Artificial neural networks for photonic applications—from algorithms to implementation: tutorial
This tutorial–review on applications of artificial neural networks in photonics targets a broad
audience, ranging from optical research and engineering communities to computer science …
audience, ranging from optical research and engineering communities to computer science …
artificial intelligence-enabled mode-locked fiber laser: A review
Q Ma, H Yu - Nanomanufacturing and Metrology, 2023 - Springer
Owing to their compactness, robustness, low cost, high stability, and diffraction-limited beam
quality, mode-locked fiber lasers play an indispensable role in micro/nanomanufacturing …
quality, mode-locked fiber lasers play an indispensable role in micro/nanomanufacturing …
Realizing a deep reinforcement learning agent for real-time quantum feedback
Realizing the full potential of quantum technologies requires precise real-time control on
time scales much shorter than the coherence time. Model-free reinforcement learning …
time scales much shorter than the coherence time. Model-free reinforcement learning …
Deep reinforcement learning empowers automated inverse design and optimization of photonic crystals for nanoscale laser cavities
Photonics inverse design relies on human experts to search for a design topology that
satisfies certain optical specifications with their experience and intuitions, which is relatively …
satisfies certain optical specifications with their experience and intuitions, which is relatively …
A deep learning method for empirical spectral prediction and inverse design of all-optical nonlinear plasmonic ring resonator switches
All-optical plasmonic switches (AOPSs) utilizing surface plasmon polaritons are well-suited
for integration into photonic integrated circuits (PICs) and play a crucial role in advancing all …
for integration into photonic integrated circuits (PICs) and play a crucial role in advancing all …
Artificial intelligence and machine learning<? TeX\break?> in optics: tutorial
K Yadav, S Bidnyk, A Balakrishnan - Journal of the Optical Society of …, 2024 - opg.optica.org
Across the spectrum of scientific inquiry and practical applications, the emergence of
artificial intelligence (AI) and machine learning (ML) has comprehensively revolutionized …
artificial intelligence (AI) and machine learning (ML) has comprehensively revolutionized …
[HTML][HTML] A review of automation of laser optics alignment with a focus on machine learning applications
I Rakhmatulin, D Risbridger, RM Carter… - Optics and Lasers in …, 2024 - Elsevier
In industrial and laboratory-based laser systems there are complicated processes involved
in the positioning of various optical components and these processes are time consuming …
in the positioning of various optical components and these processes are time consuming …
Automatic mode-locked fiber laser based on adaptive genetic algorithm
D Han, R Guo, G Li, Y Chen, B Zhang, K Ren… - Optical Fiber …, 2024 - Elsevier
A modified adaptive genetic algorithm (GA) is proposed and implemented in a mode-locked
erbium-doped fiber laser (EDFL) based on nonlinear polarization rotation. The algorithm …
erbium-doped fiber laser (EDFL) based on nonlinear polarization rotation. The algorithm …
A deep reinforcement learning algorithm for smart control of hysteresis phenomena in a mode-locked fiber laser
We experimentally demonstrate the application of a double deep Q-learning network
algorithm (DDQN) for design of a self-starting fiber mode-locked laser. In contrast to the …
algorithm (DDQN) for design of a self-starting fiber mode-locked laser. In contrast to the …
Machine learning for self-tuning mode-locked lasers with multiple transmission filters
We develop an adaptive control and self-tuning procedure for mode-locked fiber laser
systems using multiple transmission filters. Each transmission filter set consists of two …
systems using multiple transmission filters. Each transmission filter set consists of two …