S.k. Turitsyn

Aston University · Aston Institute of Photonic Technologies

We introduce a new approach to reservoir computing based on up-sampling and modulation, utilizing semiconductor optical amplifier and photodetector as nonlinear elements without conventionally used delay loop. We demonstrated the 400-step prediction capability of the proposed scheme for the Mackey-Glass time series test.

A generic novel model governing optical pulse propagation in a nonlinear dispersive amplifying medium with asymmetric (linear spectral slope) gain is introduced. We examine the properties of asymmetric optical pulses formed in such gain-skewed media, both theoretically and numerically. We derive a dissipative optical modification of the classical s...

Primary methods for generating short pulses in lasers require intracavity elements or physical mechanisms for modulation or the saturable absorption of radiation. This often complicates laser design and limits capabilities, particularly beyond single-wavelength operation. We propose and explore a method for the synchronous generation of bicolor, hi...

The anisotropy due to a magnetic field is shown to result in significant changes in Langmuir collapse. Using a variational approach, the quasi-classical collapse phenomenon is investigated analytically. A hierarchy of quasi-classical collapses is determined, along with the structure of a field in the proximity of a stationary singularity that is su...

The anisotropy due to a magnetic field is shown to result in significant changes in Langmuir collapse. Using a variational approach, the quasi-classical collapse phenomenon is investigated analytically. A hierarchy of quasi-classical collapses is determined , along with the structure of a field in the proximity of a stationary singularity that is s...

This chapter documents progress in the extensive area of supercontinuum (SC) generation research devoted to applications in telecommunications, including research into the different mechanisms of spectral broadening and their interplay, SC generation in various media and the most promising SC applications in fibre-based and free-space telecom.Keywo...

We experimentally demonstrate the application of a double deep Q-learning network algorithm (DDQN) for design of a self-starting fiber mode-locked laser. In contrast to the static optimization of a system design, the DDQN reinforcement algorithm is capable of learning the strategy of dynamic adjustment of the cavity parameters. Here, we apply the D...

We examine a possibility to exploit the nonlinear lens effect—the initial stage of self-focusing to localize initially broad field distribution into the small central area where wave collapse is arrested—the nonlinear beam tapering. We describe two-dimensional localized solitary waves (ring solitons) in a physical system that presents a linear medi...

We numerically observe multiple-period pulsation of the solitons parameters in a Mamyshev oscillator. Numerical model of the laser cavity was -based on nonlinear Schrödinger equation. We show that the period of pulsation can be controlled by the distance between the spectral filters. The pulse energy fluctuations ranged from 2 to 47% of the maximum...

Increasing complexity of modern laser systems, mostly originated from the nonlinear dynamics of radiation, makes control of their operation more and more challenging, calling for development of new approaches in laser engineering. Machine learning methods, providing proven tools for identification, control, and data analytics of various complex sys...

In this work, we address the question of the adaptability of artificial neural networks (NNs) used for impairments mitigation in optical transmission systems. We demonstrate that by using well-developed techniques based on the concept of transfer learning, we can efficaciously retrain NN-based equalizers to adapt to the changes in the transmission...

Recovery of optical phases using direct intensity detection methods is an ill-posed problem and some prior information is required to regularize it. In the case of multi-mode fibers, the known structure of eigenmodes is used to recover optical field and find mode decomposition by measuring intensity distribution. Here we demonstrate numerically and...

This paper performs a detailed multi-faceted analysis of the key challenges and common design caveats related to the development of efficient neural networks (NN) nonlinear channel equalizers in coherent optical communication systems. Our study aims to guide researchers and engineers working in this field. We start by clarifying the metrics used to...

Delay differential equation model of a nonlinear optical–nonlinear amplifying loop mirror mode-locked laser is developed that takes into account the finite relaxation rate of the gain medium and asymmetric beam splitting at the entrance of the nonlinear mirror loop. Asymptotic linear stability analysis of the continuous wave solutions performed in...

In this paper, we address the question of which type of predictive modeling, classification, or regression, fits better the task of equalization using neural networks (NN) based post-processing in coherent optical communication, where the transmission channel is nonlinear and dispersive. For the first time, we presented some possible drawbacks in u...

We demonstrate that spectral peak power of negatively chirped optical pulses can acquire a blueshift after amplification by a semiconductor optical amplifier. The central wavelength of a transform limited optical pulse translates over 20 nm towards a shorter wavelength after propagation in a single-mode fiber and semiconductor optical amplifier. A...

Understanding dynamical complexity is one of the most important challenges in science. Significant progress has recently been made in optics through the study of dissipative soliton laser systems, where dynamics are governed by a complex balance between nonlinearity, dispersion, and energy exchange. A particularly complex regime of such systems is...

