  Because of the kinematic reversibility of the Stokes equation, fluid mixing
at the microscale requires an interplay between advection and diffusion. Here
we introduce mutual information between particle positions before and after
mixing as a measure of mixing efficiency. We demonstrate its application in a
Couette flow in an annulus and show that non-uniform rotation sequences can
lead to more efficient mixing. We also determine mutual information from
Brownian dynamics simulations using data compression algorithms. Our results
show that mutual information provides a universal and assumption-free measure
of mixing efficiency in microscale flows.
