Machine learning and applications in ultrafast photonics

G Genty, L Salmela, JM Dudley, D Brunner… - Nature …, 2021 - nature.com
Recent years have seen the rapid growth and development of the field of smart photonics,
where machine-learning algorithms are being matched to optical systems to add new …

[HTML][HTML] The past, present and future of photonic glasses: A review in homage to the United Nations International Year of glass 2022

W Blanc, YG Choi, X Zhang, M Nalin… - Progress in Materials …, 2023 - Elsevier
Since the invention and further development of lasers in the 1960s, photonics has grown
into a field that permeates virtually every aspect of modern life. As photonics deals with the …

Deep learning in nano-photonics: inverse design and beyond

PR Wiecha, A Arbouet, C Girard, OL Muskens - Photonics Research, 2021 - opg.optica.org
Deep learning in the context of nano-photonics is mostly discussed in terms of its potential
for inverse design of photonic devices or nano-structures. Many of the recent works on …

Rogue waves and analogies in optics and oceanography

JM Dudley, G Genty, A Mussot, A Chabchoub… - Nature Reviews …, 2019 - nature.com
Over a decade ago, an analogy was drawn between the generation of large ocean waves
and the propagation of light fields in optical fibres. This analogy drove numerous …

[HTML][HTML] Artificial intelligence and machine learning approaches for drug design: challenges and opportunities for the pharmaceutical industries

C Selvaraj, I Chandra, SK Singh - Molecular diversity, 2021 - Springer
The global spread of COVID-19 has raised the importance of pharmaceutical drug
development as intractable and hot research. Developing new drug molecules to overcome …

Intelligent breathing soliton generation in ultrafast fiber lasers

X Wu, J Peng, S Boscolo, Y Zhang… - Laser & Photonics …, 2022 - Wiley Online Library
Harnessing pulse generation from an ultrafast laser is a challenging task as reaching a
specific mode‐locked regime generally involves adjusting multiple control parameters, in …

Theory of neuromorphic computing by waves: machine learning by rogue waves, dispersive shocks, and solitons

G Marcucci, D Pierangeli, C Conti - Physical Review Letters, 2020 - APS
We study artificial neural networks with nonlinear waves as a computing reservoir. We
discuss universality and the conditions to learn a dataset in terms of output channels and …

Predicting ultrafast nonlinear dynamics in fibre optics with a recurrent neural network

L Salmela, N Tsipinakis, A Foi, C Billet… - Nature machine …, 2021 - nature.com
The propagation of ultrashort pulses in optical fibre plays a central role in the development
of light sources and photonic technologies, with applications from fundamental studies of …

[HTML][HTML] A framework for biosensors assisted by multiphoton effects and machine learning

JA Arano-Martinez, CL Martínez-González, MI Salazar… - Biosensors, 2022 - mdpi.com
The ability to interpret information through automatic sensors is one of the most important
pillars of modern technology. In particular, the potential of biosensors has been used to …

Extreme events in dynamical systems and random walkers: A review

SN Chowdhury, A Ray, SK Dana, D Ghosh - Physics Reports, 2022 - Elsevier
Extreme events gain the attention of researchers due to their utmost importance in various
contexts ranging from climate to brain. An observable that deviates significantly from its long …