Nonlinear Mixing Research Articles

The Improved U-STFM: A Deep Learning-Based Nonlinear Spatial-Temporal Fusion Model for Land Surface Temperature Downscaling

The thermal band of a satellite platform enables the measurement of land surface temperature (LST), which captures the spatial-temporal distribution of energy exchange between the Earth and the atmosphere. LST plays a critical role in simulation models, enhancing our understanding of physical and biochemical processes in nature. However, the limitations in swath width and orbit altitude prevent a single sensor from providing LST data with both high spatial and high temporal resolution. To tackle this challenge, the unmixing-based spatiotemporal fusion model (STFM) offers a promising solution by integrating data from multiple sensors. In these models, the surface reflectance is decomposed from coarse pixels to fine pixels using the linear unmixing function combined with fractional coverage. However, when downsizing LST through STFM, the linear mixing hypothesis fails to adequately represent the nonlinear energy mixing process of LST. Additionally, the original weighting function is sensitive to noise, leading to unreliable predictions of the final LST due to small errors in the unmixing function. To overcome these issues, we selected the U-STFM as the baseline model and introduced an updated version called the nonlinear U-STFM. This new model incorporates two deep learning components: the Dynamic Net (DyNet) and the Chang Ratio Net (RatioNet). The utilization of these components enables easy training with a small dataset while maintaining a high generalization capability over time. The MODIS Terra daytime LST products were employed to downscale from 1000 m to 30 m, in comparison with the Landsat7 LST products. Our results demonstrate that the new model surpasses STARFM, ESTARFM, and the original U-STFM in terms of prediction accuracy and anti-noise capability. To further enhance other STFMs, these two deep-learning components can replace the linear unmixing and weighting functions with minor modifications. As a deep learning-based model, it can be pretrained and deployed for online prediction.

Tension evaluation of prestressed strand based on combined features of nonlinear ultrasonic mixing

The estimation of prestressed strand stress levels is of great significance in ensuring the structurally reasonable performance of post-tensioned concrete structures, cable-stayed bridges, and arch bridges. This paper proposes a method to evaluate the remaining tensile stress on the strand through the ultrasonic mixing technique. The relationship between the strand tension and the nonlinear harmonics is established based on the theory of contact acoustic nonlinearity, and the acoustic nonlinear parameters at different tension levels are investigated by finite element analysis and step-loading experiments. The results show that the nonlinear parameters follow a power-law decrease with the increase in the tensile stress. To overcome the shortage of decreasing sensitivity of theoretical nonlinear parameters in monitoring early loosening, support vector regression is introduced to utilize complex high-order nonlinear generations in stress evaluation. With this approach, the accuracy of early-stage stress evaluation based on wave mixing has been remarkably improved.

Structural optimization of photoacoustic transducer with PDMS/CSNPs nanocomposite for fatigue crack detection using laser-induced nonlinear surface waves

Laser ultrasonics is a promising non-contact inspection technique but faces challenges of low signal-to-noise and low amplitude under non-destructive thermoelastic regime. In this paper, a laser ultrasonic surface acoustic wave (SAW) modulation method and photoacoustic transducer (PAT) are proposed and combined with nonlinear wave mixing technique to inspect microscale fatigue crack. PATs comprised of candle soot nanoparticles and polydimethylsiloxane are systematically optimized and combined with a line-arrayed laser source to generate desired high-amplitude and pure fundamental SAWs. Two modulated SAWs with frequencies of 2.1 and 2.9 MHz are excited on a fatigued aluminum plate to generate nonlinear mixed components, and the ultrasonic responses over the fatigue crack regions are acquired with a scanning laser Doppler vibrometer. The localization of fatigue crack with microscale is eventually achieved by mapping the nonlinear parameter of the mixed components, which proves it a reliable and non-destructive technique to inspect the fatigue crack.

Hyperspectral Blind Unmixing Using a Double Deep Image Prior.

