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We demonstrate an optical fiber-based, multiple-access frequency transmission using two optical frequency combs. The experimental results using the Allan deviation analysis show that with the phase compensation technique, the frequency instabilities at the remote site are 8.7 × 10 -15 /1 s and 1.0 × 10 -17 /10 3 s, and at the accessing node along the fiber link, the frequency instabilities are 6.9 × 10 -15 /1 s and 1.1 × 10 -17 /10 3 s. Similarly, the power spectral density of phase noise was analyzed in the frequency domain. These experimental results demonstrate that the compensation scheme improved the performance by two to three orders of magnitude. Thus, the proposed frequency transmission technique has potential application for disseminating ultrastable frequency references in the optical fiber network.

In real-world complex systems, heterogeneous components often interact in complex connection patterns and could be schematized by a formalism of multilayer network. In this work, the synchronization characteristics of multilayer network composed of semiconductor lasers (SLs) are investigated systematically. It is demonstrated that the interplay between different layers plays an important role on the synchronization patterns. We elucidate that the performance of cluster synchronization could be facilitated effectively with the introduction of disjoint layer symmetry into network topology. Intertwined stability of clusters from different layers could be decoupled into independent, and the parameter spaces for stable synchronization are extended significantly. The robustness of our proposed regulation scheme on operation parameters is numerically evaluated. Furthermore, the generality of presented theoretical results is validated in networks with more complex topology and multiple layers.

Fiber nonlinearity compensation (NLC) is likely to become an indispensable component of coherent optical transmission systems for extending the transmission reach and increasing capacity per fiber. In this work, we introduce what we believe to be a novel fast black-box neural network model based on the Fourier neural operator (FNO) to compensate for the chromatic dispersion (CD) and nonlinearity simultaneously. The feasibility of the proposed approach is demonstrated in uniformly distributed as well as probabilistically-shaped 32GBaud 16/32/64-ary quadrature amplitude modulation (16/32/64QAM) polarization-division-multiplexed (PDM) coherent optical communication systems. The experimental results demonstrate that about 0.31 dB Q-factor improvement is achieved compared to traditional digital back-propagation (DBP) with 5 steps per span for PDM-16QAM signals after 1600 km standard single-mode fiber (SSMF) transmission at the optimal launched power of 4 dBm. While, the time consumption is reduced from 6.04 seconds to 1.69 seconds using a central processing unit (CPU), and from 1.54 seconds to only 0.03 seconds using a graphic processing unit (GPU), respectively. This scheme also reveals noticeable generalization ability in terms of launched power and modulation format.

To meet the requirements of time-frequency networks and enable frequency downloadability for nodes along the link, we demonstrated the extraction of stable frequency signals at nodes using a mode-locked laser under the condition of 100 km laboratory fiber. The node consists of a simple structure that utilizes widely used optoelectronic devices and enables plug-and-play applications. In addition, the node can recover frequency signals with multiple frequencies, which are useful for scenarios that require different frequencies. Here, we experimentally demonstrated a short-term frequency instability of 2.83 × 10 -13 @1 s and a long-term frequency instability of 1.18 × 10 -15 @10,000 s at the node, which is similar to that at the remote site of the frequency transfer system. At the same time, frequency signals with different frequencies also achieved stable extraction with the same performance at the node. Our results can support the distributed application under large-scale time-frequency networks.

In this work, an adaptive control scheme based on the optimized AdamSPGD algorithm is proposed to maintain the stable state of polarization (SOP) of the optical signal in a fiber system. The search space can be reduced by half with the guidance of the physical equation of optical intensity that passes through a liner polarizer, leading to an increase in the speed and stability. Moreover, the robustness is guaranteed by the adoption of AdamSPGD as the optimization object. In the experiment, the input optical signals with random SOPs are successfully controlled to a stable output SOP. Compared to the original algorithm, the speed is increased by 44.73%, and the standard deviation of the required number of iterations is reduced by 21.27%.

