4.6 Article

Modeling nonlinear optical interactions of focused beams in bulk crystals and thin films: A phenomenological approach

Journal

JOURNAL OF APPLIED PHYSICS
Volume 133, Issue 12, Pages -

Publisher

AIP Publishing
DOI: 10.1063/5.0136252

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Coherent nonlinear optical mu-spectroscopy is a powerful tool in material science, but interpreting the data can be challenging due to various effects. To simplify interpretation, this study presents an easy-to-use semi-analytical modeling approach based on Gaussian beams. The model successfully predicts nonlinear optical responses of optical materials, outperforming rigorous simulations in terms of computational time and system requirements.
Coherent nonlinear optical mu-spectroscopy is a frequently used tool in modern material science as it is sensitive to many different local observables, which comprise, among others, crystal symmetry and vibrational properties. The richness in information, however, may come with challenges in data interpretation, as one has to disentangle the many different effects like multiple reflections, phase jumps at interfaces, or the influence of the Guoy-phase. In order to facilitate interpretation, the work presented here proposes an easy-to-use semi-analytical modeling Ansatz, which bases upon known analytical solutions using Gaussian beams. Specifically, we apply this Ansatz to compute nonlinear optical responses of (thin film) optical materials. We try to conserve the meaning of intuitive parameters like the Gouy-phase and the nonlinear coherent interaction length. In particular, the concept of coherence length is extended, which is a must when using focal beams. The model is subsequently applied to exemplary cases of second- and third-harmonic generation. We observe a very good agreement with experimental data, and furthermore, despite the constraints and limits of the analytical Ansatz, our model performs similarly well as when using more rigorous simulations. However, it outperforms the latter in terms of computational power, requiring more than three orders less computational time and less performant computer systems.

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