Design and Fabrication of Chip-Integrated Coupled Lasers for Photonic Reservoir Computing

Abstract

Reservoir computing is an emerging paradigm in neuromorphic computing, particularly well-suited for processing temporal data such as speech recognition, time-series forecasting, and real-time signal analysis. The use of photonic devices offers significant advantages over traditional electronic implementations, such as higher speed, broader bandwidth, and improved energy efficiency. The core focus of this Senior Thesis is the design and fabrication of strongly coupled diode lasers integrated on a single semiconductor chip. An emphasis is placed on the fabrication procedures of such lasers intersecting at shallow angles, forming a photonic reservoir. By embedding these components within a monolithic chip, the reliance on external optics and complex alignment procedures is eliminated. This streamlined integration not only simplifies the overall architecture, but also reduces the size, cost, and power consumption of the system, paving the way for scalable and practical photonic reservoir computing platforms.