An effective drift-diffusion model for pandemic propagation and uncertainty prediction.

Predicting pandemic evolution involves complex modeling challenges, typically involving detailed discrete mathematics executed on large volumes of epidemiological data. Making them physics based provides added intuition as well as predictive value. Differential equations have the advantage of offering smooth, well-behaved solutions that try to capture overall predictive trends and averages. In this paper, the canonical susceptible-infected-recovered model is simplified, in the process generating quasi-analytical solutions and fitting functions that agree well with the numerics, as well as infection data across multiple countries. The equations provide an elegant way to visualize the evolution of the pandemic spread, by drawing equivalents with the similar dynamics of a particle, whose location over time represents the growing fraction of the population that is infected. This particle slides down a potential whose shape is set by model epidemiological parameters such as reproduction rate. Potential sources of errors and their growth over time are identified, and the uncertainties are mapped into a diffusive jitter that tends to push the particle away from its minimum. The combined physical understanding and analytical expressions offered by such an intuitive drift-diffusion model sets the foundation for their eventual extension to a multi-patch model while offering practical error bounds and could thus be useful in making policy decisions going forward.

Direct Evidence of Klein and Anti-Klein Tunneling of Graphitic Electrons in a Corbino Geometry.

Transport measurement of electron optics in monolayer graphene p-n junction devices has been traditionally studied with negative refraction and chiral transmission experiments in Hall bar magnetic focusing setups. We show direct signatures of Klein (monolayer) and anti-Klein (bilayer) tunneling with a circular "edgeless" Corbino geometry made out of gated graphene p-n junctions. Noticeable in particular is the appearance of angular sweet spots (Brewster angles) in the magnetoconductance data of bilayer graphene, which minimizes head-on transmission, contrary to conventional Fresnel optics or monolayer graphene which show instead a sharpened collimation of transmission paths. The local maxima on the bilayer magnetoconductance plots migrate to higher fields with increasing doping density. These experimental results are in good agreement with detailed numerical simulations and analytical predictions.

Anatomy of nanomagnetic switching at a 3D topological insulator PN junction.

A P-N junction engineered within a Dirac cone system acts as a gate tunable angular filter based on Klein tunneling. For a 3D topological insulator with a substantial bandgap, such a filter can produce a charge-to-spin conversion due to the dual effects of spin-momentum locking and momentum filtering. We analyze how spins filtered at an in-plane topological insulator PN junction (TIPNJ) interact with a nanomagnet, and argue that the intrinsic charge-to-spin conversion does not translate to an external gain if the nanomagnet also acts as the source contact. Regardless of the nanomagnet's position, the spin torque generated on the TIPNJ is limited by its surface current density, which in turn is limited by the bulk bandgap. Using quantum kinetic models, we calculated the spatially varying spin potential and quantified the localization of the current versus the applied bias. Additionally, with the magnetodynamic simulation of a soft magnet, we show that the PN junction can offer a critical gate tunability in the switching probability of the nanomagnet, with potential applications in probabilistic neuromorphic computing.

Low Power In-Memory Computation with Reciprocal Ferromagnet/Topological Insulator Heterostructures.

The surface state of a 3D topological insulator (3DTI) is a spin-momentum locked conductive state, whose large spin hall angle can be used for the energy-efficient spin-orbit torque based switching of an overlying ferromagnet (FM). Conversely, the gated switching of the magnetization of a separate FM in or out of the TI surface plane can turn on and off the TI surface current. By exploiting this reciprocal behavior, we can use two FM/3DTI heterostructures to design an integrated 1-transistor 1-magnetic tunnel junction random access memory unit (1T1MTJ RAM) for an ultra low power Processing-in-Memory (PiM) architecture. Our calculation involves combining the Fokker-Planck equation with the Nonequilibrium Green Function (NEGF) based flow of conduction electrons and Landau-Lifshitz-Gilbert (LLG) based dynamics of magnetization. Our combined approach allows us to connect device performance metrics with underlying material parameters, which can guide proposed experimental and fabrication efforts.