Machine learning and applications in ultrafast photonics
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 …
where machine-learning algorithms are being matched to optical systems to add new …
Recent advances on time-stretch dispersive Fourier transform and its applications
The need to measure high repetition rate ultrafast processes cuts across multiple areas of
science. The last decade has seen tremendous advances in the development and …
science. The last decade has seen tremendous advances in the development and …
Recent advances in supercontinuum generation in specialty optical fibers
The physics and applications of fiber-based supercontinuum (SC) sources have been a
subject of intense interest over the last decade, with significant impact on both basic science …
subject of intense interest over the last decade, with significant impact on both basic science …
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 …
Actor neural networks for the robust control of partially measured nonlinear systems showcased for image propagation through diffuse media
The output of physical systems, such as the scrambled pattern formed by shining the spot of
a laser pointer through fog, is often easily accessible by direct measurements. However …
a laser pointer through fog, is often easily accessible by direct measurements. However …
A unified framework for photonic time‐stretch systems
Photonic time stretch is the key enabling technology for a wide variety of instruments with
unparalleled single‐shot data acquisition performance at high throughput and continuous …
unparalleled single‐shot data acquisition performance at high throughput and continuous …
Extreme events prediction from nonlocal partial information in a spatiotemporally chaotic microcavity laser
The forecasting of high-dimensional, spatiotemporal nonlinear systems has made
tremendous progress with the advent of model-free machine learning techniques. However …
tremendous progress with the advent of model-free machine learning techniques. However …
[HTML][HTML] Modelling self-similar parabolic pulses in optical fibres with a neural network
We expand our previous analysis of nonlinear pulse shaping in optical fibres using machine
learning [Opt. Laser Technol., 131 (2020) 106439] to the case of pulse propagation in the …
learning [Opt. Laser Technol., 131 (2020) 106439] to the case of pulse propagation in the …
[HTML][HTML] Optimizing supercontinuum spectro-temporal properties by leveraging machine learning towards multi-photon microscopy
Multi-photon microscopy has played a significant role in biological imaging since it allows to
observe living tissues with improved penetration depth and excellent sectioning effect. Multi …
observe living tissues with improved penetration depth and excellent sectioning effect. Multi …
Feed-forward neural network as nonlinear dynamics integrator for supercontinuum generation
The nonlinear propagation of ultrashort pulses in optical fibers depends sensitively on the
input pulse and fiber parameters. As a result, the optimization of propagation for specific …
input pulse and fiber parameters. As a result, the optimization of propagation for specific …