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Updated: Jul 31, 2025
14:18
Automation of Mode Locking in a Nonlinear Polarization Rotation Fiber Laser through Output Polarization Measurements
Published on: February 28, 2016
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Chaotic mode-competition dynamics in a multimode semiconductor laser with optical feedback and injection.
Optics Express
|May 8, 2023
Summary
Controlling chaotic mode dynamics in semiconductor lasers via optical injection accelerates machine learning. This technique shows promise for photonic artificial intelligence applications like reinforcement learning.
Area of Science:
- Physics
- Optoelectronics
- Computer Science
Background:
- Photonic computing offers accelerated information processing for machine learning.
- Multimode semiconductor lasers exhibit mode-competition dynamics relevant to reinforcement learning problems.
Purpose of the Study:
- To numerically evaluate chaotic mode-competition dynamics in a multimode semiconductor laser with optical feedback and injection.
- To explore control techniques for these dynamics using optical signal injection.
Main Methods:
- Numerical evaluation of chaotic mode-competition dynamics.
- Optical signal injection into a longitudinal mode of a multimode semiconductor laser.
- Analysis of dominant mode ratio concerning optical injection strength and frequency detuning.
Main Results:
- Chaotic mode-competition dynamics were observed and controlled via optical injection.
- Dominant mode ratio increased with optical injection strength, with distinct characteristics across modes due to feedback phases.
- A control technique using precise frequency detuning was proposed.
- Regions of large dominant mode ratios were found to be distinct from the injection-locking range.
Conclusions:
- Precise tuning of optical injection parameters can control chaotic mode-competition dynamics in multimode lasers.
- This control method is promising for applications in reinforcement learning and reservoir computing within photonic artificial intelligence.
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