The nonlinear evolution of ultrashort pulses in optical fiber has broad applications, but the computational burden of convolutional numerical solutions necessitates rapid modeling methods. Here, a lightweight convolutional neural network is designed to characterize nonlinear multi-pulse propagation in highly nonlinear fiber. With the proposed network, we achieve the forward mapping of multi-pulse propagation using the initial multi-pulse temporal profile as well as the inverse mapping of the initial multi-pulse based on the propagated multi-pulse with the coexistence of group velocity dispersion and self-phase modulation. A multi-pulse comprising various Gaussian pulses in 4-level pulse amplitude modulation is utilized to simulate the evolution of a complex random multi-pulse and investigate the prediction precision of two tasks. The results obtained from the unlearned testing sets demonstrate excellent generalization and prediction performance, with a maximum absolute error of 0.026 and 0.01 in the forward and inverse mapping, respectively. The approach provides considerable potential for modeling and predicting the evolution of an arbitrary complex multi-pulse.

By introducing a third measurement comb with different repetition frequencies ( Δ f r e p ), the tri-comb spectroscopy technique overcomes the ambiguity problem of the original dual-comb spectroscopy technique and eliminates physical delay stages in multidimensional coherent spectroscopy. Nowadays, tri-comb generation based on three frequency-stabilized comb lasers is overly complicated and costly for many potential applications. Previous research on single-cavity dual-combs inspired research on single-cavity tri-combs. However, the currently reported tri-comb structures cannot achieve independently controllable pulses. This paper shows a dual-ring tri-comb seed-source structure using wavelength-based multiplexing in one of the rings. The wavelength and power of the output pulse are independently controlled by using the dual-ring structure. The Δ f r e p of wavelength multiplexing-based dual-comb output can be tuned by adjusting the intra-ring polarization controller (PC). In the case of single-wavelength mode-locking, the PC can be adjusted to achieve a wavelength tuning range of nearly 20 nm. The tri-comb source could offer an attractive alternative solution as a low-complexity light source for field-deployable multi-comb metrology applications.

To meet the demand of flexible access for high-precision synchronization frequency, we demonstrate multi-node stable radio frequency (RF) dissemination over a long-distance optical fiber. Stable radio frequency signals can be extracted at any node along the optical fiber, not just at the endpoint. The differential mixing structure (DMS) is employed to avoid the frequency harmonic leakage and enhance the precision. The phase-locked loop (PLL) provides frequency reference for the DMS while improving the signal to noise ratio (SNR) of dissemination signal. We measure the frequency instability of multi-node stable frequency dissemination system (MFDS) at different locations along the 2,000 km optical fiber. The measured short-term instability with average time of 1 s are 1.90 × 10 -14 @ 500 km, 2.81 × 10 -14 @ 1,000 km, 3.46 × 10 -14 @ 1,500 km, and 3.84 × 10 -14 @ 2,000 km respectively. The long-term instability with average time of 10,000 s are basically the same at any position of the optical fiber, which is about (6.24 ± 0.05) × 10 -17 . The resulting instability is sufficient for the propagation of precision active hydrogen masers.

A hybrid aperiodic-coded Brillouin optical correlation domain analysis (HA-coded BOCDA) fiber sensor is proposed to achieve long-range high-spatial-resolution distributed measurement. It is found that high-speed phase modulation in the BOCDA actually forms a special energy transformation mode. This mode can be exploited to suppress all detrimental effects parasitized in a pulse coding-induced cascaded stimulated Brillouin scattering (SBS) process and thereby enable the HA-coding to reach its full potential to improve the BOCDA performance. As a result, under a low system complexity and an enhanced measurement speed, a 72.65-km sensing range and a 5-cm spatial resolution are achieved with a temperature/strain measurement accuracy of 2℃/40 με.

