Séminaire de Probabilités L
著者
書誌事項
Séminaire de Probabilités L
（Lecture notes in mathematics, 2252 . Séminaire de probabilités）
Springer, c2019
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注記
Includes bibliographical references
内容説明・目次
内容説明
This milestone 50th volume of the "Seminaire de Probabilites" pays tribute with a series of memorial texts to one of its former editors, Jacques Azema, who passed away in January. The founders of the "Seminaire de Strasbourg", which included Jacques Azema, probably had no idea of the possible longevity and success of the process they initiated in 1967. Continuing in this long tradition, this volume contains contributions on state-of-art research on Brownian filtrations, stochastic differential equations and their applications, regularity structures, quantum diffusion, interlacing diffusions, mod-O convergence, Markov soup, stochastic billiards and other current streams of research.
目次
- Part I In memoriam Jacques Azema. - Un temoignage. - Un dimanche de juin avec Jacques. - Mosaique de Poisson-Voronoi sur une surface. - Sur le retournement du temps. - La martingale d'Azema. - Part II Regular Contributions. - Complementability and Maximality in Different Contexts: Ergodic Theory, Brownian and Poly-Adic Filtrations. - Uniform Entropy Scalings of Filtrations. - Solving Rough Differential Equations with the Theory of Regularity Structures. - On the Euler-Maruyama Scheme for Degenerate Stochastic Differential Equations with Non-sticky Condition. - On a Construction of Strong Solutions for Stochastic Differential Equations with Non-Lipschitz Coefficients: A Priori Estimates Approach. - Heat Kernel Coupled with Geometric Flow and Ricci Flow. - Scaled Penalization of Brownian Motion with Drift and the Brownian Ascent. - Interlacing Diffusions. - Brownian Sheet Indexed by RN: Local Time and Bubbles. - Mod- Convergence, II: Estimates on the Speed of Convergence. - Random Flows Defined by Markov Loops. - Brownian Winding Fields. - Recurrence and Transience of Continuous-Time Open Quantum Walks. - Explicit Speed of Convergence of the Stochastic Billiard in a Convex Set.
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