Highly nonlinear chalcogenide suspended-core fibers for applications in the mid-infrared

Due to their unique dispersion and nonlinear properties, chalcogenide suspended-core fibers, characterized by a few micrometer-sized core suspended between large air-holes by few small glaß struts, are excellent candidates for mid-infrared applications. In the present study the influence of the main croß-section characteristics of the chalcogenide suspended-core fibers on the dispersion curve and on the position of the zero-dispersion wavelength has been thoroughly analyzed with a full-vector modal solver based on the finite element. In particular, the design of suspended-core fibers made of both As2S3 and As2Se3 has been optimized to obtain dispersion properties suitable for the supercontinuum generation in the mid-infrared.

Eigenvalue communications in nonlinear fiber channels

Continuous progress in optical communication technology and corresponding increasing data rates in core fiber communication systems are stimulated by the evergrowing capacity demand due to constantly emerging new bandwidth-hungry services like cloud computing, ultra-high-definition video streams, etc. This demand is pushing the required capacity of optical communication lines close to the theoretical limit of a standard single-mode fiber, which is imposed by Kerr nonlinearity [1–4]. In recent years, there have been extensive efforts in mitigating the detrimental impact of fiber nonlinearity on signal transmission, through various compensation techniques. However, there are still many challenges in applying these methods, because a majority of technologies utilized in the inherently nonlinear fiber communication systems had been originally developed for linear communication channels. Thereby, the application of ”linear techniques” in a fiber communication systems is inevitably limited by the nonlinear properties of the fiber medium. The quest for the optimal design of a nonlinear transmission channels, development of nonlinear communication technqiues and the usage of nonlinearity in a“constructive” way have occupied researchers for quite a long time.

Nonlinear Fourier transform for optical communications

The nonlinear Fourier transform, also known as eigenvalue communications, is a transmission and signal processing technique that makes positive use of the nonlinear properties of fibre channels. I will discuss recent progress in this field.

Chalcogenide suspended-core fibers for supercontinuum generation in the mid-infrared

Chalcogenide suspended core fibers are a valuable solution to obtain supercontinuum generation of light in the mid-infrared, thanks to glass high transparency, high index contrast, small core diameter and widely-tunable dispersion. In this work the dispersion and nonlinear properties of several chalcogenide suspended core mi-crostructured fibers are numerically evaluated, and the effects of all the structural parameters are investigated. Optimization of the design is carried out to provide a fiber suitable for wide-band supercontinuum generation in the mid-infrared.

Robust control of nonlinear stochastic systems by modelling conditional distributions of control signals

We introduce a novel inversion-based neuro-controller for solving control problems involving uncertain nonlinear systems that could also compensate for multi-valued systems. The approach uses recent developments in neural networks, especially in the context of modelling statistical distributions, which are applied to forward and inverse plant models. Provided that certain conditions are met, an estimate of the intrinsic uncertainty for the outputs of neural networks can be obtained using the statistical properties of networks. More generally, multicomponent distributions can be modelled by the mixture density network. In this work a novel robust inverse control approach is obtained based on importance sampling from these distributions. This importance sampling provides a structured and principled approach to constrain the complexity of the search space for the ideal control law. The performance of the new algorithm is illustrated through simulations with example systems.

Identification of nonlinear systems by correlation using pseudorandom signals

This thesis is concerned with the measurement of the characteristics of nonlinear systems by crosscorrelation, using pseudorandom input signals based on m sequences. The systems are characterised by Volterra series, and analytical expressions relating the rth order Volterra kernel to r-dimensional crosscorrelation measurements are derived. It is shown that the two-dimensional crosscorrelation measurements are related to the corresponding second order kernel values by a set of equations which may be structured into a number of independent subsets. The m sequence properties determine how the maximum order of the subsets for off-diagonal values is related to the upper bound of the arguments for nonzero kernel values. The upper bound of the arguments is used as a performance index, and the performance of antisymmetric pseudorandom binary, ternary and quinary signals is investigated. The performance indices obtained above are small in relation to the periods of the corresponding signals. To achieve higher performance with ternary signals, a method is proposed for combining the estimates of the second order kernel values so that the effects of some of the undesirable nonzero values in the fourth order autocorrelation function of the input signal are removed. The identification of the dynamics of two-input, single-output systems with multiplicative nonlinearity is investigated. It is shown that the characteristics of such a system may be determined by crosscorrelation experiments using phase-shifted versions of a common signal as inputs. The effects of nonlinearities on the estimates of system weighting functions obtained by crosscorrelation are also investigated. Results obtained by correlation testing of an industrial process are presented, and the differences between theoretical and experimental results discussed for this case;

