Reciprocal diffusions and stochastic differential equations of second order∗

DOI10.1080/17442508808833525zbMath0653.60048OpenAlexW1993938411MaRDI QIDQ3799427

Arthur J. Krener

Publication date: 1988

Published in: Stochastics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/17442508808833525

zbMATH Keywords

continuum mechanicsnonlinear conservation lawssecond order stochastic differential equationssecond order diffusion processes

Mathematics Subject Classification ID

Stochastic ordinary differential equations (aspects of stochastic analysis) (60H10) Hyperbolic conservation laws (35L65) Diffusion processes (60J60) Classical equilibrium statistical mechanics (general) (82B05) Generalities, axiomatics, foundations of continuum mechanics of solids (74A99)

Related Items

Second order stochastic differential equations and non-Gaussian reciprocal diffusions, Reciprocal classes of random walks on graphs, Reciprocal class of jump processes, Fluctuations of bridges, reciprocal characteristics and concentration of measure, Stochastic mechanics of reciprocal diffusions, Couplings, gradient estimates and logarithmic Sobolev inequalitiy for Langevin bridges, Characterization of multivariate stationary Gaussian reciprocal diffusions, Gaussian reciprocal processes and self-adjoint stochastic differential equations of second order, Reciprocal Processes: A Stochastic Analysis Approach, A second order equation for Schrödinger bridges with applications to the hot gas experiment and entropic transportation cost, Reciprocal properties of random fields on undirected graphs, Reciprocal processes. A measure-theoretical point of view, Nearest-neighbour modelling of reciprocal chains, Dynamics and kinematics of reciprocal diffusions, Duality formula for the bridges of a Brownian diffusion: Application to gradient drifts, A stochastic control approach to reciprocal diffusion processes

Cites Work

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• [https://portal.mardi4nfdi.de/wiki/Publication:4140092 The Markov processes of Schr�dinger]
• Reciprocal Processes: The Stationary Gaussian Case