Noticias en español
A simple model for an epidemic with contact tracing and cluster isolation, and a detection paradox.
Abstract: We determine the distributions of some random variables related to a simple model of an epidemic with contact tracing and cluster isolation, which is inspired by a recent work of Bansaye, Gu and Yuan. Notably, we compute explicitly the asymptotic proportion of isolated clusters with a given size amongst all isolated clusters, conditionally on survival of the epidemic. Somewhat surprisingly, the latter differs from the distribution of the size of a typical cluster at the time of its detection; and we explain the reasons behind this seeming paradox.
Read MoreQuantum Decoherence for probabilists.
Resumen: Quantum decoherence (QD) is today one cornerstone in the development of quantum computing (QC). This refers to the collapse of a quantum state into a classical one. From a mathematical point of view, its modelling has also been a major problem, motivating the development of new research in open systems theory. One could classify today this phenomenon at the interface between non-commutative and commutative probabilities. The general question is: how a quantum evolution becomes classical? Is this inevitable? Shall QC live with that? The talk will provide a panorama on the...
Read MoreRough walks in random environments.
Resumen: We shall discuss functional CLTs for additive functionals of Markov processes and regenerative processes lifted to the rough path space. The limiting rough path has two levels of which the first one is a Brownian motion with a well-known covariance matrix. However, in the second level we see a new feature: it is the iterated integral of the same Brownian motion perturbed by a deterministic linear function called the area anomaly and characterized in terms of the model. With that one obtains sharper information on the limiting path. The construction of new examples for SDE...
Read MoreError Bounds for the One-Dimensional Constrained Langevin Approximation for Density Dependent Markov Chains.
Resumen: The stochastic dynamics of chemical reaction networks are often modeled using continuous-time Markov chains. However, except in very special cases, these processes cannot be analysed exactly and their simulation can be computationally intensive. An approach to this problem is to consider a diffusion approximation. The Constrained Langevin Approximation (CLA) is a reflected diffusion approximation for stochastic chemical reaction networks proposed by Leite & Williams. In this work, we extend this approximation to (nearly) density dependent Markov chains, when the diffusion state...
Read MoreA novel notion of barycenter for probability distributions based on optimal weak mass transport.
Resumen: We introduce weak barycenters of a family of probability distributions, based on the recently developed notion of optimal weak transport of mass. We provide a theoretical analysis of this object and discuss its interpretation in the light of convex ordering between probability measures. In particular, we show that, rather than averaging in a geometric way the input distributions, as the Wasserstein barycenter based on classic optimal transport does, weak barycenters extract common geometric information shared by all the input distributions, encoded as a latent random variable that...
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