Scattering on the cloud: scaling-up wave physics computations

With applications from photonics to seismology, wave scattering is ubiquitous in physics. Yet, to study scattering in highly heterogeneous materials, evidence must be obtained from theoretical approximations and surface measurements. Numerical approaches can offer an insight into the wave behavior deep within a complex structure; however, the large scale, with respect to the short wavelength of light, of most systems of interest makes photonic simulations some of the most challenging numerical problems. Memory and time constraints typically limit coherent light scattering calculations to the micrometer scale in 2D and to the nanoscale in 3D. The study of large photonic structures, or scattering in biological samples larger than a few cells, remains out of reach of conventional computational methods. Here, we highlight a connection between the wave equation that governs light-scattering and the structure of a recurrent network. A one-to-one correspondence enables us to leverage efficient machine learning infrastructure and address coherent scattering problems on an unprecedented scale.