Optimizations of optical chaos in semiconductor lasers based on multiobjective genetic algorithms

Area of Science:

• Nonlinear dynamics
• Semiconductor laser physics
• Information theory

Background:

• Chaotic temporal waveforms are crucial for secure communications and random number generation.
• Semiconductor lasers with time-delayed feedback exhibit complex chaotic dynamics.
• Optimizing chaotic signal properties like bandwidth and complexity is essential for practical applications.

Purpose of the Study:

• To investigate and optimize the frequency bandwidth, autocorrelation function, and complexity of chaotic waveforms.
• To explore the relationships between these properties and control parameters in coupled semiconductor lasers.
• To understand the trade-offs involved in optimizing chaotic laser outputs.

Main Methods:

• Utilized unidirectionally coupled semiconductor lasers with time-delayed optical feedback.
• Employed multiobjective genetic algorithms to search for optimal control parameters.
• Analyzed frequency bandwidth, autocorrelation function, and maximum Lyapunov exponent.

Main Results:

• Achieved simultaneous optimization of effective bandwidth, autocorrelation peak value, and maximum Lyapunov exponent.
• Identified a conflicting relationship between effective bandwidth enhancement and time-delay signature suppression.
• Revealed a detailed correlation between the maximum Lyapunov exponent and the autocorrelation function's peak value.

Conclusions:

• Multiobjective optimization can effectively tune chaotic laser dynamics.
• Balancing bandwidth and security (time-delay suppression) presents a significant challenge.
• The interplay between chaos complexity and signal predictability is further elucidated.