Related Experiment Video
Updated: Sep 3, 2026

Automation of Mode Locking in a Nonlinear Polarization Rotation Fiber Laser through Output Polarization Measurements
Published on: February 28, 2016
Physics-guided residual Kolmogorov-Arnold network equalizer for high-speed dual-polarization coherent optical
Abstract:
We propose a physics-guided residual Kolmogorov-Arnold network (RN-KAN) equalizer for nonlinear impairment compensation in high-speed dual-polarization (DP) 16-QAM coherent transmission. RN-KAN combines a multiple-input multiple-output finite-impulse-response (MIMO-FIR) backbone with spline-gated residual branches constructed from self-power and cross-polarization interaction features. These branches provide compact representations of self-phase modulation (SPM)- and cross-polarization modulation (XPolM)-related distortions. Experiments over a 60-km standard single-mode fiber (SSMF) link from 119 to 147 GBaud show lower bit-error rates (BERs) than the evaluated third-order Volterra nonlinear equalizer (VNLE), fully connected deep neural network (FC-DNN), and one-dimensional convolutional neural network (1D-CNN) equalizers. With 1,100 trainable parameters and 178.25 real multiplications per recovered bit (RMPB), RN-KAN has the fewest parameters and the lowest multiplication complexity among the evaluated nonlinear equalizers.
Related Concept Videos
Propagation Speed of Electromagnetic Waves
Transmission-Line Differential Equations
Line Section Model
A circuit representing a line section of length Δx helps in understanding the transmission line parameters. The voltage V(x) and current i(x) are measured from the...
Linear Approximation in Frequency Domain
In contrast, nonlinear systems do not inherently possess these properties. However, for small deviations around an operating point, a nonlinear system can often be approximated as linear.
Reconstruction of Signal using Interpolation
Transmission Line Design Considerations
Insensitive Nuclei Enhanced by Polarization Transfer (INEPT)

