Machine learning and applications in ultrafast photonics

Genty, Goëry; Salmela, Lauri; Dudley, John M.; Brunner, Daniel; Kokhanovskiy, Alexey; Kobtsev, Sergey; Turitsyn, Sergei K.

doi:10.1038/s41566-020-00716-4

Cited by 306 publications

(129 citation statements)

References 103 publications

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“…However, mode-resolved simulations are time-efficient for fewer than 10 modes and a low number of modes may not give an accurate picture of the spatiotemporal nonlinear propagation in a fibre of more than 200 modes. In this regard, the work by Salmela et al 1 enables a faster computation scheme when the neural network is trained 20 .…”

Section: Spatiotemporal Nonlinearities and Simulationsmentioning

confidence: 99%

Reusability report: Predicting spatiotemporal nonlinear dynamics in multimode fibre optics with a recurrent neural network

2021

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Section: Spatiotemporal Nonlinearities and Simulationsmentioning

confidence: 99%

Reusability report: Predicting spatiotemporal nonlinear dynamics in multimode fibre optics with a recurrent neural network

2021

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“…Machine learning algorithms have been already shown to be highly effective in solving optimization problems arising in photonics 23 – 27 . Particular type of the optimization algorithm should be chosen taking into account specific features of the fitness function.…”

Section: Introductionmentioning

confidence: 99%

Inverse design of mode-locked fiber laser by particle swarm optimization algorithm

Kokhanovskiy

Kuprikov

Bednyakova

et al. 2021

Sci Rep

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A wide variety of laser applications, that often require radiation with specific characteristics, and relative flexibility of laser configurations offer a prospect of designing systems with the parameters on demand. The inverse laser design problem is to find the system architecture that provides for the generation of the desired laser output. However, typically, such inverse problems for nonlinear systems are sensitive to the computation of the gradients of a target (fitness) function making direct back propagation approach challenging. We apply here particle swarm optimization algorithm that does not rely on the gradients of the fitness function to the design of a fiber 8-figure laser cavity. This technique allows us to determine the laser cavity architectures tailored to generating on demand pulses with duration in the range of 1.5–105 ps and spectral width in the interval 0.1–20.5 nm. The proposed design optimisation algorithm can be applied to a variety of laser applications, and, more generally, in a range of engineering systems with flexible adjustable configurations and the outputs on demand.

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“…Recently, photonic approaches to decision-making problems have been intensively studied using single photons 12 , 13 , chaotic lasers 14 , 15 , and entangled photons 16 . Related topics are discussed in recent review articles 1 , 17 , 18 .…”

Section: Introductionmentioning

confidence: 99%

Entangled and correlated photon mixed strategy for social decision making

Maeda

Chauvet

Saigo

et al. 2021

Sci Rep

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Collective decision making is important for maximizing total benefits while preserving equality among individuals in the competitive multi-armed bandit (CMAB) problem, wherein multiple players try to gain higher rewards from multiple slot machines. The CMAB problem represents an essential aspect of applications such as resource management in social infrastructure. In a previous study, we theoretically and experimentally demonstrated that entangled photons can physically resolve the difficulty of the CMAB problem. This decision-making strategy completely avoids decision conflicts while ensuring equality. However, decision conflicts can sometimes be beneficial if they yield greater rewards than non-conflicting decisions, indicating that greedy actions may provide positive effects depending on the given environment. In this study, we demonstrate a mixed strategy of entangled- and correlated-photon-based decision-making so that total rewards can be enhanced when compared to the entangled-photon-only decision strategy. We show that an optimal mixture of entangled- and correlated-photon-based strategies exists depending on the dynamics of the reward environment as well as the difficulty of the given problem. This study paves the way for utilizing both quantum and classical aspects of photons in a mixed manner for decision making and provides yet another example of the supremacy of mixed strategies known in game theory, especially in evolutionary game theory.

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Machine learning and applications in ultrafast photonics

Cited by 306 publications

References 103 publications

Reusability report: Predicting spatiotemporal nonlinear dynamics in multimode fibre optics with a recurrent neural network

Reusability report: Predicting spatiotemporal nonlinear dynamics in multimode fibre optics with a recurrent neural network

Inverse design of mode-locked fiber laser by particle swarm optimization algorithm

Entangled and correlated photon mixed strategy for social decision making

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