A passive dual-comb laser can generate two optical frequency combs with different repetition frequencies. These repetition differences have high relative stability and mutual coherence through passive common-mode noise suppression without complex tight phase locking from a single-laser cavity. The comb-based frequency distribution requires the dual-comb laser to have a high repetition frequency difference. This paper presents a high repetition frequency difference bidirectional dual-comb fiber laser based on an all-polarization-maintaining cavity configuration and a semiconductor saturable absorption mirror with single polarization output. The proposed comb laser has a standard deviation of 69 Hz and an Allan deviation of 1.17 × 10 -7 at τ = 1 s under different repetition frequencies of 12.815 MHz. Moreover, a transmission experiment has been conducted. Owing to the passive common-mode noise rejection capability of dual-comb laser, after passing an 84 km fiber link, the frequency stability of the repetition frequency difference signal is improved by two orders of magnitude than the repetition frequency signal at the receiver side.

A probabilistic shaping (PS) quadrature amplitude modulation (QAM) based on Y-00 quantum noise stream cipher (QNSC) has been proposed. We experimentally demonstrated this scheme with data rate of 201.6Gbit/s over a 1200-km standard single mode fiber (SSMF) under a 20% SD-FEC threshold. Accounting for the 20% FEC and 6.25% pilot overhead, the achieved net data rate is ∼160Gbit/s. In the proposed scheme, a mathematical cipher (Y-00 protocol) is utilized to convert the original low-order modulation PS-16 (2 2  × 2 2 ) QAM into ultra-dense high-order modulation PS-65536 (2 8  × 2 8 ) QAM. Then, the physical randomness of quantum (shot) noise at photodetection and amplified spontaneous emission (ASE) noise from optical amplifiers are employed to mask the encrypted ultra-dense high-order signal for further improving the security. We further analyze the security performance by two metrics known in the reported QNSC systems, namely the number of masked signals (NMS) of noise and the detection failure probability (DFP). Experimental results show it is difficult or even impossible to extract transmission signals from quantum or ASE noise for an eavesdropper (Eve). We believe that the proposed PS-QAM/QNSC secure transmission scheme has the potential to be compatible with existing high-speed long-distance optical fiber communication systems.

A label-free microfluidic immunosensor based on the double helix microfiber coupler (DHMC) coated with graphene oxide (GO) was proposed for the specific detection of anti-Müllerian hormone (AMH). Two single-mode optical fibers were twisted in a parallel direction, the coning machine was used to fuse and taper them, and the high-sensitivity DHMC was obtained. To make a stable sensing environment, it was immobilized in a microfluidic chip. And then, the DHMC was modified by GO and bio-functionalized by the AMH monoclonal antibodies (anti-AMH MAbs) for the specific detection of AMH. The experimental results showed that the detection range of the immunosensor for AMH antigen solutions was 200 fg/mL∼50 µg/mL, the detection of limit (LOD) was ∼235.15 fg/mL, and the detection sensitivity and the dissociation coefficient were ∼3.518   nm/(log(mg/mL)) and ∼1.85 × 10 - 12 M, respectively. The alpha fetoprotein (AFP), des-carboxy prothrombin (DCP), growth stimulation expressed gene 2 (ST2) and AMH serum were used to confirm the excellent specific and clinical properties of the immunosensor, showing that the proposed immunosensor was easy-made and can be potentially applied in the biosensing field., Competing Interests: The authors declare no financial or commercial conflict of interest., (© 2023 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement.)