With the rise of machine learning, hyperspectral image (HSI) unmixing problems have been tackled using learning-based methods. However, physically meaningful unmixing results are not guaranteed without proper guidance. In this work, we propose an unsupervised framework inspired by deep image prior (DIP) that can be used for both linear and nonlinear blind unmixing models. The framework consists of three modules: 1) an Endmember estimation module using DIP (EDIP); 2) an Abundance estimation module using DIP (ADIP); and 3) a mixing module (MM). EDIP and ADIP modules generate endmembers and abundances, respectively, while MM produces a reconstruction of the HSI observations based on the postulated unmixing model. We introduce a composite loss function that applies to both linear and nonlinear unmixing models to generate meaningful unmixing results. In addition, we propose an adaptive loss weight strategy for better unmixing results in nonlinear mixing scenarios. The proposed methods outperform state-of-the-art unmixing algorithms in extensive experiments conducted on both synthetic and real datasets.

New hybrid model for nonlinear systems via Takagi-Sugeno fuzzy approach

<p>Mathematical models, especially complex nonlinear systems, are always difficult to analyze and synthesize, and researchers need effective and suitable control methods to address these issues. In the present work, we proposed a hybrid method that combines the well-known Takagi-Sugeno fuzzy model with wavelet decomposition to investigate nonlinear systems characterized by the presence of mixed nonlinearities. Here, one nonlinearity is super-linear and convex, and other is sub-linear, concave, and singular at zero, which leads to difficulties in the analysis, as is known in PDE theory. Linear and polynomial fuzzy models were combined with wavelets to ensure an improvement in both methods for investigating such problems. The results showed a high performance compared with existing methods via error estimates and Lyapunov theory of stability. The model was applied to a prototype nonlinear Schrödinger dynamical system.</p>

Modeling and Simulation of Parametric Nonlinear Focused Ultrasound in Three-Dimensional Bubbly Liquids with Axial Symmetry by a Finite-Element Model

This paper presents the development of a numerical model able to track in time the behavior of nonlinear focused ultrasound when interacting with tiny gas bubbles in a liquid. Our goal here is to analyze the frequency components of the waves by developing a model that can easily be adapted to the geometrical restrictions and complexities that come out in several application frameworks (sonochemistry, medicine, and engineering). We thus model the behavior of nonlinear focused ultrasound propagating in a liquid with gas bubbles by means of the finite-element method in an axisymmetric three-dimensional domain and the generalized-α method in the time domain. The model solves a differential system derived for the nonlinear interaction of acoustic waves and gas bubble oscillations. The high nonlinearity and dispersion of the bubbly medium hugely affect the behavior of the finite-amplitude waves. These characteristics are used here to generate frequency components of the signals that do not exist at the source through nonlinear mixing (parametric antenna). The ability of the model to work with complex geometries, which is the main advantage of the method, is illustrated through the simulation of nonlinear focused ultrasound in a medium excited from two spherical sources in opposite directions.

THz generation by nonlinear mixing of obliquely incident laser beams in the closely-packed assemblage of anharmonic upright CNTs

THz generation by nonlinear mixing of obliquely incident laser beams in the closely-packed assemblage of anharmonic upright CNTs

