  High-dimensional nonlinear dynamical systems including neural networks can be
utilized as a computational resource for information processing. In this sense,
nonlinear wave systems are good candidate for such a computational resource.
Here, we propose and numerically demonstrate information processing based on
nonlinear wave dynamics in microcavity lasers, i.e., optical spatiotemporal
systems at a microscale. One of the remarkable features is the ability of
high-dimensional and nonlinear mapping of input information into the wave
states, enabling efficient and fast information processing at a microscale. We
show that the computational capability for nonlinear/memory tasks is maximized
at the edge of the dynamical stability. Moreover, we also show that the
computational capability can be enhanced by applying a time division
multiplexing technique to the wave dynamics; thus, the computational potential
of the wave dynamics can sufficiently be extracted even when the number of
detectors to monitor the wave states is limited. In addition, we discuss the
merging of optical information processing and optical sensing, opening a novel
method of model-free sensing by using a microcavity reservoir itself as a
sensing element. These results open a way to on-chip photonic computing with
high-dimensional dynamics and a novel model-free sensing scheme.
