Methods for compact modeling of process variations in silicon photonics devices

Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2018.

Bibliographic Details
Main Author: Martinez, Germain
Other Authors: Duane S. Boning.
Format: Thesis
Language:eng
Published: Massachusetts Institute of Technology 2018
Subjects:
Online Access:http://hdl.handle.net/1721.1/119567
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author Martinez, Germain
author2 Duane S. Boning.
author_facet Duane S. Boning.
Martinez, Germain
author_sort Martinez, Germain
collection MIT
description Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2018.
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spelling mit-1721.1/1195672019-04-10T19:14:27Z Methods for compact modeling of process variations in silicon photonics devices Martinez, Germain Duane S. Boning. Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science. Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science. Electrical Engineering and Computer Science. Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2018. This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections. Cataloged from student-submitted PDF version of thesis. Includes bibliographical references (pages 123-127). Photonic systems are being developed with extensions to existing CMOS processes, and are growing in complexity. Silicon photonics designs are evaluated in simulation using similar methods to those used for CMOS transistor and circuit designs; simulation models for common silicon-based photonics structures and devices currently exist and are used to design larger photonic systems. However, these photonics models are often not constructed with manufacturing variations in mind. This thesis presents methods for creating simulation models for nanophotonic devices that take systematic and random variations from manufacturing into account. Factorial experiment design is used to explore the eect of process variations on photonic device performance. Corner models are constructed using the results from experiment design and capture worst-case variations. The response surface modeling method is employed to develop parameterized compact models. Example variation-aware compact models are generated using these methods for the directional coupler and the Y-branch, two passive devices widely used in silicon photonics. The use of these models is demonstrated through corner and statistical variation analyses of a simple Mach-Zehnder interferometer photonic circuit composed of the directional coupler and Y-branch devices. by Germain Martinez. M. Eng. 2018-12-11T20:40:26Z 2018-12-11T20:40:26Z 2018 2018 Thesis http://hdl.handle.net/1721.1/119567 1076274956 eng MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission. http://dspace.mit.edu/handle/1721.1/7582 127 pages application/pdf Massachusetts Institute of Technology
spellingShingle Electrical Engineering and Computer Science.
Martinez, Germain
Methods for compact modeling of process variations in silicon photonics devices
title Methods for compact modeling of process variations in silicon photonics devices
title_full Methods for compact modeling of process variations in silicon photonics devices
title_fullStr Methods for compact modeling of process variations in silicon photonics devices
title_full_unstemmed Methods for compact modeling of process variations in silicon photonics devices
title_short Methods for compact modeling of process variations in silicon photonics devices
title_sort methods for compact modeling of process variations in silicon photonics devices
topic Electrical Engineering and Computer Science.
url http://hdl.handle.net/1721.1/119567
work_keys_str_mv AT martinezgermain methodsforcompactmodelingofprocessvariationsinsiliconphotonicsdevices