The nonlinear parametric process is of great significance for achieving high-quality coherent optical signals and quantum correlated photons. With the development of classical and quantum information processing, the study of the properties of parametric processes is evolving in complex scenarios of multimode, which is limited in conventional nonlinear media due to strict phase matching, e.g. nonlinear crystals. Here we study the dressing-energy-level-cascaded four-wave mixing process to generate multimode optical parametric signals. Via cascading double-Λ type configuration of 85 Rb D 1 line, the non-degenerate energy-level-cascaded FWM is constructed to generate multimode self-parametric amplification. Moreover, with the dressing effects based on atomic coherence, the spatial and frequency multimode characteristics of energy-level-cascaded FWM parametric amplification, i.e., the modes number and pattern, are actively modulated by the pump fields detuning. Also, the spatial modes from the coupling of two coexisting spontaneous parametric FWMs can be controlled to reach tremendous scalability via the atomic coherence and Kerr non-linearity. The atomic coherence effects and unique phase-matching symmetry nature allow flexible modulation of the multimode property of the generated parametric signals within a nonlinear device, which paves a way for multimode classical and quantum information processing.

Assessing the metastatic status of axillary lymph nodes is a common clinical practice in the staging of early breast cancers. Yet sentinel lymph nodes (SLNs) are the regional lymph nodes believed to be the first stop along the lymphatic drainage path of the metastasizing cancer cells. Compared to axillary lymph node dissection, sentinel lymph node biopsy (SLNB) helps reduce morbidity and side effects. Current SLNB methods, however, still have suboptimum properties, such as restrictions due to nuclide accessibility and a relatively low therapeutic efficacy when only a single contrast agent is used. To overcome these limitations, researchers have been motivated to develop a non-radioactive SLN mapping method to replace or supplement radionuclide mapping. We proposed and demonstrated a clinical procedure using a dual-modality photoacoustic (PA)/ultrasound (US) imaging system to locate the SLNs to offer surgical guidance. In our work, the high contrast of PA imaging and its specificity to SLNs were based on the accumulation of carbon nanoparticles (CNPs) in the SLNs. A machine-learning model was also trained and validated to distinguish stained SLNs based on single-wavelength PA images. In the pilot study, we imaged 11 patients in vivo, and the specimens from 13 patients were studied ex vivo. PA/US imaging identified stained SLNs in vivo without a single false positive (23 SLNs), yielding 100% specificity and 52.6% sensitivity based on the current PA imaging system. Our machine-learning model can automatically detect SLNs in real time. In the new procedure, single-wavelength PA/US imaging uses CNPs as the contrast agent. The new system can, with that contrast agent, noninvasively image SLNs with high specificity in real time based on the unique features of the SLNs in the PA images. Ultimately, we aim to use our systems and approach to substitute or supplement nuclide tracers for a non-radioactive, less invasive SLN mapping method in SLNB for the axillary staging of breast cancer., Competing Interests: Regarding activities related to the present article, L.G., H.D., Y.B., X.W., Y.T. J.G., and B.L. have no relevant relationships to disclose. C.M. has a financial interest in TsingPAI Technology Co., Ltd., which provided the data acquisition unit (DAQ) used in this work., (© 2023 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement.)

A millimeter-wave (MMW) joint radar-communication (JRC) system with super-resolution is proposed and experimentally demonstrated, using optical heterodyne upconversion and self-coherent detection downconversion techniques. The point lies in the designed coherent dual-band constant envelope linear frequency modulation-orthogonal frequency division multiplexing (LFM-OFDM) signal with opposite phase modulation indexes for the JRC system. Then the self-coherent detection, as a simple and low-cost means, is accordingly facilitated for both de-chirping of MMW radar and frequency downconversion reception of MMW communication, which circumvents costly high-speed mixers along with MMW local oscillators and, more significantly, achieves the real-time decomposition of radar and communication information. Furthermore, a super-resolution radar range profile is realized through the coherent fusion processing of dual-band JRC signals. In experiments, a dual-band LFM-OFDM JRC signal centered at 54 GHz and 61 GHz is generated. The two bands feature an identical instantaneous bandwidth of 2 GHz and carry an OFDM signal of 1 Gbaud, which helps to achieve a 6-Gbit/s data rate for communication and a 1.76-cm range resolution for radar.

