The nonlinear Shannon limit and the need for new fibres

This paper will review the current understanding of the so called nonlinear Shannon limit, and will speculate on methods to approach the limit through new system configurations, and increase the limit using new optical fibres. © 2012 Copyright Society of Photo-Optical Instrumentation Engineers (SPIE).

Challenges of developing non-linear devices to achieve the linear Shannon limit

To achieve the Shannon Capacity Limit, we need to develop practical, effective and deployable non-linear devices to invert the non-linear effects of the transmission line. In this work, we will summarise the progress we are making to realise these, specifically looking at optical phase conjugation and phase regenerators as methods to improve non-linear tolerances. © 2014 IEEE.

Transmission comparison of ultra-long Raman fibre laser based amplification with first and dual order Raman amplification using 10×118 Gbit/s DP-QPSK

Experimental investigations of 10×118 Gbit/s DP-QPSK WDM transmission using three types of distributed Raman amplification techniques are presented. Novel ultra-long Raman fibre laser based amplification with second order counter-propagated pumping is compared with conventional first order and dual order counter-pumped Raman amplification. We demonstrate that URFL based amplification can extend the transmission reach up to a distance of 7520 km in comparison with 5010 km and 6180 km using first order and dual order Raman amplification respectively. © 2014 IEEE.

First order optical differentiator based on an FBG in transmission

Optical differentiators constitute a basic device for analog all-optical signal processing [1]. Fiber grating approaches, both fiber Bragg grating (FBG) and long period grating (LPG), constitute an attractive solution because of their low cost, low insertion losses, and full compatibility with fiber optic systems. A first order differentiator LPG approach was proposed and demonstrated in [2], but FBGs may be preferred in applications with a bandwidth up to few nm because of the extreme sensitivity of LPGs to environmental fluctuations [3]. Several FBG approaches have been proposed in [3-6], requiring one or more additional optical elements to create a first-order differentiator. A very simple, single optical element FBG approach was proposed in [7] for first order differentiation, applying the well-known logarithmic Hilbert transform relation of the amplitude and phase of an FBG in transmission [8]. Using this relationship in the design process, it was theoretically and numerically demonstrated that a single FBG in transmission can be designed to simultaneously approach the amplitude and phase of a first-order differentiator spectral response, without need of any additional elements. © 2013 IEEE.

Second order distributed Raman amplification for quasi-lossless transmission

A novel distributed Raman amplification scheme for quasi-lossless transmission is presented. The scheme is able to keep signal power variations below 3 dB in a 100 km periodic cell and 0.36 dB in 60 km.

High spectral efficiency transmission emulation for non-linear transmission performance estimation for high order modulation formats

We demonstrate a simple method to experimentally evaluate nonlinear transmission performance of high order modulation formats using a low number of channels and channel-like ASE. We verify it's behaviour is consistent with the AWGN model of transmission.

Long-haul transmission performance evaluation of ultra-long Raman fibre laser based amplification influenced by second order co-pumping

A transmission performance investigation using ultra-long Raman fibre laser based amplification with different co-pump power is presented. We attribute Q2 factor degradation to RIN of co-pump and induced fibre laser as well as increased SBS.

The evolution of learning systems:to Bayes or not to be

Bayesian algorithms pose a limit to the performance learning algorithms can achieve. Natural selection should guide the evolution of information processing systems towards those limits. What can we learn from this evolution and what properties do the intermediate stages have? While this question is too general to permit any answer, progress can be made by restricting the class of information processing systems under study. We present analytical and numerical results for the evolution of on-line algorithms for learning from examples for neural network classifiers, which might include or not a hidden layer. The analytical results are obtained by solving a variational problem to determine the learning algorithm that leads to maximum generalization ability. Simulations using evolutionary programming, for programs that implement learning algorithms, confirm and expand the results. The principal result is not just that the evolution is towards a Bayesian limit. Indeed it is essentially reached. In addition we find that evolution is driven by the discovery of useful structures or combinations of variables and operators. In different runs the temporal order of the discovery of such combinations is unique. The main result is that combinations that signal the surprise brought by an example arise always before combinations that serve to gauge the performance of the learning algorithm. This latter structures can be used to implement annealing schedules. The temporal ordering can be understood analytically as well by doing the functional optimization in restricted functional spaces. We also show that there is data suggesting that the appearance of these traits also follows the same temporal ordering in biological systems. © 2006 American Institute of Physics.

Impact of third-order dispersion on the evolution of parabolic pulses

We present a perturbation analysis that describes the effect of third-order dispersion on the similariton pulse solution of the nonlinear Schrödinger equation in a fibre gain medium. The theoretical model predicts with sufficient accuracy the pulse structural changes induced, which are observed through direct numerical simulations.

