Optical Anderson localization in one-dimension: a non-Monte Carlo approach for continuous disorder

Glen J. Kissel

doi:10.1117/12.860853

10 September 2010 Optical Anderson localization in one-dimension: a non-Monte Carlo approach for continuous disorder

Glen J. Kissel

Proceedings Volume 7754, Metamaterials: Fundamentals and Applications III; 775419 (2010) https://doi.org/10.1117/12.860853
Event: SPIE NanoScience + Engineering, 2010, San Diego, California, United States

Abstract

A long product of random transfer matrices is frequently used to model disordered one-dimensional photonic bandgap structures in order to investigate optical Anderson localization. The Lyapunov exponent of this long matrix product, known to exist from Furstenberg's theorem, is identified as the localization factor (inverse localization length). It is not unusual to have 5,000,000 random matrices with Monte Carlo chosen elements in one product to calculate a single Lyapunov exponent, and then have results averaged over as many as 10,000 ensembles. The entire process has to be repeated for 100 or more frequencies to clearly show the frequency dependence of the optical localization effects. This paper instead uses a non-Monte Carlo numerical technique to calculate the Lyapunov exponents. This technique, by Froyland and Aihara, is especially suited to the case where the disorder in the photonic bandgap structure is discrete. Namely, it is used to calculate the probability distribution of the direction of the vector propagated by the long chain of random matrices by finding the left eigenvector of a certain sparse row-stochastic matrix. This distribution is used in Furstenberg's integral formula to calculate the Lyapunov exponent. Now this technique is extended to the case where the random elements of the photonic bandgap transfer matrices are intended to be chosen from a continuous distribution. Specifically, discrete probability mass functions whose moments increasingly match those of a uniform probability density function are used with the Froyland-Aihara method. A very significant savings in computation time is noted compared to Monte Carlo approaches.

Citation Download Citation

Glen J. Kissel "Optical Anderson localization in one-dimension: a non-Monte Carlo approach for continuous disorder", Proc. SPIE 7754, Metamaterials: Fundamentals and Applications III, 775419 (10 September 2010); https://doi.org/10.1117/12.860853

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