Now showing items 1-4 of 4

    • Exact distributions of the maximum and range of random diffusivity processes 

      Grebenkov, D. S.; Sposini, V.; Metzler, R.; Oshanin, G.; Seno, F. (2021-02-09)
      We study the extremal properties of a stochastic process $x_t$ defined by the Langevin equation ${\dot {x}}_{t}=\sqrt{2{D}_{t}}\enspace {\xi }_{t}$, in which $\xi_t$ is a Gaussian white noise with zero mean and $D_t$ is a ...
    • Exact first-passage time distributions for three random diffusivity models 

      Grebenkov, D. S.; Sposini, V.; Metzler, R.; Oshanin, G.; Seno, F. (2021-01-04)
      We study the extremal properties of a stochastic process $x_t$ defined by a Langevin equation $\dot{x}= \sqrt{2D_o V (B_t )} \xi_t$, where $\xi$ is a Gaussian white noise with zero mean, $D_0$ is a constant scale factor, ...
    • Single-trajectory spectral analysis of scaled Brownian motion 

      Sposini, V.; Metzler, R.; Oshanin, G. (2019-06)
      A standard approach to study time-dependent stochastic processes is the power spectral density (PSD), an ensemble-averaged property defined as the Fourier transform of the autocorrelation function of the process in the ...
    • Universal spectral features of different classes of random diffusivity processes 

      Sposini, V.; Grebenkov, D.S.; Metzler, R.; Oshanin, G.; Seno, F. (2020-06-26)
      Stochastic models based on random diffusivities, such as the diffusing- diffusivity approach, are popular concepts for the description of non-Gaussian diffusion in heterogeneous media. Studies of these models typically ...