Multi-parameter optimisation of dual-pump NALM fibre laser using machine-learning approaches

Keyphrases

• Nonlinear Optical Loop Mirror 100%
• Pumping Power 100%
• Fiber Laser 100%
• Dual Pumps 100%
• Multi-parameter Optimization 100%
• Machine Learning Approach 100%
• Active Fiber 66%
• Nonlinear Polarization Evolution 66%
• Figure-of-eight 66%
• Machine Learning Techniques 33%
• Mode-locking 33%
• Mode-locked Lasers 33%
• All-fiber 33%
• Fiber-based 33%
• Polarization Controller 33%
• Average Power 33%
• Parameter Space 33%
• Propagation Model 33%
• Spectral Response 33%
• Fiber Propagation 33%
• Nonlinear Schrödinger Equation 33%
• Pulse Parameters 33%
• Lasing 33%
• Operating Regime 33%
• High Energy 33%
• Variation Range 33%
• Laser Output 33%
• Stable Mode 33%
• Rate Equations 33%
• Cavity Dynamics 33%
• Piecewise 33%
• Coupling Ratio 33%
• Gain Saturation 33%
• Power Module 33%
• Fiber Segment 33%
• Adjustable Parameters 33%
• Output Coupling 33%
• Nonlinear Cavity 33%
• Independently Controllable 33%
• Power Dynamics 33%
• Average Signal Power 33%
• Gradient Boosted Trees 33%
• Adjustable Range 33%
• Predictive Regression 33%
• Target Mode 33%
• Live Electronics 33%
• Gain Coefficient 33%
• Electronic Adjusting 33%
• Energy Stable 33%
• High Degree of Freedom 33%
• Boosted Trees Algorithm 33%

Engineering

• Pump Power 100%
• Learning Approach 100%
• Fiber Laser 100%
• Learning System 100%
• Active Fiber 66%
• Machine Learning Technique 33%
• Average Power 33%
• Parameter Space 33%
• Spectral Response 33%
• Propagation Model 33%
• Schr Dinger Equation 33%
• Operating Regime 33%
• Signal Power 33%
• Rate Equation 33%
• Lasing Regime 33%
• Coupling Ratio 33%
• Gain Saturation 33%
• Degree of Freedom 33%
• Polarization Controller 33%
• Fibre Segment 33%
• Gain Coefficient 33%

Material Science

• Fiber Laser 100%