White noise flashing Brownian pump

A Brownian pump of particles powered by a stochastic flashing ratchet mechanism is studied. The pumping device is embedded in a finite region and bounded by particle reservoirs. In the steady state, we exactly calculate the spatial density profile, the concentration ratio between both reservoirs and the particle flux. A simple numerical scheme is presented allowing for the consistent evaluation of all such observable quantities

On the Generalized Kramers Problem with Oscillatory Memory Friction

The time-dependent transmission coefficient for the Kramers problem exhibits different behaviors in different parameter regimes. In the high friction regime it decays monotonically ("non-adiabatic"), and in the low friction regime it decays in an oscillatory fashion ("energy-diffusion-limited"). The generalized Kramers problem with an exponential memory friction exhibits an additional oscillatory behavior in the high friction regime ("caging"). In this paper we consider an oscillatory memory kernel, which can be associated with a model in which the reaction coordinate is linearly coupled to a nonreactive coordinate, which is in turn coupled to a heat bath. We recover the non-adiabatic and energy-diffusion-limited behaviors of the transmission coefficient in appropriate parameter regimes, and find that caging is not observed with an oscillatory memory kernel. Most interestingly, we identify a new regime in which the time-dependent transmission coefficient decays via a series of rather sharp steps followed by plateaus ("stair-like"). We explain this regime and its dependence on the various parameters of the system

Transverse transport in graphite

Graphite is a layered material showing a strong anisotropy. Among the unconventional properties reported by experiments, the electronic transport along the c-axis, which has direct implications in order to build graphitic devices, remains a controversial topic. We study the influence of inelastic scattering on the electron tunnelling between layers. In the presence of electron electron interactions, tunnelling processes are modified by inelastic scattering events.Comment: 9 pages, no figures Proceedings of the Graphene Conference, MPI PKS Dresden, September 200

On the Generalized Kramers Problem with Exponential Memory Friction

The time-dependent transmission coefficient for the generalized Kramers problem with exponential memory friction has recently been calculated by Kohen and Tannor [D. Kohen and D. J. Tannor, J. Chem. Phys. Vol. 103, 6013 (1995)] using a procedure based on the method of reactive flux and the phase space distribution function. Their analysis is restricted to the high friction regime or diffusion-limited regime. We recently developed a complementary theory for the low-friction energy-diffusion-limited regime in the Markovian limit [Sancho et al., cond-mat/9806001, to appear in J. Chem. Phys.]. Here we generalize our method to the case of an exponential dissipative memory kernel. We test our results, as well as those of Kohen and Tannor, against numerical simulations

An analytical approach to sorting in periodic potentials

There has been a recent revolution in the ability to manipulate micrometer-sized objects on surfaces patterned by traps or obstacles of controllable configurations and shapes. One application of this technology is to separate particles driven across such a surface by an external force according to some particle characteristic such as size or index of refraction. The surface features cause the trajectories of particles driven across the surface to deviate from the direction of the force by an amount that depends on the particular characteristic, thus leading to sorting. While models of this behavior have provided a good understanding of these observations, the solutions have so far been primarily numerical. In this paper we provide analytic predictions for the dependence of the angle between the direction of motion and the external force on a number of model parameters for periodic as well as random surfaces. We test these predictions against exact numerical simulations