centre Emile Borel Rezakhanlou, Fraydoun ; Villani, Cédric ; Golse, François ; Olla, Stefano | Springer 2008

Congrès

- 105 p.
ISBN 978-3-540-73704-9

Lecture notes in mathematics , 1916

Localisation : Collection 1er étage

mécanique des fluides # structure anatomique # structure moléculaire # théorie cinétique du gaz # théorie de l'information # mécanique statistique # processus aléatoire # système de particule en intéraction aléatoire

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## Radiative transport and homogenization for the random Schrödinger equation Ryzhik, Lenya | CIRM H

Multi angle

Research talks;Partial Differential Equations;Probability and Statistics

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## Some applications of irreversibility Rey-Bellet, Luc | CIRM H

Multi angle

Research talks;Probability and Statistics

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## Steady states and long range correlations in driven systems - Lecture 1 Mukamel, David | CIRM H

Multi angle

Research School;Mathematical Physics

In these three lectures steady states and dynamical properties of nonequilibrium systems will be discussed.
Systems driven out of thermal equilibrium often reach a steady state which under generic conditions exhibits long-range correlations. This is very different from systems in thermal equilibrium where long-range correlations develop only at phase transition points. In some cases these correlations even lead to long-range order in d=1 dimension, of the type occurring in traffic jams. Simple examples of such correlations induced in the steady state of driven systems will be presented and discussed. Close correspondence of these nonequilibrium steady states to electrostatic potentials induces by charge distribution will be pointed out.
Another class which will be discussed is that of systems with boundary drive, such as in heat conduction problems, where anomalous heat conduction takes place in low dimensions. In addition some similarities between driven systems and equilibrium systems with long-range interactions will be elucidated.
In these three lectures steady states and dynamical properties of nonequilibrium systems will be discussed.
Systems driven out of thermal equilibrium often reach a steady state which under generic conditions exhibits long-range correlations. This is very different from systems in thermal equilibrium where long-range correlations develop only at phase transition points. In some cases these correlations even lead to long-range order in d=1 ...

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## Steady states and long range correlations in driven systems - Lecture 2 Mukamel, David | CIRM H

Multi angle

Research School;Mathematical Physics

In these three lectures steady states and dynamical properties of nonequilibrium systems will be discussed.
Systems driven out of thermal equilibrium often reach a steady state which under generic conditions exhibits long-range correlations. This is very different from systems in thermal equilibrium where long-range correlations develop only at phase transition points. In some cases these correlations even lead to long-range order in d=1 dimension, of the type occurring in traffic jams. Simple examples of such correlations induced in the steady state of driven systems will be presented and discussed. Close correspondence of these nonequilibrium steady states to electrostatic potentials induces by charge distribution will be pointed out.
Another class which will be discussed is that of systems with boundary drive, such as in heat conduction problems, where anomalous heat conduction takes place in low dimensions. In addition some similarities between driven systems and equilibrium systems with long-range interactions will be elucidated.
In these three lectures steady states and dynamical properties of nonequilibrium systems will be discussed.
Systems driven out of thermal equilibrium often reach a steady state which under generic conditions exhibits long-range correlations. This is very different from systems in thermal equilibrium where long-range correlations develop only at phase transition points. In some cases these correlations even lead to long-range order in d=1 ...

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## Nonconventional limit theorems in probability and dynamical systems Kifer, Yuri | CIRM

Multi angle

Research talks;Dynamical Systems and Ordinary Differential Equations;Probability and Statistics

We discuss various limit theorems for "nonconventional" sums of the form $\sum ^N_{n=1}F\left ( \xi \left ( n \right ),\xi \left ( 2n \right ),...,\xi \left ( \ell n \right ) \right )$ where $\xi \left ( n \right )$ is a stochastic process or a dynamical system. The motivation for this study comes, in particular, from many papers about nonconventional ergodic theorems appeared in the last 30 years. Such limit theorems describe multiple recurrence properties of corresponding stochastic processes and dynamical systems. Among our results are: central limit theorem, a.s. central limit theorem, local limit theorem, large deviations and averaging. Some multifractal type questions and open problems will be discussed, as well.
Keywords : limit theorems - nonconventional sums - multiple recurrence
We discuss various limit theorems for "nonconventional" sums of the form $\sum ^N_{n=1}F\left ( \xi \left ( n \right ),\xi \left ( 2n \right ),...,\xi \left ( \ell n \right ) \right )$ where $\xi \left ( n \right )$ is a stochastic process or a dynamical system. The motivation for this study comes, in particular, from many papers about nonconventional ergodic theorems appeared in the last 30 years. Such limit theorems describe multiple ...