This study proposes a refractive index (RI) sensor using a cascaded tapered thin-core microfiber (TTCMF) based on the Vernier effect. The thin-core fiber was made into a TTCMF by arc discharging and flame heating and then sandwiched between two single-mode fibers (SMFs). The two structures with the same SMF-TTCMF-SMF but slightly different free spectral ranges (FSRs) were cascaded to generate the Vernier effect. The FSR varied with the taper parameters of TTCMF. The RI sensitivities of a single TTCMF sensor, series SMF-TTCMF-SMF sensor, and parallel SMF-TTCMF-SMF sensor were compared and analyzed. Using the Vernier effect in the RI measurement range from 1.3313 to 1.3392, a very high RI sensitivity of -15,053.411 n m / R I U was obtained using the series SMF-TTCMF-SMF structure, and -16,723.243 n m / R I U using the parallel structure, which were basically consistent with the simulation results. Compared with the RI sensitivity of the single TTCMF sensor, the RI sensitivities of series and parallel sensors were increased by 4.65 times and 5.16 times, respectively. In addition, in the temperature range from 35°C to 65°C, temperature sensitivities of -0.196 n m / ∘ C and -0.0489 n m / ∘ C were obtained using series and parallel structures, respectively; the corresponding temperature cross errors were 1.302×10 -5 R I U / ∘ C and 2.92×10 -6 R I U / ∘ C , respectively. Based on the advantages of high RI sensitivity, simple structure, low-temperature cross sensitivity, and convenient fabrication, the proposed sensors have great potential in biosensing fields.

A model construction scheme of chaotic optoelectronic oscillator (OEO) based on the Fourier neural operator (FNO) is proposed. Different from the conventional methods, we learn the nonlinear dynamics of OEO (actual components) in a data-driven way, expecting to obtain a multi-parameter OEO model for generating chaotic carrier with high-efficiency and low-cost. FNO is a deep learning architecture which utilizes neural network as a parameter structure to learn the trajectory of the family of equations from training data. With the assistance of FNO, the nonlinear dynamics of OEO characterized by differential delay equation can be modeled easily. In this work, the maximal Lyapunov exponent is applied to judge whether these time series have chaotic behavior, and the Pearson correlation coefficient (PCC) is introduced to evaluate the modeling performance. Compare with long and short-term memory (LSTM), FNO is not only superior to LSTM in modeling accuracy, but also requires less training data. Subsequently, we analyze the modeling performance of FNO under different feedback gains and time delays. Both numerical and experimental results show that the PCC can be greater than 0.99 in the case of low feedback gain. Next, we further analyze the influence of different system oscillation frequencies, and the generalization ability of FNO is also analyzed.

A highly sensitive optical fiber Mach-Zehnder interference curvature sensor based on MMF-GIMMF-MMF, which was made by sandwiching the graded-index multimode fiber (GIMMF) between two pieces of very short stepped-index multimode fibers (SIMMFs) spliced with input-single-mode fiber (SMF) and output-SMF, respectively, was proposed. The core diameter of the SIMMFs and GIMMF was 105 µm and 50 µm, respectively, and cladding diameter of them were both 125 µm. The sensing principle of the MMF-GIMMF- MMF sensors and the influences of structure parameters on the interference spectrum characteristics were theoretically analyzed in detail. Experimental results showed that when the length of the GIMMF was short enough (usually ≤ 10 mm), interference spectrum was induced by the interaction between the core modes and the low-order cladding modes due to the special structure of the designed Mach-Zehnder interferometer. Intensity of the interference valleys was highly sensitive to the applied bending but nearly independent of the surrounding temperature, on the contrary, the dip wavelength showed negligible sensitivity to the applied bending but relatively high temperature sensitivity. Thus, a temperature- independent curvature sensor could be realized by tracing the intensity variation of interference valley. In addition, different interference valley exhibited different intensity-based curvature sensitivity, providing more options for curvature sensing applications. Especially, total length of the sensor could be as short as 3 mm with length of GIMMF and SIMMFs only 1mm, the maximum curvature sensitivity could reach up to -78.75 dB/m -1 in the small curvature range of 0-2.36 m -1 . Owing to its compact size, easy fabrication, good reproducibility and low cost, the proposed sensor is promising for bending-related high-precision engineering applications.

