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Mode Visualization and Control of Complex Lasers Using Neural Networks.

Wai Kit Ng¹, T V Raziman^1,2, Dhruv Saxena¹

¹Blackett Laboratory, Department of Physics, Imperial College London, London SW7 2BW, U.K.

|October 20, 2025

Summary

This summary is machine-generated.

Researchers developed a new spectroscopy method using artificial neural networks to visualize hidden gain profiles in complex laser systems. This technique allows for precise control over laser emission by selectively enhancing targeted modes.

Keywords:

complex laser systems lasing control mode visualization multilayer perceptron quantum dots

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Area of Science:

Photonics
Laser Physics
Artificial Intelligence

Background:

Visualizing complex laser system behavior, especially with nonlinear mode interactions, is challenging.
Hidden features like gain distributions and spatial mode localization are critical for understanding laser action but difficult to measure experimentally.

Purpose of the Study:

To introduce an experimental method for visualizing gain profiles of lasing modes in complex microring array lasers.
To reconstruct spatial gain distributions without prior knowledge of the laser device.
To develop a control mechanism for laser emission based on modal gain/loss profiles.

Main Methods:

Utilized an experimental lasing spectroscopy method.
Employed an artificial neural network (ANN) to reconstruct spatial gain distributions.
Extended the ANN into a tandem neural network for enhanced control.

Main Results:

Successfully visualized gain profiles of modes in a complex, disorderly coupled microring array laser.
Reconstructed spatial gain distributions of lasing modes without prior device knowledge.
Demonstrated selective enhancement of targeted laser modes by matching modal gain/loss profiles.

Conclusions:

The developed method provides a novel approach to extract hidden spatial mode features from photonic structures.
This technique can improve the understanding and control of complex photonic systems, including lasers.
The artificial neural network-based approach offers a powerful tool for analyzing and manipulating laser modes.