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Publication detail

Authors: W. Bogaerts
Title: Teaching photonic integrated circuits with Jupyter notebooks: design, simulation, fabrication
Format: International Conference Proceedings
Publication date: 5/2019
Journal/Conference/Book: Proc. SPIE: Fifteenth Conference on Education and Training in Optics and Photonics: ETOP 2019
Editor/Publisher: SPIE, 
Volume(Issue): 11143 p.111430D
Location: Quebec, Canada
DOI: 10.1117/12.2518401
Citations: 2 (Web of Knowledge / Dimensions.ai - last update: 28/9/2020)
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Download: Download this Publication (4.3MB) (4.3MB)

Abstract

At Ghent University, we have built a course curriculum on integrated photonics, and in particular silicon photonics, based on interactive Jupyter Notebooks. This has been used in short workshops, specialization courses at PhD level, as well as the M.Sc. Photonics Engineering program at Ghent University and the Free University of Brussels. The course material teaches the concepts of on-chip waveguides, basic building blocks, circuits, the design process, fabrication and measurements. The Jupyter notebook environment provides an interface where static didactic content (text, figures, movies, formulas) is mixed with Python code that the user can modify and execute, and interactive plots and widgets to explore the effect of changes in circuits or components. The Python environment supplies a host of scientific and engineering libraries, while the photonic capabilities are based on IPKISS, a commercial design framework for photonic integrated circuits by Luceda Photonics. The IPKISS framework allows scripting of layout and simulation directly from the Jupyter notebooks, so the teaching modules contain live circuit simulation, as well as integration with electromagnetic solvers. Because this is a complete design framework, students can also use it to tape out a small chip design which is fabricated through a rapid prototyping service and then measured, allowing the students to validate the actual performance of their design against the original simulation. The scripting in Jupyter notebooks also provides a self-documenting design flow, and the use of an established design tool guarantees that the acquired skills can be transferred to larger, real-world design projects.


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