Multi-objective and constrained design of fibre Bragg gratings using Evolutionary Algorithms.

Area of Science:

• Photonics and Optical Engineering
• Computational Electromagnetics
• Signal Processing

Background:

• High-speed optical communication systems require precise signal extraction.
• Passive optical gratings offer a potential solution for clock signal recovery.
• Existing methods may lack the specificity needed for complex data streams.

Purpose of the Study:

• To design optical gratings for passive extraction of 10 GHz clock signals.
• To optimize gratings based on specific transmission spectrum features.
• To address the challenge of clock recovery in 10 Gbps OTDM RZ encoded data streams.

Main Methods:

• Application of a multi-objective evolutionary algorithm (MOEA).
• Utilizing a real-encoded evolutionary algorithm with elitist multi-objective selection.
• Defining and optimizing four key spectral features (e.g., bandwidth, passband quality).

Main Results:

• A set of optimized grating designs was generated.
• Solutions satisfied multiple spectral objectives to varying degrees.
• The approach accounted for manufacturing and design constraints.

Conclusions:

• MOEA is effective for designing optical gratings with specific spectral requirements.
• The developed method enables passive clock signal extraction in high-speed optical data streams.
• The technique provides a viable pathway for optimizing photonic devices under realistic constraints.