Inverse Design of Photonic Components

Leuven - Master projects/internships
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About a week ago

Computer assisted silicon photonics devices design

Silicon photonics is a rapidly developing and viable industrial platform for telecom and datacom applications. Alongside with well-established methodologies to design photonic building blocks, new approaches are welcome to improve optical components.

Photonic integrated chip is composed of structures with subwavelength features to guide and govern light at the nano-scale. Gratings and photonic crystals formed by a collection of elements of simple shape like holes and stripes allow to use analytical and semi-analytical approaches for initial device optimization.

Next, finite device dimensions and other fabrication constraints are taken into account and numerical simulations (finite-difference solution to Maxwell’s equations) are conducted. Simple optimization routines like simplex method, scanning device response in parametric space, ect. are adapted to fine-tune the size and position of features of certain shape. The restriction to certain shape of feature can be overcome by intuitive modifications of element geometry. This can improve component specifications however all options and possibilities of device performance remain unraveled.

Ability to design, characterize and optimize devices described by free-shape geometries with permittivity as a function of coordinate inside the structure opens possibility for global device optimization and investigation of fundamental limits of nanophotonic devices.  Inverse design allows for arbitrary spatial permittivity variation bounded only by minimum feature size, selection of materials, given device functionality and design area. In this challenging project student will optimize photonic component, such as splitter or fiber grating coupler, using computationally favorable gradient-based inverse design approach.

Required skills:

  • Intermediate level in math and programming and strong desire to improve these skills
  • Knowledge of Python is essential, hands-on experience with Lumerical is a plus
     

Type of project: Internship, Combination of internship and thesis

Required degree: Master of Engineering Technology, Master of Science

Required background: Physics, Nanoscience & Nanotechnology

Supervising scientists: For further information or for application, please contact Sebastien Lardenois (sebastien.lardenois@imec.be) and Aliaksandra Ivinskaya (aliaksandra.ivinskaya@imec.be).

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