Programmable chalcogenide‐based all‐optical deep neural networks

Abstract

Abstract We demonstrate a passive all‐chalcogenide all‐optical perceptron scheme. The network’s nonlinear activation function (NLAF) relies on the nonlinear response of Ge 2 Sb 2 Te 5 to femtosecond laser pulses. We measured the sub‐picosecond time‐resolved optical constants of Ge 2 Sb 2 Te 5 at a wavelength of 1500 nm and used them to design a high‐speed Ge 2 Sb 2 Te 5 ‐tuned microring resonator all‐optical NLAF. The NLAF had a sigmoidal response when subjected to different laser fluence excitation and had a dynamic range of −9.7 dB. The perceptron’s waveguide material was AlN because it allowed efficient heat dissipation during laser switching. A two‐temperature analysis revealed that the operating speed of the NLAF is ns. The percepton’s nonvolatile weights were set using low‐loss Sb 2 S 3 ‐tuned Mach Zehnder interferometers (MZIs). A three‐layer deep neural network model was used to test the feasibility of the network scheme and a maximum training accuracy of 94.5% was obtained. We conclude that combining Sb 2 S 3 ‐programmed MZI weights with the nonlinear response of Ge 2 Sb 2 Te 5 to femtosecond pulses is sufficient to perform energy‐efficient all‐optical neural classifications at rates greater than 1 GHz.