Experimental demonstration of silicon photonic devices optimized by a flexible and deterministic pixel-by-pixel technique

We present the experimental realization of photonic devices optimized by a pixel-by-pixel binary optimization method, which can straightforwardly take into account the technological constraints such as minimum feature sizes in the fabrication process. In this approach, for each iteration, one considers all the candidate structures that differ by a single pixel from the starting structure and update by adopting the structure that has the best figure of merit among all candidate structures. This approach can be implemented with high computational efficiency using a Green's function method. The devices optimized by this approach have been realized on 200 mm and 300 mm Silicon-On-Insulator platforms, using either e-beam lithography or deep-UV immersion lithography. Characterizations experimentally demonstrate the reliability of the method, given the technological constraints of Silicon Photonics.

[1]  Salim Boutami,et al.  Efficient pixel-by-pixel optimization of photonic devices utilizing the Dyson’s equation in a Green’s function formalism: Part II. Implementation using standard electromagnetic solvers , 2019 .

[2]  Dries Vercruysse,et al.  Fully-automated optimization of grating couplers. , 2017, Optics express.

[3]  S. Glavic,et al.  Feasible adjoint sensitivity technique for EM design optimization , 2002, 2002 IEEE MTT-S International Microwave Symposium Digest (Cat. No.02CH37278).

[4]  Olivier J. F. Martin,et al.  Electromagnetic scattering in polarizable backgrounds , 1998 .

[5]  Alexander Y. Piggott,et al.  Inverse design and demonstration of a compact and broadband on-chip wavelength demultiplexer , 2015, Nature Photonics.

[6]  A. Yaghjian.  Electric dyadic Green's functions in the source region , 1980 .

[7]  Shanhui Fan,et al.  Method for sensitivity analysis of photonic crystal devices. , 2004 .

[8]  Dries Vercruysse,et al.  Analytical level set fabrication constraints for inverse design , 2019, Scientific Reports.

[9]  Olivier J. F. Martin,et al.  Iterative scheme for computing exactly the total field propagating in dielectric structures of arbitrary shape , 1994 .

[10]  David J. Lockwood Pavesi,et al.  Silicon Fundamentals for Photonics Applications , 2004 .

[11]  Eli Yablonovitch,et al.  Adjoint shape optimization applied to electromagnetic design. , 2013, Optics express.

[12]  N. Vulliet,et al.  Recent progress in Silicon Photonics R&D and manufacturing on 300mm wafer platform , 2015, 2015 Optical Fiber Communications Conference and Exhibition (OFC).

[13]  Alexander Y. Piggott,et al.  Fabrication-constrained nanophotonic inverse design , 2016, Scientific Reports.

[14]  S. Fan,et al.  Efficient pixel-by-pixel optimization of photonic devices utilizing the Dyson’s equation in a Green’s function formalism: Part I Implementation with the method of discrete dipole approximation , 2019, Journal of the Optical Society of America B.

[15]  K. Yee.  Numerical solution of initial boundary value problems involving maxwell's equations in isotropic media , 1966 .

[16]  Jesse Lu,et al.  Objective-first design of high-efficiency, small-footprint couplers between arbitrary nanophotonic waveguide modes. , 2012, Optics express.

[17]  Salim Boutami,et al.  Determining the optimal learning rate in gradient-based electromagnetic optimization using the Shanks transformation in the Lippmann-Schwinger formalism. , 2020, Optics letters.

[18]  Allen Taflove,et al.  Application of the Finite-Difference Time-Domain Method to Sinusoidal Steady-State Electromagnetic-Penetration Problems , 1980, IEEE Transactions on Electromagnetic Compatibility.

[19]  Jesper Mørk,et al.  Maximizing the quality factor to mode volume ratio for ultra-small photonic crystal cavities , 2018, Applied Physics Letters.

[20]  B. Shen,et al.  An integrated-nanophotonics polarization beamsplitter with 2.4 × 2.4 μm2 footprint , 2015, Nature Photonics.