Amorphous silicon intrinsic photomixing detector for optical ranging

Today’s optical range finders or 3D imagers suffer from significant drawbacks and do not allow to combine performance (sensitivity, precision) with simplicity, and scalability enabling very-large scale integration with minimum footprint. Here, we present the amorphous silicon Intrinsic Photomixing Detector (IPD) for direct and highly sensitive optical envelope mixing. The ability to generate a photocurrent that is proportional to the nonlinear mixing of two optical modulation envelope functions enables high performance Time-of-Flight optical ranging at low light levels down to ~0.1mWcm−2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\sim \\!0.1\\,{{{{{\\rm{mW}}}}}}{{{{{\\rm{cm}}}}}}^{-2}$$\\end{document} at 444nm\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$444\\,{{{{{\\rm{nm}}}}}}$$\\end{document}. The IPD exceeds MHz bandwidth, covers a broad distance detection range from 10cm\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$10\\,{{{{{\\rm{cm}}}}}}$$\\end{document} to 101m\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$101\\,{{{{{\\rm{m}}}}}}$$\\end{document}, and achieves a mean depth resolution below 44mm\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$44\\,{{{{{\\rm{mm}}}}}}$$\\end{document} for distances up to 25m\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$25\\,{{{{{\\rm{m}}}}}}$$\\end{document}. The IPD paves the way towards simple but high-performance photodetectors that allow for very-large scale integration on top of silicon or flexible electronics at low costs with pixel fill factors up to 100%.

Tube-to-tube impact wear damage mechanism and nonlinear ultrasonic detection method of alloy 690 tubes

Tube-to-tube impact wear is one of the prime reasons that cause the failure of alloy 690 tubes in nuclear steam generators. Therefore, it is of great importance to study the tube-to-tube impact wear damage mechanism and damage detection method of alloy 690 tubes. In this paper, the tube-to-tube impact wear experiments are conducted on alloy 690 tubes under different impact loads and cycle numbers. The impact wear damage mechanism of alloy 690 tubes is revealed by analyzing the macro and micro morphologies as well as metallographic structures of the wear scar. A nonlinear ultrasonic wave mixing (NUWM) method is proposed for damage detection of alloy 690 tubes. A detection device is developed to implement the NUWM method. A nonlinear modulation index is used to assess the damage degree of alloy 690 tubes. Experimental results indicate that, for an impact load lower than 100 N and a cycle number smaller than 2 × 105, the tube damage is mainly in forms of the surface plastic deformation and delamination. For a higher impact load or a larger cycle number, the fatigue cracking is the main tube damage mode. With increasing the impact load or cycle number, the tube damage degree increases, leading to an increase of the nonlinear modulation index. Therefore, the NUWM method is effective for detecting and assessing the damage of alloy 690 tubes.

Multiplicity and stability of normalized solutions to non-autonomous Schrödinger equation with mixed non-linearities

AbstractThis paper first studies the multiplicity of normalized solutions to the non-autonomous Schrödinger equation with mixed nonlinearities \begin{equation*} \begin{cases} -\Delta u=\lambda u+h(\epsilon x)|u|^{q-2}u+\eta |u|^{p-2}u,\quad x\in \mathbb{R}^N, \\ \int_{\mathbb{R}^N}|u|^2\,\textrm{d}x=a^2, \end{cases} \end{equation*} where $a, \epsilon, \eta \gt 0$, q is L2-subcritical, p is L2-supercritical, $\lambda\in \mathbb{R}$ is an unknown parameter that appears as a Lagrange multiplier and h is a positive and continuous function. It is proved that the numbers of normalized solutions are at least the numbers of global maximum points of h when ϵ is small enough. The solutions obtained are local minimizers and probably not ground state solutions for the lack of symmetry of the potential h. Secondly, the stability of several different sets consisting of the local minimizers is analysed. Compared with the results of the corresponding autonomous equation, the appearance of the potential h increases the number of the local minimizers and the number of the stable sets. In particular, our results cover the Sobolev critical case $p=2N/(N-2)$.

Adapted poling to break the nonlinear efficiency limit in nanophotonic lithium niobate waveguides.

