Thermally Tunable Hybrid Photonic Architecture for Nonlinear Optical Circuits

Abstract

Integrated photonic systems are a leading solution for fast and energy-efficient information processing. We develop a thermally tunable hybrid photonic platform for implementation of coherent optical networks applicable to dedicated computing and machine learning. The hybrid architecture comprises gallium arsenide (GaAs) photonic crystal cavities, silicon nitride (SiNx) grating couplers and waveguides, and chromium (Cr) microheaters on an integrated photonic chip. We utilize the band-edge nonlinearity in GaAs photonic crystal cavity for switching at 6 ps time scale. The cavities are evanescently connected to a common bus waveguide, separating the computation and communication layers. To synchronize the operating frequency, we design metal microheaters that locally, continuously, and reversibly tune photonic crystal cavities to a common resonance. We demonstrate 7 nm tunability range with no significant quality factor deterioration. By coupling the free-space light to the photonic chip, we demonstrate the ...