Nanophotonic Device Design from Conventional to Mathematical Optimization-assisted Method

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As photonic integrated circuits become more advanced with different multiplexing techniques, the demand for sophisticated nanophotonic devices increases. The conventional nanophotonic design method is showing limitations with this trend. Firstly, as the nanophotonic devices become more sophisticated, only highly experienced photonic designers who have a deep understanding of photonics can propose ideas to fulfill these demands. Secondly, the sizes of conventionally designed devices tend to increase to meet the multifunctional requirements. Novel mathematical optimization-assisted methods are promising tools to significantly reduce the size of silicon photonic components while maintaining their functionality and performance. These methods have been investigated intensively over the past decades. In this talk, the conventional nanophotonic device design methods are reviewed. The mathematical description of the nanophotonic device design is given. Then, the mathematical optimization-assisted design methods are discussed, including heuristic methods and the adjoint method. Finally, the possible future directions of mathematical optimization-assisted methods will be discussed, including potential limitations and problems that still need to be solved.



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  • Date: 12 Apr 2022
  • Time: 01:00 PM to 01:45 PM
  • All times are (GMT-05:00) Canada/Eastern
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This is an in-person event only. 

Attendees must complete the following self-assessment before coming on campus.

https://www.mcgill.ca/coronavirus/self-evaluation-form

 

 

  • McGill University
  • 3630 University Street
  • Montreal, Quebec
  • Canada
  • Building: Trottier Engineering Building
  • Room Number: TR0070

  • Starts 04 April 2022 05:28 AM
  • Ends 12 April 2022 10:00 AM
  • All times are (GMT-05:00) Canada/Eastern
  • No Admission Charge


  Speakers

Guowu Zhang of McGill University

Topic:

Nanophotonic Device Design from Conventional to Mathematical Optimization-assisted Method

As photonic integrated circuits become more advanced with different multiplexing techniques, the demand for sophisticated nanophotonic devices increases. The conventional nanophotonic design method is showing limitations with this trend. Firstly, as the nanophotonic devices become more sophisticated, only highly experienced photonic designers who have a deep understanding of photonics can propose ideas to fulfill these demands. Secondly, the sizes of conventionally designed devices tend to increase to meet the multifunctional requirements. Novel mathematical optimization-assisted methods are promising tools to significantly reduce the size of silicon photonic components while maintaining their functionality and performance. These methods have been investigated intensively over the past decades. In this talk, the conventional nanophotonic device design methods are reviewed. The mathematical description of the nanophotonic device design is given. Then, the mathematical optimization-assisted design methods are discussed, including heuristic methods and the adjoint method. Finally, the possible future directions of mathematical optimization-assisted methods will be discussed, including potential limitations and problems that still need to be solved.

Biography:

Guowu Zhang received his B.E. degree in optical information science and technology from the Huazhong University of Science and Technology, Wuhan, China, in 2015, and his M.S. degree in optical engineering from Zhejiang University, Hangzhou, China, in 2018. Currently, he is working toward his Ph.D. degree in the Department of Electrical and Computer Engineering at McGill University, Montreal, Canada under the supervision of Prof. Odile Liboiron-Ladouceur, where he works on advanced inverse design algorithms. His research interests are in mode division multiplexing (MDM), numerical optimization method (convex/non-convex optimization) for nanophotonic device design.

Email:

Address:McGill University, Department of Electrical and Computer Engineering, Montreal, Quebec, Canada