Past exam of the thermal and statistical physics course of the University of Cambridge / 2012 / Paper 1 / 2 / b

Brownian motion arises from many microscopic collisions. A one-dimensional Langevin description isThe fluctuation-dissipation relation ties random forcing to drag, ensuring thermal equilibrium. For a free particle set $\kappa =0$. With initially thermal velocities, its mean-square displacement isIt is ballistic, $(k_{B}T/m)t^2$, at short times and diffusive, $2Dt$, for $t\gg {\tau }_v$. In three dimensions the corresponding long-time result is $6Dt$. At diffusive times, the position propagator from a specified origin is Gaussian with variance $2Dt$ per coordinate. A small sphere in a viscous liquid supplies a physical example; in the slow unbounded-fluid limit its drag is $6\pi {\eta }_{f}a$.

For a harmonic trap, overdamped relaxation has time ${\tau }_{\kappa }=\zeta /\kappa$, equilibrium variance $k_{B}T/\kappa$ and stationary correlationConsequently stationary trapped Brownian displacement obeysConfinement makes this displacement saturate, unlike free diffusion. A trajectory initialized exactly at the centre instead has variance $(k_{B}T/\kappa )(1-e^{-2t/{\tau }_{\kappa }})$; confusing that conditional variance with the stationary displacement gives an erroneous factor of two. The equilibrium position distribution is proportional to $\exp [-\kappa x^2/(2k_{B}T)]$. More general finite confinement has a geometry-dependent equilibrium distribution and bounded displacement, not necessarily a Gaussian one.