Resolution of the inverse problem of optical grating testing by means of a neural network

Stephane Robert; Alain Mure-Ravaud

doi:10.1117/12.514126

26 February 2004 Resolution of the inverse problem of optical grating testing by means of a neural network

Stephane Robert, Alain Mure-Ravaud

Proceedings Volume 5252, Optical Fabrication, Testing, and Metrology; (2004) https://doi.org/10.1117/12.514126
Event: Optical Systems Design, 2003, St. Etienne, France

Abstract

The characterization of sub-micrometer period gratings by resolution of the inverse problem has become a real need in the area of the microelectronic. We present an optical scatteromettric method based on the use of a Neural Network (NN). This one permits to learn the relationship linking the diffracted efficiencies to the geometrical parameters. The great advantage of this method is to reject the limitations in resolution that occur with classical microscopic characterization. Theoretical results are demonstrated in this paper. The characterization can be achieved with accuracy close to 5 nm. We also study the index influence on the results and the importance of the choice of the assumed profile shape. Experimental results concerning a silicon 1-μm-period grating are also demonstrated. Finally, a comparison with results obtained by a microscopic characterization permits the validation of the presented method.

Citation Download Citation

Stephane Robert and Alain Mure-Ravaud "Resolution of the inverse problem of optical grating testing by means of a neural network", Proc. SPIE 5252, Optical Fabrication, Testing, and Metrology, (26 February 2004); https://doi.org/10.1117/12.514126

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