Addressing the neural network-based optical channel equalizers, we quantify the trade-off between their performance and complexity by carrying out the comparative analysis of several neural network architectures, presenting the results for TWC and SSMF set-ups.

We quantify the achievable reduction of the processing complexity of artificial neural network-based equalizers in a coherent optical channel using the pruning and quantization techniques. First, we explain how to correctly compute the complexity of the compressed equalizer in the DSP sense. Then, considering a basic neural network architecture, a...

We present a novel end-to-end autoencoder-based learning for coherent optical communications using a "parallelizable" perturbative channel model. We jointly optimized constellation shaping and nonlinear pre-emphasis achieving mutual information gain of 0.18 bits/sym./pol. simulating 64 GBd dual-polarization single-channel transmission over 30x80 km...

Active multi‐core fibers represent a powerful platform for coding information via power, phase, frequency, and topological charge, as presented by Petra P. Beličev, Sergei Turitsyn, and co‐workers in article number 2100108. Depending on the gain distribution between the periphery and central core, the system supports multiple functions in applicati...

We present the results of the comparative performance-versus-complexity analysis for the several types of artificial neural networks (NNs) used for nonlinear channel equalization in coherent optical communication systems. The comparison is carried out using an experimental set-up with the transmission dominated by the Kerr nonlinearity and componen...

Delay differential equation model of a NOLM-NALM mode-locked laser is developed that takes into account finite relaxation rate of the gain medium and asymmetric beam splitting at the entrance of the nonlinear mirror loop. Asymptotic linear stability analysis of the continuous wave solutions performed in the limit of large delay indicates that in a...

Topological properties can make light field remarkably robust to various external perturbations. The ability to control and change on demand topological characteristics of light paves the way to new interesting physical phenomena and applications. Here, numerical modelling design of the device based on active multi‐core fiber that can change topolo...

A wide variety of laser applications, that often require radiation with specific characteristics, and relative flexibility of laser configurations offer a prospect of designing systems with the parameters on demand. The inverse laser design problem is to find the system architecture that provides for the generation of the desired laser output. Howe...

We combine the nonlinear Fourier transform (NFT) signal processing with machine learning methods for solving the direct spectral problem associated with the nonlinear Schrödinger equation. The latter is one of the core nonlinear science models emerging in a range of applications. Our focus is on the unexplored problem of computing the continuous no...

We propose a convolutional-recurrent channel equalizer and experimentally demonstrate 1dB Q-factor improvement both in single-channel and 96 x WDM, DP-16QAM transmission over 450km of TWC fiber. The new equalizer outperforms previous NN-based approaches and a 3-steps-per-span DBP.

Transfer learning is proposed to adapt an NN-based nonlinear equalizer across different launch powers and modulation formats using a 450km TWC-fiber transmission. The result shows up to 92% reduction in epochs or 90% in the training dataset.

We propose an efficient neural-network-based equalization jointly compensating fiber and transceiver nonlinearities for high-symbol-rate coherent short-reach links. Providing about 0.9 dB extra SNR gain, it allows achieving experimentally the record single-channel 1.48 Tbps net rate over 240 km G.652 fiber.

We experimentally demonstrate transmission of four 10 Gbit/s NRZ channels in the E-band over 160 km of SMF-28 using a bismuth-doped fibre amplifier with 32 dB maximum gain and 5 dB minimum NF.

In this work, we address the paramount question of generalizability and adaptability of artificial neural networks (NNs) used for impairment mitigation in optical transmission systems. We demonstrate that by using well-developed techniques based on the concept of transfer learning, we can efficaciously retrain NN-based equalizers to adapt to change...

We evaluate improvement in the performance of the optical transmission systems operating with the continuous nonlinear Fourier spectrum by the artificial neural network equalisers installed at the receiver end. We propose here a novel equaliser designs based on bidirectional long short-term memory (BLSTM) gated recurrent neural network and compare...

We present the results of the comparative analysis of the performance versus complexity for several types of artificial neural networks (NNs) used for nonlinear channel equalization in coherent optical communication systems. The comparison has been carried out using an experimental set-up with transmission dominated by the Kerr nonlinearity and com...

The nonlinear Fourier transform (NFT) is used to characterize the optical combs in the Lugiato-Lefever equation with both anomalous and normal dispersion. We demonstrate that the NFT signal processing technique can simplify analysis of the formation of dissipative dark solitons and regimes exploiting modulation instability for a generation of coher...

Practical implementation of digital signal processing for mitigation of transmission impairments in optical communication systems requires reduction of the complexity of the underlying algorithms. Here, we investigate the application of convolutional neural networks for compensating nonlinear signal distortions in a 3200~km fiber-optic 11x400-Gb/s...

