activity
20182020
collaborators

5 papers

physics.data-an2020

Stochastic interpolation of sparsely sampled time series via multi-point fractional Brownian bridges

J. Friedrich, S. Gallon, A. Pumir +1

We propose and test a method to interpolate sparsely sampled signals by a stochastic process with a broad range of spatial and/or temporal scales. To this end, we extend the notion…

physics.flu-dyn2020

Probability Density Functions in Homogeneous and Isotropic Magneto-Hydrodynamic Turbulence

J. Friedrich

We derive a hierarchy of evolution equations for multi-point probability density functions in magneto-hydrodynamic (MHD) turbulence. We discuss the relation to the moment hierarchy…

physics.flu-dyn2019

Modelling Lagrangian velocity and acceleration in turbulent flows as infinitely differentiable stochastic processes

Bianca Viggiano, Jan Friedrich, Romain Volk +3

We develop a stochastic model for Lagrangian velocity as it is observed in experimental and numerical fully developed turbulent flows. We define it as the unique statistically stat…

physics.comp-ph2018

Instanton based importance sampling for rare events in stochastic PDEs

Lasse Ebener, Georgios Margazoglou, Jan Friedrich +2

We present a new method for sampling rare and large fluctuations in a non-equilibrium system governed by a stochastic partial differential equation (SPDE) with additive forcing. To…

physics.flu-dyn2018

Multiscale velocity correlations in turbulence and Burgers turbulence: Fusion rules, Markov processes in scale, and multifractal predictions

Jan Friedrich, Georgios Margazoglou, Luca Biferale +1

We compare different approaches towards an effective description of multi-scale velocity field correlations in turbulence. Predictions made by the operator product expansion, the s…