The goal of Photonics Design Automation is to use algorithmic methods (such as graph theory, optimization methods, statistics, and machine learning) to ease human burden when designing a photonics chip. Here the repo contains many useful references related to photnoics circuits from various perspectives, such as theory, modeling, application. I am hoping to inspire readers to excavate and then address underlying design problems using algorithms. Together, we will push design automation being a necessary compnonent in the photonic design flow and help its design easier than ever.
The reference list below will be updated regularly along the author's reading and research. Want to contribute? If you find some overlooked papers (or even a whole overlooked area), please open issues, contact the author at [email protected], or pull requests. For more info about the author, please see his homepage: https://zhengqigao.github.io/.
Warm Up: Prediction of the Market, BigTech Company
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Global Silicon Photonics Market Size Revenue Expected to Grow USD 9.14 Billion by 2030
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Intel Labs Announces Integrated Photonics Research Advancement
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Nvidia shows what optically linked GPU sytems might look like
Electromagnetic (EM) Basics
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John D. Jackson, 'Classical Electrodynamics'
- A classical textbook in EM. It is very comprehensive and math dense. It is more appropriate to readers who have background in EM.
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David J. Griffiths, 'Introduction to Electrodynamics'
- A classical textbook in EM. Compared to Jackson's, Griffiths's is more beginner friendly. It has many graphical illustrations and the math derivation is step by step. However, a few advanced topics are not covered (e.g., Green functions).
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David H. Staelin, Ann Morgenthaler, and Jin Au Kong 'Electromagnetic Waves'
- A Classical textbook in EM. Jackson's and Griffiths's start from electrostatics, while this book directly starts from electrodynamics. In this sense, it is more suitable if you are looking for a book 'more cut to the point'.
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Katsunari Okamoto, 'Fundamentals of Optical Waveguides'
- The first two chapters give good explanations on modes in waveguide.
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Allan W. Snyder, John D. Love, 'Optical Waveguide Theory'
- Classical and comprehensive.
Introduction to Integrated Silicon Photonics
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Richard Soref 'The Past, Present, and Future of Silicon Photonics'
- A bit old though, published on 2006, but still a good overall summary.
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Winnie N. Ye and Yule Xiong, 'Review of silicon photonics: history and recent advances'
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Lukas Chrostowski and Michael Hochberg, 'Silicon Photonics Design From Devices to Systems'
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Wim Bogaerts, Martin Fiers, and Pieter Dumon 'Design Challenges in Silicon Photonics'
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Near Margalit et al., 'Perspective on the future of silicon photonics and electronics'
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Dan-Xia Xu et al., 'Silicon Photonic Integration Platform—Have We Found the Sweet Spot?'
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Zhengqi Gao, 'Introduction to Photonic Design Automation'
- A 2-page newbie-friendly article. Only high school knowledge required.
Numerical Simulation Techniques (Mode, FDTD, S-Matrix, etc.)
Effective Index Method:
Eigenmode Solver:
Couple Mode Theory:
Finite Difference Time Domain (FDTD):
Scattering Matrix:
Mode Expansion:
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Using and understanding Mode Expansion Monitors
- A rough description on how Lumerical impelments mode expansions.
Inverse Design (Shape/Topology Optimization)
Adjoint method plus gradient descent optimization appears to be the main stream currently. Using gradients in optimization is named first-order method. On the other hand, zero-order method (optimization without gradient) is occasionally used in inverse design of silicon photonics.
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Alexander Y. Piggott et al., 'Fabrication-constrained nanophotonic inverse design'
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Christopher M. Lalau-Keraly et al., 'Adjoint shape optimization applied to electromagnetic design'
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Zhaocheng Liu et al., 'Tackling Photonic Inverse Design with Machine Learning'
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Wei Ma et al., 'Deep learning for the design of photonic structures'
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- Not limited to silicon photonics.
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K. Kojima et al., 'Deep Neural Networks for Inverse Design of Nanophotonic Devices'
Surrogate Model for Simulation (EM Field Prediction)
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Rahul Trivedi et al., 'Data-driven acceleration of photonic simulations'
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Tyler W. Hughes et al., 'Wave physics as an analog recurrent neural network'
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Zongyi Li et al., 'Fourier Neural Operator for Parametric Partial Differential Equations'
Programmable Photonics
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Xiangfeng Chen et al., 'Graph Representation for Programmable Photonic Circuits'
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Daniel Pérez-López et al., 'Multipurpose self-configuration of programmable photonic circuits'
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Wim Bogaerts's presentation on programmable photonics
- Highly recommended. A really nice introduction with lots of figures!
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Aitor López et al., 'Auto-routing algorithm for field-programmable photonic gate arrays'
Optical Neural Network
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Yichen Shen et al., 'Deep learning with coherent nanophotonic circuits'
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Ying Zuo et al., 'All-optical neural network with nonlinear activation functions'
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Ryan Hamerly et al., 'Large-Scale Optical Neural Networks Based on Photoelectric Multiplication'
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J. Bueno et al., 'Reinforcement learning in a large-scale photonic recurrent neural network'
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Qiming Zhang et al., 'Artificial neural networks enabled by nanophotonics'
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H. Zhang et al., 'An optical neural chip for implementing complex-valued neural network'
Variation: Impact, Modeling, and Calibration
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D. Melati et al., 'Real photonic waveguides: guiding light through imperfections'
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S. Johnson et al., 'Perturbation theory for Maxwell’s equations with shifting material boundaries'
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Y. Xing et al., 'Accurate extraction of fabricated geometry using optical measurement'
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Y. Xing et al., 'Capturing the effects of spatial process variations in silicon photonic circuits'
Optical Phased Array (Antenna Array, Beam Steering)
Photonics for Quantumn
Ali W. Elshaari et al., 'Hybrid integrated quantum photonic circuits'
Electronic-Photonic Co-simulation
To me, this topic is a very important one, yet at a very immature stage. The futuer of circuits in my understanding will be a mixture of electronics and photonics on the same chip. Thus, electronic and photonic co-simulation is of huge interest. There are a few works exploring along this direction; even a commerical product, OptiSpice, is now available. However, personally, I feel that the current paradigm for co-simulation is far from satisfying, while tremendous efforts should be devoted to this topic. Of course, since {E,H} for photonics and {I,V} for electronics locate at two different abstract physical level, this topic won't be easy.
Mark A. Neifeld and Wu-Chun Chou, 'Spice-based optoelectronic system simulation'