The sweep rate of conventional short-cavity lasers with an intracavity-swept filter is limited by the buildup time of laser signals from spontaneous emissions. The Fourier domain mode-locked (FDML) laser was proposed to overcome the limitations of buildup time by inserting a long fiber delay in the cavity to store the whole swept signal and has attracted much interest in both theoretical and experimental studies. In this review, the theoretical models to understand the dynamics of the FDML laser and the experimental techniques to realize high speed, wide sweep range, long coherence length, high output power and highly stable swept signals in FDML lasers will be discussed. We will then discuss the applications of FDML lasers in optical coherence tomography (OCT), fiber sensing, precision measurement, microwave generation and nonlinear microscopy.

Ultrafast nonlinear dynamics plays a crucial role in ultrafast optics, necessitating accurate solutions to the generalized nonlinear Schrödinger equation (GNLSE) for understanding its underlying mathematical mechanisms. However, the GNLSE exhibits intricate physical interactions with highly nonlinear effects, leading to the complexity bottleneck in numerical methods and physical inconsistency in data-driven methods. Physics-informed neural networks (PINNs) can address these challenges by learning prior physical knowledge during the network optimization. However, the pathologies in the structure and learning mode of the vanilla PINN hinders its ability to learn high-nonlinear dynamics and high-frequency features. In this study, an enhanced PINN is proposed for ultrafast nonlinear dynamics in fiber optics, which strictly follows the spatial causality while simultaneously learning all frequency components. The model performance and generalization ability are investigated in two typical ultrafast nonlinear scenarios: higher-order soliton compression and supercontinuum generation, and the generated results exhibit remarkable agreement with reference results. Moreover, we also analyze the computational complexity of numerical methods and physical inconsistency of data-driven methods, and propose potential extensions for more complex scenarios. This work demonstrates the promising potential of the enhanced PINN in comprehending, characterizing, and modeling intricate dynamics with high-nonlinearity and high-frequency.

Bound states in the continuum (BICs) of plasmonic systems offer a powerful method for enhancing light–matter interaction at the nanoscale. The recent emergence of flatband quasi-BICs has alleviated the limitation of the incident angle of the excitation light on generating high-quality-factor (high-Q-factor) resonances, which makes it feasible to produce substantial near-field enhancement by focused light. However, the current works are limited to passive systems with fixed amplitude and Q-factor, hindering the dynamic tunability of light field enhancement. Here, we design a plasmonic metasurface integrated with monolayer graphene to achieve tunable flatband quasi-BICs. Under the illumination of a tightly focused transverse-magnetic wave, our simulations show that adjusting the chemical potential of graphene can increase Q-factor from 52.5 to 75.9 and improve absorption amplitude from 81% to 95%. These results pave the way for dynamically adjustable near-field enhancement with tightly focused light.

Rayleigh scattering-based distributed optical fiber sensors with long sensing distance and large dynamic range are highly desired for application scenarios such as vehicle tracking, structure health monitoring, and geological survey. To enlarge the dynamic range, we propose a coherent optical time domain reflectometry (COTDR) based on double-sideband linear frequency modulation (LFM) pulse. By utilizing I/Q demodulation, both the positive and negative frequency band of the Rayleigh backscattering (RBS) signal can be properly demodulated. Consequently, the dynamic range is doubled without increasing the bandwidth of signal generator, photodetector (PD), and oscilloscope. In the experiment, the chirped pulse with 10 μs pulse width and 498 MHz frequency sweeping range is launched into the sensing fiber. Single-shot strain measurement is achieved over 5 km single-mode fiber with a spatial resolution of 2.5 m and a strain sensitivity of 7.5 pε/Hz. A vibration signal with 3.09 με peak-to-peak amplitude (corresponding to 461 MHz frequency shift) is successfully measured with the double-sideband spectrum, which cannot be properly recovered with the single-sideband spectrum.

Mode converters (MCs) play an essential role in mode‐division multiplexing (MDM) systems. Numerous schemes have been developed on the silicon‐on‐insulator (SOI) platform, yet most of them focus solely on the conversion of fundamental mode to one or two specific higher‐order modes. In this study, we introduce a hybrid shape optimization (HSO) method that combines particle swarm optimization (PSO) with adjoint methods to optimize the shape of the S‐bend waveguide, facilitating the design of arbitrary‐order MCs featuring compactness and high performance. Our approach was validated by designing a series of 13 μm‐long MCs, enabling efficient conversion between various TE modes, ranging from TE ₀ to TE ₃ . These devices can be fabricated in a single lithography step and exhibit robust fabrication tolerances. Experiment results indicate that these converters achieve low insertion losses under 1 dB and crosstalks below −15 dB across bandwidths of 80 nm (TE ₀ –TE ₁ ), 62 nm (TE ₀ –TE ₂ ), 70 nm (TE ₀ –TE ₃ ), 80 nm (TE ₁ –TE ₂ ), 55 nm (TE ₁ –TE ₃ ), and 75 nm (TE ₂ –TE ₃ ). This advancement paves the way for flexible mode conversion, significantly enhancing the versatility of on‐chip MDM technologies.