Nonlinear frequency mixing is a method to extend the wavelength range of optical sources with applications in quantum information and photonic signal processing. Lithium niobate with periodic poling is the most widely used material for frequency mixing due to its strong second-order nonlinear coefficient. The recent development using nanophotonic lithium niobate waveguides promises to improve nonlinear efficiencies by orders of magnitude thanks to subwavelength optical confinement. However, the intrinsic nanoscale inhomogeneity of nanophotonic lithium niobate waveguides limits the coherent interaction length, leading to low nonlinear efficiencies. Here we show improved second-order nonlinear efficiency in nanophotonic lithium niobate waveguides that breaks the limit imposed by nanoscale inhomogeneity. This is realized by developing the adapted poling approach to eliminate the impact of nanoscale inhomogeneity. We realize an overall second-harmonic efficiency of 104% W-1 (without cavity enhancement), approaching the theoretical performance for nanophotonic lithium niobate waveguides. The ideal square dependence of the nonlinear efficiency on the waveguide length is recovered. Phase-matching bandwidths and temperature tuneability are improved through dispersion engineering. We finally demonstrate a conversion ratio from pump to second-harmonic power greater than 80% in a single-pass configuration with pump power as low as 20 mW. Our work therefore breaks the trade-off between the conversion ratio and pump power, offering a potential solution for highly efficient and scalable nonlinear-optical sources, amplifiers and converters.

Peristaltic motion of Jeffrey fluid with nonlinear mixed convection

Since previous few decays the consideration of non-Newtonian liquids motion due to its immense usages in medicine, biology, industrial procedures, chemistry of catalysts and in environment. Various studies examine the significance of bio-materials flow in physiological procedures to explore the cure of diagnosed symptoms of disease appearing during movement in a human physiological system. To illustrate the characteristics of physiological liquids various non-Newtonian models have been proposed, but yet no such single liquid model is exploited which describes all the properties of nonlinear behaving liquids. Among these several non-Newtonian models, Jeffery liquid model should be reduced to its base fluid case (i.e. viscous liquid) by choosing λ₁ = λ₂ = 0. Various physiological materials which represents both linear and nonlinear characteristics respectively blood is one of these. Jeffery fluid and peristaltic motion have some common properties such as radii, relaxation time and retardation time. Moreover heat and mass transfer is also an important phenomenon which is suitable for various physiological processes such as hemodialysis and oxygenation etc. Thus due to such motivating facts this research is conducted to investigate the peristaltic motion of electrically conducting Jeffery liquid. The peristaltic propagating channel walls are asymmetric and inclined. Joule heating and magnetic field effects are considered by applying magnetic field in transverse direction to the flow. Further conservation laws modelled the flow situation via considering quadric mix convection, thermos diffusion and diffusion-thermos, heat generation and absorption, chemical reaction with activation energy features. Moreover, creeping flow and long wavelength assumptions are used to simplify the mathematical modelling. The reduced system of equation is solved numerically through built-in technique in Mathematica software. This built-in technique is working through ND Solve command and shooting and RK-Felburg numerical schemes are behind this technique. These numerical results are used to discuss the flow quantities i.e., velocity, temperature and concentration against the sundry dimensionless quantities. Examining the results it comes to know that both thermal and concentration nonlinear mix convection have oppositely affecting the axial velocity. Both heat and mass transfer are escalating function of thermo-diffusion/diffusion-thermo aspects.

Elliptic problems with mixed nonlinearities and potentials singular at the origin and at the boundary of the domain

We are interested in the following Dirichlet problem: -Δu+λu-μu|x|2-νudist(x,RN\\Ω)2=f(x,u)inΩu=0on∂Ω,\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\begin{aligned} \\left\\{ \\begin{array}{ll} -\\Delta u + \\lambda u - \\mu \\frac{u}{|x|^2} - \ u \\frac{u}{\ extrm{dist}(x,\\mathbb {R}^N \\setminus \\Omega )^2} = f(x,u) &{} \\quad \ ext{ in } \\Omega \\\\ u = 0 &{} \\quad \ ext{ on } \\partial \\Omega , \\end{array} \\right. \\end{aligned}$$\\end{document}on a bounded domain Ω⊂RN\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\Omega \\subset \\mathbb {R}^N$$\\end{document} with 0∈Ω\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$0 \\in \\Omega $$\\end{document}. We assume that the nonlinear part is superlinear on some closed subset K⊂Ω\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$K \\subset \\Omega $$\\end{document} and asymptotically linear on Ω\\K\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\Omega \\setminus K$$\\end{document}. We find a solution with the energy bounded by a certain min–max level, and infinitely, many solutions provided that f is odd in u. Moreover, we study also the multiplicity of solutions to the associated normalized problem.

