Related papers: Sensitivity and spectral control of network lasers
Neural networks (NNs) are inherently multidimensional classifiers that learn complex, non-linear relationships among input observables. While their flexibility enables unprecedented performance in high-energy physics (HEP) analyses, it also…
Network synchronization of lasers is critical for reaching high-power levels and for effective optical computing. Yet, the role of network topology for the frequency synchronization of lasers is not well understood. Here, we report our…
The transient-absorption spectrum of a $V$-type three-level system is investigated, when this is periodically excited by a train of equally spaced, $\delta$-like pump pulses as, e.g., from an optical-frequency-comb laser. We show that, even…
We analyze the spectral properties of squeezed light produced by means of pulsed, single-pass degenerate parametric down-conversion. The multimode output of this process can be decomposed into characteristic modes undergoing independent…
Narrowband x- and gamma-ray sources based on the inverse Compton scattering of laser pulses suffer from a limitation of the allowed laser intensity due to the onset of nonlinear effects that increase their bandwidth. It has been suggested…
Nonlinear selective reflection from the interface YAG window-high density rubidium vapor in the high-temperature cell is studied at the transition 5S$_{1/2}$-5P$_{3/2}$. In the experiment tunable pump and probe lasers are used. The…
A theory of resonant Raman scattering spectroscopy of one dimensional electronic systems is developed on the assumptions that (i) the excitations of the one dimensional electronic system are described by the Luttinger Liquid model, (ii)…
Parity-time ($\cal PT$) symmetric lasers have attracted considerable attention lately due to their promising applications and intriguing properties, such as free spectral range doubling and single-mode lasing. In this work we discuss…
Latent space models are frequently used for modeling single-layer networks and include many popular special cases, such as the stochastic block model and the random dot product graph. However, they are not well-developed for more complex…
We analyze experimentally and theoretically the response of a network of spiking nodes to external perturbations. The experimental system consists of an array of semiconductor lasers that are adaptively coupled through an optoelectronic…
Controlling complex light waves to achieve desired behaviours or characteristics on demand presents a significant challenge. This task becomes even more complicated when manipulating speckled light beams owing to their inherently fuzzy…
We study norm-based uniform convergence bounds for neural networks, aiming at a tight understanding of how these are affected by the architecture and type of norm constraint, for the simple class of scalar-valued one-hidden-layer networks,…
We present theoretical study of wavelength dependence of mode instability (MI) in high power fiber lasers, which employs an improved semi-analytical theoretical model. The influence of pump / seed wavelength and photodarkening on threshold…
The recent advent of wave-shaping methods has demonstrated the focusing of light through and inside even the most strongly scattering materials. Typically in wavefront shaping, light is focused in an area with the size of one speckle spot.…
Linewidth-tunable lasers have great application requirements in the fields of high-resolution spectroscopy, optical communications and other industry and scientific research. Here, the switchable plasmonic scattering of the metal particles…
The widespread use of Multi-layer perceptrons (MLPs) often relies on a fixed activation function (e.g., ReLU, Sigmoid, Tanh) for all nodes within the hidden layers. While effective in many scenarios, this uniformity may limit the networks…
Deep unfolding networks have recently emerged as a promising approach for synthetic aperture radar (SAR) imaging. However, baseline unfolding networks, typically derived from iterative reconstruction algorithms such as the alternating…
Optically-coupled semiconductor laser arrays are described by coupled rate equations. The coupled mode equations and carrier densities are included in the analysis, which inherently incorporate the carrier-induced nonlinearities including…
A multi-layer neural network is employed to learn the mapping between Raman gain profile and pump powers and wavelengths. The learned model predicts with high-accuracy, low-latency and low-complexity the pumping setup for any gain profile.
We present a novel procedure for manipulating the near-field of plasmonic nanoantennas using neural network-controlled laser pulse-shaping. As model systems we numerically studied the spatial distribution of the second harmonic response of…