This internship project aims at realizing a preliminary (and preparatory) study prior to a more ambitious project that will be undertaken in the context of a Cifre PhD thesis between Ansys R&D and Inria. The internship will take place in the Atlantis project-team from Inria Center at Université Côte d’Azur in Sophia Antipolis. The overall objective will be to develop and assess an inverse design strategy leveraging a modern global optimization algorithm. Specifically, we want to implement the global optimization of a PIC device by combining the following approaches:
- A DGTD (Discontinuous Galerkin Time-Domain) Maxwell solver [1] to simulate a device and compute a specified figure-of-merit (FoM) for a given design;
- The EGO (Efficient Global Optimization) method, which is a statistical learning-based global optimization algorithm [2] belonging to the family of Bayesian optimization methods [3];
- A shape parameterization technique, which is compliant with the fact that the DGTD method makes use of an unstructured tetrahedral mesh for the simulations.
As an initial use case, we will optimize a symmetric Y-branch (50:50 optical splitter). This basic and well-studied device [4] requires a relatively low number of parameters (< 20) and is therefore well-suited for global optimization.
The individual software components mentioned above are already available in the DIOGENeS software suite developed by the Atlantis project-team. The internship focusses on the geometrical modeling and parametrization of the PIC device as well as the integration of the individual components. The results of the internship will be integrated in DIOGENeS.
[1] S. Lanteri, C. Scheid and J. Viquerat. Analysis of a generalized dispersive model coupled to a DGTD method with application to nanophotonics. SIAM Journal on Scientific Computing, Vol. 39, No. 3, pp. A831–A859 (2017)
[2] D. Jones. Efficient global optimization of expensive black-box functions. Journal of Global Optimization, Vol. 13, No. 4, pp. 455-492 (1998)
[3] R. Garnett. Bayesian Optimization. Cambridge University Press (2023)
[4] https://optics.ansys.com/hc/en-us/articles/360042305274-Inverse-design-of-y-branch
