A genetic algorithm based approach to fiber design for high coherence and large bandwidth supercontinuum generation

Area of Science:

• * Optics and Photonics
• * Materials Science
• * Computational Physics

Background:

• * Supercontinuum (SC) generation is crucial for spectroscopy and optical frequency measurements.
• * Designing optical microstructured fibers with tailored properties (dispersion, nonlinearity) is key for efficient SC generation.
• * Current methods often struggle to optimize fibers for broadband, coherent SC, especially in the mid-infrared (Mid-IR).

Purpose of the Study:

• * To develop a novel, efficient method for designing optical microstructured fibers for SC generation.
• * To achieve highly coherent and large bandwidth SC in the Mid-IR spectrum.
• * To investigate the robustness of designed fiber structures against parameter variations.

Main Methods:

• * A hybrid approach combining a genetic algorithm (GA) with pulse propagation modeling.
• * The genetic algorithm optimizes fiber structure without including pulse propagation within the loop.
• * Design robustness was assessed by analyzing variations in structural parameters.

Main Results:

• * The first known application of a GA for designing optical fibers for SC generation.
• * Optimized tellurite glass fiber (70TeO2-10Na2O-20ZnF2) exhibits near-zero GVD (±2 ps/nm/km) from 2-3 µm.
• * Predicted effective nonlinear coefficient (gamma) of ~174 W⁻¹km⁻¹ at 2 µm.
• * Enhanced SC output with significant bandwidth and coherence compared to single-zero-GVD wavelength fibers.

Conclusions:

• * The GA-based hybrid approach is effective for designing specialized optical fibers for SC generation.
• * The optimized tellurite glass fiber shows promise for generating high-quality Mid-IR SC.
• * This method offers a pathway to robustly design fibers for advanced photonic applications.