A Dual Self-Calibrating Framework for Noninvasive Fetal ECG R-Peak Detection

Fetal heart rate (fHR) is critical for assessing fetal health and diagnosing disorders such as fetal distress, congenital heart disease, and intrauterine growth retardation. With the rapid development of the Internet of Medical Things (IoT), fetal R-peak detection plays an important role in diagnosing heart defects during pregnancy. However, due to the nonlinear mixing of multiple sources in the non-invasive signals and the low signal-to-noise ratio (SNR), it is difficult to obtain accurate R-peak detection result. This article presents a dual Self-calibrating system based on a Spectral Attention Kernel Independent Component Analysis (SA-KICA) module and a Selfcalibrating fetal R-peak detection (SC-FRD) module. SA-KICA is an ICA-based calibration module constructed by SA mechanism, which was sought from Short-Time Fourier Transform (STFT) and was shipped back to original signal with convolution to achieve perfect maternal electrocardiogram (MECG) separation in high-dimensional linear separable space. Then a periodic and morphological based Channel Selector is designed to select the optimal MECG. After MECG removal, to further improve the performance of fetal R-peak detection, the SC-FRD module is introduced to utilize the interior peak information and selfcalibrating strategy, which includes variance-based fetal R-peak seed selection, time-varying coarse prediction and adaptive probability mask calibration. The proposed framework is a primary attempt to concurrently introduce the nonlinear feature, spectral information and self-calibrating strategy in the field of fetal ECG processing. The framework achieved excellent performance in fetal R-peak detection accuracy on a simulated dataset and two public datasets with varying divergence and richness of resources. The experimental results show that our framework is superior to existing methods and can be used as a potential fetal monitoring method in the application of Internet of Medical Things. The code is released in https://github.com/bfyjr/NI-FECG-Extraction.

δ13 C and δ18 O heterogeneities in carbonates: Nonlinear mixing in the application of dual-carbonate-clumped isotope thermometer.

Dual-carbonate-clumped isotope thermometry assumes any departure from Δ47 and Δ48 co-equilibrium is due to disequilibrium processes; however, the effects of endmember mixing have not been evaluated for Δ48 . We show that variations in δ13 C and δ18 O values within a sample can lead to offsets in Δ47 and Δ48 that can be mistaken for kinetic fractionation. A numerical mixing model was developed to calculate the Δ48 and Δ47 values of samples with heterogeneous isotope compositions. The model was used to test a variety of possible endmember mixing scenarios and produce a dataset of mixing offsets in both Δ48 and Δ47 . Different mixing patterns arise from endmember mixing, with different patterns between Δ48 and Δ47 . Δ47 can be both positively and negatively offset from equilibrium values by mixing; however, Δ48 can only be offset in a positive direction, producing an underestimate of formation temperature. The overall results suggest that endmember mixing can mimic kinetic fractionation caused by CO2 degassing in dual-clumped isotope measurements. Mixing between endmembers can result in patterns that resemble that of CO2 degassing. However, these effects require a variation of greater than 5‰ in endmember δ18 O values to have a significant effect relative to measurement errors on Δ48 with the detection limits of modern mass spectrometers. Δ47 remains more sensitive to endmember mixing effects and will display measurable mixing effects at 2‰ variation or less in endmember isotopic values.

Demonstration of optically-assisted reconfigurable average of two 20-Gbaud 4-phase-encoded data channels using nonlinear wave mixing.

