Optics express最新文献

In free-space optical communication (FSOC) using wavefront-sensor-less (WFS-less) adaptive optics (AO), stochastic parallel gradient descent (SPGD) is commonly used to mitigate the adverse effects of atmospheric turbulence (AT) and correct the wavefront distortions. However, conventional SPGD often converges slowly and is prone to becoming trapped in local optima, especially under severe phase aberrations. In this study, we propose ViT-SPGD, a novel wavefront-correction method that integrates a vision transformer (ViT) with SPGD, to significantly improve wavefront correction performance. Specifically, the ViT predicts a deterministic, high-confidence gradient direction while SPGD provides stochastic gradient perturbations. By adaptively fusing the two directions, the hybrid update leverages ViT's learned before accelerate convergence while preserving SPGD's stochastic exploration whenever the ViT guidance is uncertain. We first detail the ViT-SPGD design and fusion mechanism, then validate its performance by comparing it with the original SPGD and two established variants, AdamSPGD and NSPGD. Simulation results, including the system-level dynamic simulations, show that ViT-SPGD substantially accelerates convergence and improves robustness in phase distortion correction. By combining deep learning techniques (i.e., ViT), with traditional iterative optimization (i.e., SPGD), ViT-SPGD provides a practical blueprint for intelligent, high-performance AO and helps pave the way for more robust FSOC operation in atmospheric conditions.

We demonstrate the generation of femtosecond pulse trains at 1030 nm with repetition rates tunable from 330 GHz to 1 THz in a fully polarization-maintaining (PM) fiber system. Two detuned single-frequency lasers create a dual-frequency optical beat signal that undergoes strong nonlinear evolution in a PM photonic crystal fiber (PM-PCF) pumped in the anomalous dispersion regime, producing pulses with durations ranging from about 120 fs down to 60 fs without external post-compression. To deliver the required peak power, the dual-frequency signal is carved into 1-ns-long bursts at a repetition rate of 1 MHz. The nonlinear propagation is well described by breather theory. At higher input powers, the breathers evolve into Raman-shifted fundamental solitons, whose self-frequency shift and noise-driven dynamics are confirmed experimentally and numerically. These results highlight the versatility of the dual-pump scheme and the rich nonlinear dynamics of PM-PCFs, establishing a route toward compact sources of tunable, ultra-high-repetition-rate short pulses.

In this manuscript, we propose a new method for cavity- and surface-enhanced Raman spectroscopy (SERS) with improved temporal resolution in the measurement of stochastic Raman spectral fluctuations. Our approach combines Fourier spectroscopy and photon correlation to decouple the integration time from the temporal resolution. Using statistical optics Monte Carlo simulations, we establish the relationship between time resolution and Raman signal strength, revealing that typical Raman spectral fluctuations, commensurate with molecular conformational dynamics, can theoretically be resolved on micro- to millisecond timescales. The method can further extract average single-molecule dynamics from small sub-ensembles, thereby potentially mitigating challenges in achieving strictly single-molecule isolation on SERS substrates.

A high-quality Nd:LuScO₃ crystal was grown using the optical floating zone (OFZ) method. The fundamental spectroscopic properties, including the absorption and emission cross sections, fluorescence lifetimes, and Judd-Ofelt intensity parameters, were systematically analyzed. Under the laser diode pumping, five distinct laser emissions were achieved. For the ⁴F_3/2→⁴I_11/2 transition channel, a maximum output power of 1.37 W with a slope efficiency of 24.9% was obtained, alongside simultaneous emissions at 1079 nm and 1086 nm. Additionally, output powers of 1.28 W and 0.40 W were achieved at 1116 nm and 1144 nm, respectively. Notably, emission at 1144 nm represents, to the best of our knowledge, the longest wavelength reported for the ⁴F_3/2→⁴I_11/2 transition in Nd³⁺-doped materials. For the ⁴F_3/2→⁴I_13/2 channel, continuous-wave output at 1465.6 nm reached 395 mW with 10.1% slope efficiency. These results demonstrate the significant potential of Nd:LuScO₃ for multi-wavelength laser applications.

We present experimental techniques that employ an optical accordion lattice with dynamically tunable spacing to create and study bright matter-wave solitons in optical lattices. The system allows precise control of lattice parameters over a wide range of lattice spacings and depths. We detail calibration methods for the lattice parameters which are adjusted to the varying lattice spacing, and we demonstrate site-resolved atom number preparation via microwave addressing. Lattice solitons are generated through rapid quenches of the atomic interaction strength and the external trapping potential. We systematically optimize the quench parameters, such as duration and final scattering length, to maximize soliton stability. Our results provide insight into nonlinear matter-wave dynamics in discretized systems and establish a versatile platform for the controlled study of lattice solitons.