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## Fast slow systems with chaotic noise Kelly, David | CIRM H

Multi angle

Research talks;Dynamical Systems and Ordinary Differential Equations;Probability and Statistics

It has long been observed that multi-scale systems, particularly those in climatology, exhibit behavior typical of stochastic models, most notably in the unpredictability and statistical variability of events. This is often in spite of the fact that the underlying physical model is completely deterministic. One possible explanation for this stochastic behavior is deterministic chaotic effects. In fact, it has been well established that the statistical properties of chaotic systems can be well approximated by stochastic differential equations. In this talk, we focus on fast-slow ODEs, where the fast, chaotic variables are fed into the slow variables to yield a diffusion approximation. In particular we focus on the case where the chaotic noise is multidimensional and multiplicative. The tools from rough path theory prove useful in this difficult setting. It has long been observed that multi-scale systems, particularly those in climatology, exhibit behavior typical of stochastic models, most notably in the unpredictability and statistical variability of events. This is often in spite of the fact that the underlying physical model is completely deterministic. One possible explanation for this stochastic behavior is deterministic chaotic effects. In fact, it has been well established that the ...

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## Functional convergence for dependent heavy-tailed models Jakubowski, Adam | CIRM

Multi angle

Research talks;Probability and Statistics;Topology

The Skorokhod space is natural for modeling trajectories of most time series with heavy tails. We give a systematic account of topologies on the Skorokhod space. The applicability of each topology is illustrated by examples of suitable dependent stationary sequences, for which the corresponding functional limit theorem holds.

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## The almost sure invariance principle for beta-mixing measures Haydn, Nicolai | CIRM

Multi angle

Research talks;Dynamical Systems and Ordinary Differential Equations;Probability and Statistics

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## Concentration properties of dynamical systems Gouëzel, Sébastien | CIRM

Multi angle

Research talks;Dynamical Systems and Ordinary Differential Equations;Probability and Statistics

Concentration is an important property of independent random variable, showing that any reasonable function of such variables does not vary a lot around its mean. Observables generated by the iteration of a chaotic enough dynamical system often share a lot of properties with independent random variables. In this survey talk, we discuss several situations where one can prove concentration for them, in uniformly or non-uniformly hyperbolic situations. We also explain why such a property is important to answer relevant geometric or dynamical questions.
concentration - martingales - dynamical systems - Young towers - uniform hyperbolicity - moment bounds
Concentration is an important property of independent random variable, showing that any reasonable function of such variables does not vary a lot around its mean. Observables generated by the iteration of a chaotic enough dynamical system often share a lot of properties with independent random variables. In this survey talk, we discuss several situations where one can prove concentration for them, in uniformly or non-uniformly hyperbolic ...

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## Some examples of homogenization related rough paths Friz, Peter K. | CIRM H

Multi angle

Research talks;Partial Differential Equations;Probability and Statistics

We discuss the rough path principle and some of its applications to problems of homogenization.

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## Collective dynamics in life sciences - Lecture 2. The Vicsek model as a paradigm for self-organization: from particles to fluid via kinetic descriptions Degond, Pierre | CIRM H

Multi angle

Research School;Partial Differential Equations;Mathematical Physics;Mathematics in Science and Technology

Lecture 1. Collective dynamics and self-organization in biological systems : challenges and some examples.

Lecture 2. The Vicsek model as a paradigm for self-organization : from particles to fluid via kinetic descriptions

Lecture 3. Phase transitions in the Vicsek model : mathematical analyses in the kinetic framework.

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## Collective dynamics in life sciences - Lecture 3. Phase transitions in the Vicsek model: mathematical analyses in the kinetic framework Degond, Pierre | CIRM H

Multi angle

Research School;Partial Differential Equations;Mathematical Physics;Mathematics in Science and Technology

Lecture 1. Collective dynamics and self-organization in biological systems : challenges and some examples.

Lecture 2. The Vicsek model as a paradigm for self-organization : from particles to fluid via kinetic descriptions

Lecture 3. Phase transitions in the Vicsek model : mathematical analyses in the kinetic framework.

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## Fluctuations in Markov processes:time symmetry and martingale approximation Komorowski, Tomasz ; Landim, Claudio ; Olla, Stefano | Springer 2012

Ouvrage

- xvii; 491 p.
ISBN 978-3-642-29879-0

Grundlehren der mathematischen wissenschaften , 0345

Localisation : Collection 1er étage

processus de Markov # changement climatique # martingale # théorème de la limite centrale # processus stochastique # théorème des limites

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## Milieux aléatoires Gantert, Nina ; Garnier, Josselin ; Olla, Stefano ; Comets, Francis ; Pardoux, Etienne | Société Mathématique de France 2001

Ouvrage

- 133 p.
ISBN 978-2-85629-127-6

Panoramas et synthèses , 0012

Localisation : Collection 1er étage

milieux aléatoire # propagation d'onde # mouvement brownien # obstacle poissonnien # marche aléatoire # diffusion dans un potentiel aléatoire # homogénéisation stochastique # système de particule en intéraction

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