Networks can play a key role in high-speed and reconfigurable arithmetic computing. However, two performance bottlenecks may arise when: (i) relying solely on electronics to handle computation for multiple data channels at high data rates, and (ii) the data streams input to a processing node (PN) are transmitted as phase-encoded signals over an optical network. We experimentally demonstrate the operation of optically-assisted reconfigurable average of two 4-phase-encoded data channels at 10- and 20-Gbaud rates. Our input signals are two streams of 2-bit numbers representing a binary floating-point format, and the operation results in 7-phase-encoded output signals represented by 3-bit numbers. The average operation is achieved in three stages: (1) phase encoding and division-using an optical modulator to encode the data streams; (2) summation-using a highly nonlinear fiber (HNLF); and (3) multicast-using a periodically poled lithium niobate (PPLN) waveguide to multicast back the result into the original signal wavelengths. The experimental results validate the concept, and the measured penalties indicate that: (i) the error vector magnitudes (EVMs) of optical signals increase at each stage and reach ∼18-21% for the final multicast results, and (ii) compared to the inputs, the optical signal-to-noise ratio (OSNR) penalty of output is ∼6.7 dB for the 10-Gbaud rate and ∼6.9 dB for the 20-Gbaud rate at a bit error rate (BER) of 3.8e-3.

Optimal routing to cerebellum-like structures.

The vast expansion from mossy fibers to cerebellar granule cells (GrC) produces a neural representation that supports functions including associative and internal model learning. This motif is shared by other cerebellum-like structures and has inspired numerous theoretical models. Less attention has been paid to structures immediately presynaptic to GrC layers, whose architecture can be described as a 'bottleneck' and whose function is not understood. We therefore develop a theory of cerebellum-like structures in conjunction with their afferent pathways that predicts the role of the pontine relay to cerebellum and the glomerular organization of the insect antennal lobe. We highlight a new computational distinction between clustered and distributed neuronal representations that is reflected in the anatomy of these two brain structures. Our theory also reconciles recent observations of correlated GrC activity with theories of nonlinear mixing. More generally, it shows that structured compression followed by random expansion is an efficient architecture for flexible computation.

Existence of nontrivial solutions for a class of poly‐Laplacian system with mixed nonlinearity on graphs

We investigate the existence of nontrivial solutions for a class of poly‐Laplacian nonlinear system with mixed nonlinearity term on a locally finite graph or a finite graph. By using the mountain pass theorem, we obtain some sufficient conditions about existence of a nontrivial solution. Our results are different from some known results even for the scalar equation on graph.

Highly Confined Terahertz Surface Plasmons Generation in Graphene-Coated Optical Fiber by Nonlinear Mixing of Two Laser Beams

Highly Confined Terahertz Surface Plasmons Generation in Graphene-Coated Optical Fiber by Nonlinear Mixing of Two Laser Beams

Cascaded four-wave mixing all-optical wavelength converter based on highly nonlinear fiber deposited graphene oxide

The all-optical wavelength conversion using cascaded four-wave mixing (FWM) phenomena with graphene oxide (GO) and a highly nonlinear fiber (HNLF) device is demonstrated experimentally. GO has a strong third-order nonlinear effect and is an excellent nonlinear optical material for nonlinear optical wavelength conversion. The group velocity matching of pump and signal, HNLF, and GO amplification promote the cascaded nonlinear frequency mixing process. From the experimental and analytical results, the maximum spacing between signal and pump is 21 nm, and specifically, the order of cascaded FWM light increases from order 1 to order 2 with increasing GO, and the first-order FWM conversion efficiency increases to a maximum of −14.5 dB. To the best of our knowledge, this is the first time that cascaded FWM-based all-optical wavelength conversion in HNLF–GO with wide wavelength selectivity is investigated with combined pump and signal light. Our findings not only provide an effective method for achieving all-optical wavelength conversion in cascaded FWM but also offer the possibility of fabricating high-performance nonlinear optical devices.