Cluster synchronization in complex networks with mutually coupled semiconductor lasers (SLs) has recently been extensively studied. However, most of the previous works on cluster synchronization patterns have concentrated on undirected networks. Here, we numerically study the complete cluster synchronization patterns in directed networks composed of SLs, and demonstrate that the values of the SLs parameter and network parameter play a prominent role on the formation and stability of cluster synchronization patterns. Moreover, it is shown that there is a hierarchical dependency between the synchronization stability of different clusters in directed networks. The stability of one cluster can be affected by another cluster, but not vice versa. Without loss of generality, the results are validated in another SLs network with more complex topology.

Cluster synchronization is a state where clusters of nodes inside the network exhibit isochronous synchronization. Here, we present a mechanism to realize the strong cluster synchronization in semiconductor laser (SL) networks with complex topology, where stable cluster synchronization is achieved with decreased correlation between dynamics of different clusters and time delay signature concealment. We elucidate that, with the removal of intra-coupling within clusters, the stability of cluster synchronization could be enhanced effectively, while the statistical correlation among dynamics of each cluster decreases. Moreover, it is demonstrated that the correlation between clusters can be further reduced with the introduction of dual-path injection and frequency detuning. The robustness of strong cluster synchronization on operation parameters is discussed systematically. Time delay signature in chaotic outputs of SL network is concealed simultaneously with heterogeneous inter-coupling among different clusters. Our results suggest a new approach to control the cluster synchronization in complex SL networks and may potentially lead to new network solutions for communication schemes and encryption key distribution.

In phase-sensitive optical time domain reflectometry ( Φ - O T D R ), false phase peaks caused by interference fading have been observed experimentally; however, the statistical law has not yet been disclosed. In this work, after clarifying that the false phase peaks originate from the phase hopping of demodulated phase noise during the unwinding process, we define the phase hopping rate (PHR) to evaluate the degree of fading and study the quantitative relationship between the PHR and signal-to-noise ratio (SNR) of the measured signal through theoretical derivation and experimental verification. In addition, a moving rotated-vector-average (MRVA) method is proposed to suppress the fading and eliminate the false phase peaks. In the experiment, after MRVA processing with a 25 ns sliding window, the lowest SNR is pulled from 0.003 to 14.9, and the corresponding PHR is reduced from 0.237 to less than 0.0001, which is consistent with the theoretical analysis.

A physics-based deep learning (DL) method termed Phynet is proposed for modeling the nonlinear pulse propagation in optical fibers totally independent of the ground truth. The presented Phynet is a combination of a handcrafted neural network and the nonlinear Schrödinger physics model. In particular, Phynet is optimized through physics loss generated by the interaction between the network and the physical model rather than the supervised loss. The inverse pulse propagation problem is leveraged to exemplify the performance of Phynet when in comparison to the typical DL method under the same structure and datasets. The results demonstrate that Phynet is able to precisely restore the initial pulse profiles with varied initial widths and powers, while revealing a similar prediction accuracy compared with the typical DL method. The proposed Phynet method can be expected to break the severe bottleneck of the traditional DL method in terms of relying on abundant labeled data during the training phase, which thus brings new insight for modeling and predicting the nonlinear dynamics of the fibers.

