Contact electrification of dielectric grains forms the basis for a myriad of physical phenomena. However, even the basic aspects of collisional charging between grains are still unclear. Here we develop a new experimental method, based on acoustic levitation, which allows us to controllably and repeatedly collide two sub-millimeter grains and measure the evolution of their electric charges. This is therefore the first tribocharging experiment to provide complete electric isolation for the grain-grain system from its surroundings. We use this method to measure collisional charging rates between pairs of grains for three different material combinations: polyethylene-polyethylene, polystyrene-polystyrene, and polystyrene-sulfonated polystyrene. The ability to directly and noninvasively collide particles of different constituent materials, chemical functionality, size, and shape opens the door to detailed studies of collisional charging in granular materials. arXiv:1910.09669v1 [cond-mat.soft]

The renormalization group (RG) is a class of theoretical techniques used to explain the collective physics of interacting, many-body systems. It has been suggested that the RG formalism may be useful in finding and interpreting emergent low-dimensional structure in complex systems outside of the traditional physics context, such as in biology or computer science. In such contexts, one common dimensionality-reduction framework already in use is information bottleneck (IB), in which the goal is to compress an ``input'' signal X while maximizing its mutual information with some stochastic ``relevance'' variable Y. IB has been applied in the vertebrate and invertebrate processing systems to characterize optimal encoding of the future motion of the external world. Other recent work has shown that the RG scheme for the dimer model could be ``discovered'' by a neural network attempting to solve an IB-like problem. This manuscript explores whether IB and any existing formulation of RG are formally equivalent. A class of soft-cutoff non-perturbative RG techniques are defined by families of non-deterministic coarsening maps, and hence can be formally mapped onto IB, and vice versa. For concreteness, this discussion is limited entirely to Gaussian statistics (GIB), for which IB has exact, closed-form solutions. Under this constraint, GIB has a semigroup structure, in which successive transformations remain IB-optimal. Further, the RG cutoff scheme associated with GIB can be identified. Our results suggest that IB can be used to impose a notion of ``large scale'' structure, such as biological function, on an RG procedure.