Thermally tunable hybrid photonic architecture for nonlinear optical circuits

TL;DR

This paper presents a thermally tunable hybrid photonic platform combining GaAs photonic crystal cavities, SiN_x components, and Cr microheaters, enabling precise control of optical resonances for integrated photonic computing.

Contribution

It introduces a novel integrated photonic architecture with thermally tunable cavities for enhanced optical computing and machine learning applications.

Findings

Demonstrated reversible thermal tuning of photonic crystal cavities.

Integrated platform supports coherent optical network functionalities.

Potential for scalable optical computing and machine learning.

Abstract

We develop a thermally tunable hybrid photonic platform comprising gallium arsenide (GaAs) photonic crystal cavities, silicon nitride (SiN$_x$) grating couplers and waveguides, and chromium (Cr) microheaters on an integrated photonic chip. The GaAs photonic crystal cavities are evanescently connected to a common bus waveguide, separating the computation and communication layers. The microheaters are designed to continuously and reversibly tune distant photonic crystal cavities to a common resonance. This architecture can be implemented in a coherent optical network for dedicated optical computing and machine learning.