Dual-comb ranging is a typical absolute-distance measurement method. Noise in ranging systems limits improvements in ranging precision. Timing jitter is a primary noise source, and its relationship with ranging precision remains to be explored. In this study, we established a model to describe this relationship from the perspective of the noise power spectral density (PSD). We propose a corresponding simulation method and analyze the coupling between the timing jitter and intensity noise. Furthermore, we validated this model using dual combs with different noise levels, including the measurement of timing jitter PSD and analysis of ranging precision, which confirms the correctness of our model. The proposed model for timing jitter and ranging precision can help comprehend the mechanism and design dual-comb ranging systems for practical applications.

With growing public awareness of food safety, the high-sensitivity and rapid detection of hazardous substances in food has become increasingly important. Surface-enhanced Raman spectroscopy (SERS) offers significant advantages in food detection due to its high sensitivity and fast response. In this study, gold microflakes (GMFs) and bimetallic Au-Ag alloy nanostars (Au-AgNSts) were synthesized via wet chemical and seed-mediated growth methods, respectively. A liquid-liquid three-phase self-assembly technique was employed to construct a three-dimensional GMFs/Au-AgNSts substrate, where Au-AgNSts were assembled on top of GMFs. By adjusting the Au-to-Ag ratio and the molar quantity of AgNO₃ during nanostar synthesis, the influence of plasmonic "hot spot" distribution among in the Au-AgNSts and GMFs on SERS enhancement was systematically investigated. The results indicate that the optimal SERS enhancement was achieved at a 1:1 Au-to-Ag ratio with 250 μL of AgNO₃ (2 mM). The detection limits for probe molecules Rhodamine 6G (R6G) and crystal violet (CV) as low as 10^-11 M and 10^-10 M, respectively. Additionally, the substrate demonstrated a low detection limit of 0.0313 g/L for aspartame and exhibited excellent stability and uniformity. These findings highlight the substrate's high sensitivity, uniformity, and stability, suggesting its strong potential for applications in food safety monitoring and related fields.

End-to-end computational spectral imaging based on metalens, which enables compact spectral imaging systems by co-optimization of optical encoder and computational decoder, has attracted extensive attention. However, traditional end-to-end spectral imaging systems typically employ pure data-driven convolutional neural networks (CNN) that ignore physical priors of the imaging process and long-range dependencies, limiting high-precision spectral reconstruction. In this paper, we propose and experimentally demonstrate an end-to-end snapshot metalens spectral imaging based on a physics-driven deep unfolding half-shuffle Transformer network. By unfolding the iterative process of traditional optimization algorithms into a cascaded network structure, we not only integrate the advantages of adaptive feature learning neural network and physical model, but also introduce the physical priors of optical-encoder into the network to allow physically-consistent reconstruction process. Besides, a multi-head self-attention mechanism half-shuffle Transformer network is utilized to extract both local and global information. In this way, we achieve stronger generalization and higher reconstruction quality compared with traditional CNN-based reconstruction methods. We designed and fabricated the metalens, achieving high-fidelity spectral image reconstruction across 25 channels (430-670 nm) at a spatial resolution of 512 × 512 with an average peak signal-to-noise ratio (PSNR) of 42.87 dB, while preserving rich spatial details compared with state-of-the-art (SOTA) methods. Our proposed framework facilitates full interaction between the encoder and the decoder, boosting the power of joint optimization in end-to-end design, and paves a way for the design of miniaturized spectral imaging metalenes.

Single-shot electro-optic sampling (EOS) is a powerful method enabling the measurement of weak terahertz signals that would otherwise require prohibitively long acquisition times. This is generally achieved by encoding the EOS time delay into a spatial, angular, or frequency coordinate. In general, angular-encoding techniques operate well up to 3 THz but become more challenging for larger bandwidths, due to dispersion and imaging imperfections. Here, we demonstrate a reliable angular-encoding single-shot EOS implementation that reaches frequencies beyond 6 THz. Diffraction simulations are used to design the experimental setup and adapt this technique to commercial reflection gratings, removing the need for custom-built echelon mirrors. Furthermore, we show that, contrary to earlier reports, group delay dispersion from angular dispersion does not reduce the bandwidth of single-shot EOS.

We propose a reverse optimization reconstruction (ROR) method to achieve pixel-level surface recovery in the four-step shift-rotation absolute testing with both high accuracy and operational simplicity. By employing explicit shift and rotation operations, the proposed method can utilize all potential motion parameters, including the sub-pixel-level shifts, to construct a general surface recovery model. Furthermore, to enhance reconstruction accuracy, an adaptive error correction mechanism for motion parameters is also integrated, rendering the method robust against reconstruction errors caused by inaccuracies in those parameters. Compared with the existing pixel-level method without theoretical error, the proposed approach is flexible and intelligent. The feasibility of the method is experimentally validated in this paper, achieving a surface measurement accuracy of 0.25 nm root-mean-square (RMS).