Multi-objective genetic algorithm applied to spectroscopic ellipsometry of organic-inorganic hybrid planar waveguides

The applicably of multi-objective optimization to ellipsometric data analysis is presented and a method to handle complex ellipsometric problems such as multi sample or multi angle analysis using multi-objective optimization is described. The performance of a multi-objective genetic algorithm (MOGA)...

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Bibliographic Details
Published in:Optics express 2010-08, Vol.18 (16), p.16580-16586
Main Authors: Fernandes, Vasco R, Vicente, Carlos M S, Wada, Naoya, André, Paulo S, Ferreira, Rute A S
Format: Article
Language:English
Subjects:
Algorithms
Silicon Dioxide - chemistry
Spectrum Analysis - methods
Zirconium - chemistry
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Summary:The applicably of multi-objective optimization to ellipsometric data analysis is presented and a method to handle complex ellipsometric problems such as multi sample or multi angle analysis using multi-objective optimization is described. The performance of a multi-objective genetic algorithm (MOGA) is tested against a single objective common genetic algorithm (CGA). The procedure is applied to the characterization (refractive index and thickness) of planar waveguides intended for the production of optical components prepared sol-gel derived organic-inorganic hybrids, so-called di-ureasils, modified with zirconium tetrapropoxide, Zr(OPr(n))(4) deposited on silica on silicon substrates. The results show that for the same initial conditions, MOGA performs better than the CGA, showing a higher success rate in the task of finding the best final solution.
ISSN:1094-4087
1094-4087
DOI:10.1364/OE.18.016580