We propose a convolutional-recurrent channel equalizer and experiment tally demonstrate 1dB Q-factor improvement both in single-channel and 96×WDM, DP- 16QAM transmission over 450km of TWC fiber. The new equalizer outperforms previous NN-based approaches and a 3-steps-per-span DBP.

We experimentally demonstrate transmission of four 10 Gbit/s NRZ channels in the E-band over 160 km of SMF-28 using a bismuth-doped fibre amplifier with 32 dB maximum gain and 5 dB minimum NF.

We demonstrated both through numerical modeling and experimentally that optical pulses with appropriate initial chirp can undergo a nonlinear spectral blueshift, opposite to the Raman-induced redshift, when they are amplified by the SOA.

We numerically investigate E-band quality of the transmission using an experimentally characterized bismuth-doped fiber amplifier, demonstrating its impact on de-ployed C+L systems.

Bismuth-doped fibre amplifiers offer an attractive solution for expanding the bandwidth of fibre-optic telecommunication systems beyond the current C-band (1530-1565 nm). We report a bismuth-doped fibre amplifier in the spectral range from 1370 to 1490 nm, with a maximum gain exceeding 31 dB, and a noise figure as low as 4.75 dB. The developed syst...

Nonlinearity compensation is considered as a key enabler to increase channel transmission rates in the installed optical communication systems. Recently, data-driven approaches — motivated by modern machine learning techniques — have been proposed for optical communications in place of traditional model-based counterparts. In particular, the applic...

Retrieval of the optical phase information from measurement of intensity is of a high interestbecause this would facilitate simple and cost-efficient techniques and devices. In scientificand industrial applications that exploit multi-modefibers, a prior knowledge of spatial modestructure of thefiber, in principle, makes it possible to recover phase...

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 functionalities and to enhance performance. An area where machine learning shows particular potential to accelerate technology is the field of ultrafast photonics — the generation...

Optical communication systems, operating in C-band, are reaching their theoretically achievable capacity limits. An attractive and economically viable solution to satisfy the future data rate demands is to employ the transmission across the full low-loss spectrum encompassing O, E, S, C and L band of the single mode fibers (SMF). Utilizing all five...

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

We experimentally demonstrate the generation of soliton-like pulses with 195–230 fs duration and energy up to 20 nJ in the spectral region of 1.9–2.5 µ m directly from the Tm-doped all-fiber MOPA laser. The emerged Raman solitons generated directly in the fiber amplifier exhibit unusual dynamics and spectral properties forming a supercontinuum with...

We introduce a new, to the best of our knowledge, type of band-limited optical pulse—soliton-sinc tailored to the nonlinear Schrödinger (NLS) equation. The idea behind the soliton-sinc pulse is to combine, even if approximately, a property of a fundamental soliton to propagate without distortions in nonlinear systems governed by the NLS equation wi...

Control of the properties of speckle patterns produced by mutual interference of light waves is important for various applications of multimode optical fibers. It has been shown previously that a high signal-to-noise ratio in a multimode fiber can be achieved by preferential excitation of lower order spatial eigenmodes in optical fiber communicatio...

We propose a method to improve the performance of the nonlinear Fourier transform (NFT)-based optical transmission system by applying the neural network post-processing of the nonlinear spectrum at the receiver. We demonstrate through numerical modeling about one order of magnitude bit error rate improvement and compare this method with machine lea...

Optical communication systems, operating in C-band, are reaching their theoretically achievable capacity limits. An attractive and economically viable solution to satisfy the future data rate demands is to employ the transmission across the full low-loss spectrum encompassing O, E, S, C and L band of the single mode fibers (SMF). Utilizing all five...

We propose and demonstrate, in the framework of the generic mean-field model, the application of the nonlinear Fourier transform (NFT) signal processing based on the Zakharov–Shabat spectral problem to the characterization of the round trip scale dynamics of radiation in optical fiber- and microresonators.

In this work, for the first time, a full-spectrum periodic nonlinear Fourier transform (NFT) based communication system with the inverse transformation at the transmitter performed by using the solution of Riemann-Hilbert problem (RHP), is proposed and studied. The entire control over the nonlinear spectrum rendered by our technique, where we opera...

In hydrodynamics, vortex generation upon the transition from smooth laminar flows to turbulence is generally accompanied by increased dissipation. However, vortices in the plane can provide transport barriers and decrease losses, as it happens in numerous geophysical, astrophysical flows and in tokamaks. Photon interactions with matter can affect l...

We propose a modification of the conventional perturbation-based approach of fiber nonlinearity compensation that enables straight-forward implementation at the receiver and meets feasible complexity requirements. We have developed a model based on perturbation analysis of an inverse Manakov problem, where we use the received signal as the initial...