Abstract: A photonics-assisted platform for time series prediction and classification that performs signal processing directly after the signal acquisition before any analog-to-digital conversion by using a hardware neural network with recurrent connections, implemented in a silicon photonic chip. This neural network recurrency can be implemented in silicon photonics with a much lower latency than state-of-the-art electronic systems. The recurrent neural network can detect temporal correlations and extract features from the time series signal, and therefore reduce the latency constraints for the analog-to-digital conversion and further digital signal processing.

Abstract: According to various embodiments, an all-optical thresholder device is disclosed. The all-optical thresholder device includes a Mach-Zehnder interferometer (MZI) coupled to a Mach-Zehnder coupler (MZC). The MZI includes at least one microring resonator (MRR) and a first tunable element, where the MRR further includes a second tunable element. The MZC includes a third tunable element. The first, second, and third tunable elements are configured to control biases of the all-optical thresholder device to achieve a desired power transfer function.

Abstract: According to various embodiments, an all-optical thresholder device is disclosed. The all-optical thresholder device includes a Mach-Zehnder interferometer (MZI) coupled to a Mach-Zehnder coupler (MZC). The MZI includes at least one microring resonator (MRR) and a first tunable element, where the MRR further includes a second tunable element. The MZC includes a third tunable element. The first, second, and third tunable elements are configured to control biases of the all-optical thresholder device to achieve a desired power transfer function.

Abstract: A processing device comprises a plurality of artificial neurons comprising first and second artificial neurons, at least one optical connection between an optical output of the first artificial neuron and an optical input of the second artificial neuron, the optical input comprising a photosensitive element, at least one weighting element connected to the optical input of the second artificial neuron, configured to modify a gain of the optical input of the second artificial neuron, and at least one nonlinear element having an input and connected to the optical output of the first artificial neuron, configured to activate the optical output when a signal received at the input of the at least one nonlinear element rises above a threshold, wherein the optical output of the first artificial neuron comprises at least one thin film light-generating component. An LED neuron is also described.