Memory-induced Excitability in Optical Cavities

Neurons and other excitable systems can release energy suddenly given a small stimulus. Excitability has recently drawn increasing interest in optics, as it is key to realize all-optical artificial neurons enabling speed-of-light information processing. However, the realization of all-optical excitable units and networks remains challenging. Here we demonstrate how laser-driven optical cavities with memory in their nonlinear response can sustain excitability beyond the constraints of memoryless systems. First we demonstrate different classes of excitability and spiking, and their control in a single cavity with memory. This single-cavity excitability is limited to a narrow range of memory times commensurate with the linear dissipation time. To overcome this limitation, we explore coupled cavities with memory. We demonstrate that this system can exhibit excitability for arbitrarily long memory times, even when the inter-cavity coupling rate is smaller than the dissipation rate. Our coupled-cavity system also sustains spike trains -- a hallmark of neurons -- that spontaneously break mirror symmetry. Our predictions can be readily tested in thermo-optical cavities, where thermal dynamics effectively give memory to the nonlinear optical response. The huge separation between thermal and optical time scales in such cavities is promising for the realization of artificial neurons that can self-organize to the edge of a phase transition, like many biological systems do

How Wettability Controls Nanoprinting

Using large scale molecular dynamics simulations, we study in detail the impact of nanometer droplets of low viscosity on flat substrates versus the wettability of the solid plate. The comparison between the molecular dynamics simulations and different macroscopic models reveals that most of these models do not correspond to the simulation results at the nanoscale, in particular for the maximal contact diameter during the nanodroplet impact (D_{max}). We have developed a new model for D_{max} that is in agreement with the simulation data and also takes into account the effects of the liquid-solid wettability. We also propose a new scaling for the time required to reach the maximal contact diameter t_{max} with respect to the impact velocity, which is also in agreement with the observations. With the new model for D_{max} plus the scaling found for t_{max}, we present a master curve collapsing the evolution of the nanometer drop contact diameter during impact for different wettabilities and different impact velocities. We believe our results may help in designing better nanoprinters since they provide an estimation of the maximum impact velocities required to obtain a smooth and homogenous coverage of the surfaces without dry spots