The mammalian MAPK/ERK pathway exhibits properties of a negative feedback amplifier

Three-tiered kinase modules, such as the Raf-MEK (mitogen-activated or extracellular signal-regulated protein kinase kinase)-ERK (extracellular signal-regulated kinase) mitogen-activated protein kinase pathway, are widespread in biology, suggesting that this structure conveys evolutionarily advantageous properties. We show that the three-tiered kinase amplifier module combined with negative feedback recapitulates the design principles of a negative feedback amplifier (NFA), which is used in electronic circuits to confer robustness, output stabilization, and linearization of nonlinear signal amplification. We used mathematical modeling and experimental validation to demonstrate that the ERK pathway has properties of an NFA that (i) converts intrinsic switch-like activation kinetics into graded linear responses, (ii) conveys robustness to changes in rates of reactions within the NFA module, and (iii) stabilizes outputs in response to drug-induced perturbations of the amplifier. These properties determine biological behavior, including activation kinetics and the response to drugs.

Exploiting uncertainty in nonlinear stochastic control problem

This work introduces a novel inversion-based neurocontroller for solving control problems involving uncertain nonlinear systems which could also compensate for multi-valued systems. The approach uses recent developments in neural networks, especially in the context of modelling statistical distributions, which are applied to forward and inverse plant models. Provided that certain conditions are met, an estimate of the intrinsic uncertainty for the outputs of neural networks can be obtained using the statistical properties of networks. More generally, multicomponent distributions can be modelled by the mixture density network. Based on importance sampling from these distributions a novel robust inverse control approach is obtained. This importance sampling provides a structured and principled approach to constrain the complexity of the search space for the ideal control law. The developed methodology circumvents the dynamic programming problem by using the predicted neural network uncertainty to localise the possible control solutions to consider. Convergence of the output error for the proposed control method is verified by using a Lyapunov function. Several simulation examples are provided to demonstrate the efficiency of the developed control method. The manner in which such a method is extended to nonlinear multi-variable systems with different delays between the input-output pairs is considered and demonstrated through simulation examples.

Random input problem for the nonlinear Schrödinger equation

We consider the random input problem for a nonlinear system modeled by the integrable one-dimensional self-focusing nonlinear Schrödinger equation (NLSE). We concentrate on the properties obtained from the direct scattering problem associated with the NLSE. We discuss some general issues regarding soliton creation from random input. We also study the averaged spectral density of random quasilinear waves generated in the NLSE channel for two models of the disordered input field profile. The first model is symmetric complex Gaussian white noise and the second one is a real dichotomous (telegraph) process. For the former model, the closed-form expression for the averaged spectral density is obtained, while for the dichotomous real input we present the small noise perturbative expansion for the same quantity. In the case of the dichotomous input, we also obtain the distribution of minimal pulse width required for a soliton generation. The obtained results can be applied to a multitude of problems including random nonlinear Fraunhoffer diffraction, transmission properties of randomly apodized long period Fiber Bragg gratings, and the propagation of incoherent pulses in optical fibers.

From rogue waves to random walks:nonlinear instabilities in supercontinuum generation

The noise properties of supercontinuum generation continue to be a subject of wide interest within both pure and applied physics. Aside from immediate applications in supercontinuum source development, detailed studies of supercontinuum noise mechanisms have attracted interdisciplinary attention because of links with extreme instabilities in other physical systems, especially the infamous and destructive oceanic rogue waves. But the instabilities inherent in supercontinuum generation can also be interpreted in terms of natural links with the general field of random processes, and this raises new possibilities for applications in areas such as random number generation. In this contribution we will describe recent work where we interpret supercontinuum intensity and phase fluctuations in this way.