Foveation time measure in Congenital Nystagmus through second order approximation of the slow phases

Congenital Nystagmus (CN) is an ocular-motor disorder characterised by involuntary, conjugated ocular oscillations, and its pathogenesis is still unknown. The pathology is de fined as "congenital" from the onset time of its arise which could be at birth or in the first months of life. Visual acuity in CN subjects is often diminished due to nystagmus continuous oscillations, mainly on the horizontal plane, which disturb image fixation on the retina. However, during short periods in which eye velocity slows down while the target image is placed onto the fovea (called foveation intervals) the image of a given target can still be stable, allowing a subject to reach a higher visual acuity. In CN subjects, visual acuity is usually assessed both using typical measurement techniques (e.g. Landolt C test) and with eye movement recording in different gaze positions. The offline study of eye movement recordings allows physicians to analyse nystagmus main features such as waveform shape, amplitude and frequency and to compute estimated visual acuity predictors. This analytical functions estimates the best corrected visual acuity using foveation time and foveation position variability, hence a reliable estimation of this two parameters is a fundamental factor in assessing visual acuity. This work aims to enhance the foveation time estimation in CN eye movement recording, computing a second order approximation of the slow phase components of nystag-mus oscillations. About 19 infraredoculographic eye-movement recordings from 10 CN subjects were acquired and the visual acuity assessed with an acuity predictor was compared to the one measured in primary position. Results suggest that visual acuity measurements based on foveation time estimation obtained from interpolated data are closer to value obtained during Landolt C tests. © 2010 IEEE.

Higher-order femtosecond solitons generation in a hybrid mode-locked Tm-doped fibre laser

A thulium-doped all-fibre laser hybrid mode-locked by the co-action of nonlinear polarization evolution and single-walled carbon nanotubes generating 500-fs high-order solitons with the pulse energy 10.87 nJ at 1.9 μm wavelength band is demonstrated. © 2014 OSA.

Superfocusing of high-M2 semiconductor laser beams:experimental demonstration

The focusing of multimode laser diode beams is probably the most significant problem that hinders the expansion of the high-power semiconductor lasers in many spatially-demanding applications. Generally, the 'quality' of laser beams is characterized by so-called 'beam propagation parameter' M2, which is defined as the ratio of the divergence of the laser beam to that of a diffraction-limited counterpart. Therefore, M2 determines the ratio of the beam focal-spot size to that of the 'ideal' Gaussian beam focused by the same optical system. Typically, M2 takes the value of 20-50 for high-power broad-stripe laser diodes thus making the focal-spot 1-2 orders of magnitude larger than the diffraction limit. The idea of 'superfocusing' for high-M2 beams relies on a technique developed for the generation of Bessel beams from laser diodes using a cone-shaped lens (axicon). With traditional focusing of multimode radiation, different curvatures of the wavefronts of the various constituent modes lead to a shift of their focal points along the optical axis that in turn implies larger focal-spot sizes with correspondingly increased values of M2. In contrast, the generation of a Bessel-type beam with an axicon relies on 'self-interference' of each mode thus eliminating the underlying reason for an increase in the focal-spot size. For an experimental demonstration of the proposed technique, we used a fiber-coupled laser diode with M2 below 20 and an emission wavelength in ~1μm range. Utilization of the axicons with apex angle of 140deg, made by direct laser writing on a fiber tip, enabled the demonstration of an order of magnitude decrease of the focal-spot size compared to that achievable using an 'ideal' lens of unity numerical aperture. © 2014 SPIE.

Nonlinear signal transformations:path to capacity above the linear AWGN Shannon limit

We present a methodology for simultaneous optimization of modulation format and regenerative transformations in nonlinear communication channels. We derived analytically the maximum regenerative Shannon capacity, towards which any regenerative channel tends at high SNR and large number of regenerators.

The potential for networks with capacities exceeding the nonlinear-Shannon limit

We examine the network benefits of various forms of nonlinearity compensation, showing that total network capacities that are more than double the capacity of a network with reaches determined by the Nonlinear-Shannon limit © 2015 OSA.

A stable graph-based representation for object recognition through high-order matching

Many Object recognition techniques perform some flavour of point pattern matching between a model and a scene. Such points are usually selected through a feature detection algorithm that is robust to a class of image transformations and a suitable descriptor is computed over them in order to get a reliable matching. Moreover, some approaches take an additional step by casting the correspondence problem into a matching between graphs defined over feature points. The motivation is that the relational model would add more discriminative power, however the overall effectiveness strongly depends on the ability to build a graph that is stable with respect to both changes in the object appearance and spatial distribution of interest points. In fact, widely used graph-based representations, have shown to suffer some limitations, especially with respect to changes in the Euclidean organization of the feature points. In this paper we introduce a technique to build relational structures over corner points that does not depend on the spatial distribution of the features. © 2012 ICPR Org Committee.