Abstract

Neuromorphic photonics is an exciting field at the intersection of neuroscience, integrated photonics, and microelectronics. To realize large-scale neural network-inspired systems, we must have a toolbox of linear and nonlinear operators. Here, we review state of the art for integrated photonic linear operators, which can perform linear operations using interference or wavelength-division-multiplexing (WDM) techniques, and nonlinear operators, which perform nonlinear operations with a combination of photodetection and modulation. We present some devices that fit into the needed toolbox. A new type of directional coupler, using skin depth engineering of electromagnetic waves, suppresses optical crosstalk and eliminates the need for waveguide bends. An optimized high extinction ratio microring modulator, with which we demonstrate a high operating modulation frequency while having a large extinction ratio > 25 dB. We develop and improve a technique for wafer-scale thermal isolation of optical components, allowing the demonstration of a highly efficient thermo-optic phase shifter which exhibits a measured ∼ 30× improvement on the power efficient and ∼ 25× improvement on thermal parasitic cross talk. In addition to device-level optimization and design, we create a new neuromorphic photonics architecture that combines interference with WDM to create a massively scalable, wavelength-diverse integrated photonic linear neuron. This architecture enables dramatic parallelism and physical footprint reduction, resulting in a highly scalable design system. We demonstrate this architecture with devices we optimized, showing single wavelength operation of a full neural network algorithm that adapts to three logic gates (AND, OR, XOR) with reconfiguration, achieving on-chip accuracies of 96.8%, 99%, and 98.5%, respectively. We also demonstrate this architecture by simultaneously implementing four separate logic gates (OR, AND, XOR, NAND), projecting the outputs at four distinct wavelengths, and achieving on-chip accuracies of 99.87%, 99.05%, 98.05% and 99.73%, respectively. Finally, we developed packages and implemented packaging techniques to address these increasingly complicated circuits like wire bonding, printed circuit board design, and flip-chip thermo-compression bonding. These efforts represent progress towards fully integrated neuromorphic photonic systems.

Library of Congress Subject Headings

Neuromorphics--Materials; Silicon--Optical properties; Photonics; Microelectronics

Publication Date

7-21-2023

Document Type

Dissertation

Student Type

Graduate

Degree Name

Microsystems Engineering (Ph.D.)

Department, Program, or Center

Microsystems Engineering (KGCOE)

Advisor

Stefan F. Preble

Advisor/Committee Member

Gregory Howland

Advisor/Committee Member

Rui Li

Campus

RIT – Main Campus

Plan Codes

MCSE-PHD

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