Picosecond soliton transmission using concatenated nonlinear optical loop-mirror intensity filters

The issues involved in employing nonlinear optical loop mirrors (NOLMs) as intensity filters in picosecond soliton transmission were examined in detail. It was shown that inserting NOLMs into a periodically amplified transmission line allowed picosecond solitons to be transmitted under conditions considered infeasible until now. The loop mirrors gave dual function, removing low-power background dispersive waves through saturable absorption and applying a negative feedback mechanism to control the amplitude of the solitons. The stochastic characteristics of the pulses that were due to amplifier spontaneous-emission noise were investigated, and a number of new properties were determined. In addition, the mutual interaction between pulses was also significantly different from that observed for longer-duration solitons. The impact of Raman scattering in the computations was included and it was shown that soliton self-frequency shifts may be eliminated by appropriate bandwidth restrictions.

Control of the properties of micro-structured waveguides in LiNbO3 fabricated by direct femtosecond laser inscription

This paper reports on buried waveguides fabricated in lithium niobate (LN) by the method of direct femtosecond (fs) laser inscription. 5% MgO doped LiNbO3 was chosen as the host material because of its high quality and damage threshold, as well as relatively low cost. Direct fs inscription by astigmatically shaped beam in crystals usually produces multiple 'smooth' tracks (with reduced refractive index), which encircle the light guiding 'core', thus creating a depressed cladding WG. A high-repetition rate fs laser system was used for inscription at a depth of approximately 500 μm. Using numerical modelling, it was demonstrated that the properties of fs-written WGs can be controlled by the WG geometry. Buried, depressed-cladding WGs in LN host with circular cross-section were also demonstrated. Combining control over the WG dispersion with quasi-phase matching will allow various ultralow-pump-power, highly-efficient, nonlinear light-guiding devices - all in an integrated optics format.

Dispersion engineering of highly nonlinear chalcogenide suspended-core fibers

Chalcogenide optical fibers are currently undergoing intensive investigation with the aim of exploiting the excellent glass transmission and nonlinear characteristics in the near- and mid-infrared for several applications. Further enhancement of these properties can be obtained, for a particular application, with optical fibers specifically designed that are capable of providing low effective area together with a properly tailored dispersion, matching the characteristics of the laser sources used to excite nonlinear effects. Suspended-core photonic crystal fibers are ideal candidates for nonlinear applications, providing small-core waveguides with large index contrast and tunable dispersion. In this paper, the dispersion properties of As2S3 suspended-core fibers are numerically analyzed, taking into account, for the first time, all the structural parameters, including the size and the number of the glass bridges. The results show that a proper design of the cladding struts can be exploited to significantly change the fiber properties, altering the maximum value of the dispersion parameter and shifting the zero-dispersion wavelengths over a range of 400 nm.

A mixture density network approach to modelling and exploiting uncertainty in nonlinear control problems

In nonlinear and stochastic control problems, learning an efficient feed-forward controller is not amenable to conventional neurocontrol methods. For these approaches, estimating and then incorporating uncertainty in the controller and feed-forward models can produce more robust control results. Here, we introduce a novel inversion-based neurocontroller for solving control problems involving uncertain nonlinear systems which could also compensate for multi-valued systems. The approach uses recent developments in neural networks, especially in the context of modelling statistical distributions, which are applied to forward and inverse plant models. Provided that certain conditions are met, an estimate of the intrinsic uncertainty for the outputs of neural networks can be obtained using the statistical properties of networks. More generally, multicomponent distributions can be modelled by the mixture density network. Based on importance sampling from these distributions a novel robust inverse control approach is obtained. This importance sampling provides a structured and principled approach to constrain the complexity of the search space for the ideal control law. The developed methodology circumvents the dynamic programming problem by using the predicted neural network uncertainty to localise the possible control solutions to consider. A nonlinear multi-variable system with different delays between the input-output pairs is used to demonstrate the successful application of the developed control algorithm. The proposed method is suitable for redundant control systems and allows us to model strongly non-Gaussian distributions of control signal as well as processes with hysteresis. © 2004 Elsevier Ltd. All rights reserved.

Kerr nonlinear switching in a hybrid silicasilicon microspherical resonator

A hybrid silicon-core, silica-clad microspherical resonator has been fabricated from the semiconductor core fiber platform. Linear and nonlinear characterization of the resonator properties have shown it to exhibit advantageous properties associated with both materials, with the low loss cladding supporting high quality (Q) factor whispering gallery modes which can be tuned through the nonlinear response of the crystalline core. By exploiting the large wavelength shift associated with the Kerr nonlinearity, we have demonstrated all-optical modulation of a weak probe on the timescale of the femtosecond pump pulse. This novel geometry offers a route to ultra-low loss, high-Q silica-based resonators with enhanced functionality.