En savoir plus
Stochastic analysis is a field of mathematical research having numerous interactions with other domains of mathematics such as partial differential equations, riemannian path spaces, dynamical systems, optimization. It also has many links with applications in engineering, finance, quantum physics, and other fields. This book covers recent and diverse aspects of stochastic and infinite-dimensional analysis. The included papers are written from a variety of standpoints (white noise analysis, Malliavin calculus, quantum stochastic calculus) by the contributors, and provide a broad coverage of the subject.
This volume will be useful to graduate students and research mathematicians wishing to get acquainted with recent developments in the field of stochastic analysis.
Table des matières
Mathematical aspects of decoherence induced classicality in quantum systems.- Hankel operators on Segal-Bargmann spaces.- Malliavin calculus and real Bott periodicity.- Heat equation associated with Lévy laplacian.- Zeta-regularized traces versus the Wodzicki residue as tools in quantum field theory and infinite dimensional geometry.- Quantum stochastic calculus applied to path spaces over Lie groups.- Martingale approximation for self-intersection local time of brownian motion.- Itô formula for generalized functionals of brownian bridge.- Fock space operator valued martingale convergence.- Stochastic integration for compensated Poisson measures and the Lévy-Itô formula.- Exponential ergodicity of classical and quantum Markov birth and death semigroups.- Asymptotic flux across hypersurfaces for diffusion processes.- Reflected backward stochastic differential equation with superlinear growth.- Semidynamical systems with the same order relation.- Infinite-dimensional Lagrange problem and application to stochastic processes.- On portfolio separation in the Merton problem with bankruptcy or default.- Square of white noise unitary evolutions on boson Fock space.- Numerical solution of Wick stochastic differential equations.
Résumé
Stochastic analysis is a field of mathematical research having numerous interactions with other domains of mathematics such as partial differential equations, riemannian path spaces, dynamical systems, optimization. It also has many links with applications in engineering, finance, quantum physics, and other fields. This book covers recent and diverse aspects of stochastic and infinite-dimensional analysis. The included papers are written from a variety of standpoints (white noise analysis, Malliavin calculus, quantum stochastic calculus) by the contributors, and provide a broad coverage of the subject.
This volume will be useful to graduate students and research mathematicians wishing to get acquainted with recent developments in the field of stochastic analysis.
