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Active Matter models commonly consider particles with overdamped dynamics subject to a force (speed) with constant modulus and random direction. Some models include also random noise in particle displacement (Wiener process) resulting in a diffusive motion at short time scales. On the other hand, Ornstein-Uhlenbeck processes consider Langevin dynamics for the particle velocity and predict a motion that is not diffusive at short time scales. However, experiments show that migrating cells may present a varying speed as well as a short-time diffusive behavior. While Ornstein-Uhlenbeck processes can describe the varying speed, Active Mater models can explain the short-time diffusive behavior. Isotropic models cannot explain both: short-time diffusion renders instantaneous velocity ill-defined, hence impeding dynamical equations that consider velocity time-derivatives. On the other hand, both models apply for migrating biological cells and must, in some limit, yield the same observable predictions. Here we propose and analytically solve an Anisotropic Ornstein-Uhlenbeck process that considers polarized particles, with a Langevin dynamics for the particle movement in the polarization direction while following a Wiener process for displacement in the orthogonal direction. Our characterization provides a theoretically robust way to compare movement in dimensionless simulations to movement in dimensionful experiments, besides proposing a procedure to deal with inevitable finite precision effects in experiments or simulations.
This paper studies Langevin equation with random damping due to multiplicative noise and its solution. Two types of multiplicative noise, namely the dichotomous noise and fractional Gaussian noise are considered. Their solutions are obtained explicit
This paper addresses the problem of estimating drift parameter of the Ornstein - Uhlenbeck type process, driven by the sum of independent standard and fractional Brownian motions. The maximum likelihood estimator is shown to be consistent and asympto
We calculate the two-point correlation function <x(t2)x(t1)> for a subdiffusive continuous time random walk in a parabolic potential, generalizing well-known results for the single-time statistics to two times. A closed analytical expression is found
This paper is devoted to parameter estimation of the mixed fractional Ornstein-Uhlenbeck process with a drift. Large sample asymptotical properties of the Maximum Likelihood Estimator is deduced using the Laplace transform computations or the Cameron-Martin formula with extra part from cite{CK19}
We study normal diffusive and subdiffusive processes in a harmonic potential (Ornstein-Uhlenbeck process) on a uniformly growing/contracting domain. Our starting point is a recently derived fractional Fokker-Planck equation, which covers both the cas