Decoherence of quantum Markov semigroups
Décomposition du mouvement brownien avec dérive en un minimum local par juxtaposition de ses excursions positives et négatives
Démonstration d'un théorème de F. Knight à l'aide de martingales exponentielles
Démonstration probabiliste du théorème de d'Alembert
Densité des orbites des trajectoires browniennes sous l’action de la transformation de Lévy
Let Tbe a measurable transformation of a probability space , preserving the measureπ. Let X be a random variable with law π. Call K(⋅, ⋅) a regular version of the conditional law of X given T(X). Fix . We first prove that ifB is reachable from π-almost every point for a Markov chain of kernel K, then the T-orbit of π-almost every point X visits B. We then apply this result to the Lévy transform, which transforms the Brownian motion W into the Brownian motion |W| − L, where L is the local time...
Density in small time for Levy processes
Density in small time for Lévy processes
The density of real-valued Lévy processes is studied in small time under the assumption that the process has many small jumps. We prove that the real line can be divided into three subsets on which the density is smaller and smaller: the set of points that the process can reach with a finite number of jumps (Δ-accessible points); the set of points that the process can reach with an infinite number of jumps (asymptotically Δ-accessible points); and the set of points that the process cannot...
Density of paths of iterated Lévy transforms of brownian motion
The Lévy transform of a Brownian motion B is the Brownian motion B(1) given by Bt(1) = ∫0tsgn(Bs)dBs; call B(n) the Brownian motion obtained from B by iterating n times this transformation. We establish that almost surely, the sequence of paths (t → Bt(n))n⩾0 is dense in Wiener space, for the topology of uniform convergence on compact time intervals.
Density of paths of iterated Lévy transforms of Brownian motion
The Lévy transform of a Brownian motion B is the Brownian motion B(1) given by Bt(1) = ∫0tsgn(Bs)dBs; call B(n) the Brownian motion obtained from B by iterating n times this transformation. We establish that almost surely, the sequence of paths (t → Bt(n))n⩾0 is dense in Wiener space, for the topology of uniform convergence on compact time intervals.
Désintégration des fonctionnelles de Markov
Detecting a local perturbation in a continuous scenery.
Développement des distributions suivant les chaos de Wiener et applications à l'analyse stochastique
Différentiabilité des fonctions finement harmoniques.
Différentiabilité fine et différentiabilité sur des compacts
Differentiability of excessive functions of one-dimensional diffusions and the principle of smooth fit
The principle of smooth fit is probably the most used tool to find solutions to optimal stopping problems of one-dimensional diffusions. It is important, e.g., in financial mathematical applications to understand in which kind of models and problems smooth fit can fail. In this paper we connect-in case of one-dimensional diffusions-the validity of smooth fit and the differentiability of excessive functions. The basic tool to derive the results is the representation theory of excessive functions;...
Differentiability of stochastic flow of reflected Brownian motions.
Dirichlet forms, quasiregular functions and Brownian motion.
Discrete Löwner evolution
Distribution of the Brownian motion on its way to hitting zero.
Distributions of truncations of the heat kernel on the complex projective space
Let be a Brownian motion valued in the complex projective space . Using unitary spherical harmonics of homogeneous degree zero, we derive the densities of and of , and express them through Jacobi polynomials in the simplices of and respectively. More generally, the distribution of may be derived using the decomposition of the unitary spherical harmonics under the action of the unitary group yet computations become tedious. We also revisit the approach initiated in [13] and based on...