The joint radar and communication (JRC) system providing both large-capacity transmission and high-resolution ranging will play a pivotal role in the next-generation wireless networks (e.g., 6G and beyond) and defense applications. Here, we propose and experimentally demonstrate a novel photonics-assisted millimeter-wave (mm-wave) JRC system with a multi-Gbit/s data rate for communication function and centimeter-level range resolution for radar function. The key is the design of the intermediate-frequency (IF) JRC signal through the angle modulation of the linear frequency modulation (LFM) radar carrier using orthogonal frequency division multiplexing (OFDM) communication signal, inspired by the idea of constant-envelope OFDM (CE-OFDM). This IF angle-modulated waveform facilitates the broadband photonic frequency (phase)-multiplying scheme to generate mm-wave JRC signal with multiplied instantaneous bandwidth and phase modulation index for high-resolution LFM radar and noise-robust CE-OFDM communication. It is with fixed low power-to-average power ratio to render robustness against the nonlinear distortions. In proof-of-concept experiments, a 60-GHz JRC signal with an instantaneous bandwidth over 10-GHz is synthesized through a CE-LFM-OFDM signal encoded with a 2-GBaud 16-QAM OFDM signal. Consequently, a 1.5-cm range resolution of two-dimension imaging and an 8-Gbit/s data rate are achieved for both radar and communication functions, respectively. Furthermore, the proposed JRC system is able to achieve higher radar range resolution and better anti-noise communication, when using higher-order photonic frequency multiplying.

The publisher's note contains a correction to [Opt. Express2932333 (2021)10.1364/OE.438439]. The article was corrected on 17 June 2022.

The cladding mode characteristics simulation of an excessively tilted fiber grating (ExTFG) coated with gold nanoshells was conducted in this study. First, the effective refractive indices of the core and cladding mode before coating were obtained by solving the eigenvalue equation of the three-layer waveguide structure, and the coupling characteristics were briefly analyzed. Then H E 1, m and E H 1, m modes were selected as the research objects, and the spectral characteristics of ExTFG coated with gold nanoshells were simulated by the finite element method. The simulated refractive index sensitivity of H E 1,29 and E H 1,29 modes is 160.16 and 185.03 nm/RIU, respectively. Compared with the non-localized surface plasmon resonance (LSPR) effect, it increased by 10.76 nm/RIU (7.2%) and 19.53 nm/RIU (11.8%), respectively. Thus, the LSPR effect was verified to be beneficial to improve the refractive index sensitivity of ExTFG.

Chaotic optical communication technology is considered as an effective secure communication technology, which can protect information from a physical layer and is compatible with the existing optical networks. At present, to realize long-distance chaos synchronization is still a very difficult problem, mainly because well-matched hardware cannot always be guaranteed between the transmitter and receiver. In this Letter, we introduce long short-term memory (LSTM) networks to learn a nonlinear dynamics model of an opto-electronic feedback loop, and then apply the trained deep learning model to generate a chaotic waveform for encryption and decryption at the transmitter and receiver. Furthermore, to improve the security, we establish a deep learning model pool which consists of different gain trained models and different delay trained models, and use a digital signal to drive chaos synchronization between the receiver and transmitter. The proposed scheme is experimentally verified in chaotic-encrypted 56-Gbit/s PAM-4 systems, and a decrypted performance below 7%FEC threshold (BER = 3.8×10 -3 ) can be achieved over a 100-km fiber transmission.

Conventional Brillouin optical time-domain analyzer (BOTDA) with a frequency-modulated probe (FMP) could avoid non-local effects, while still suffering from the acoustic crosstalk between different frequencies. The induced Brillouin frequency shift (BFS) measurement errors over the whole sensing fiber link reduce system certainty subsequently. A BOTDA scheme with a bidirectional frequency-modulated probe (BFMP) is proposed to overcome such an effect. It utilizes BFMP to generate the crosstalk of the same magnitude and opposite direction to compensate each other. Experimental results indicate that the pulse interval of the coded sequence could be reduced to ∼500 ns to improve the measurement efficiency and BFS estimation errors (∼2.2 MHz) over 117.46-km sensor link are eliminated simultaneously.

An optical frequency comb (OFC)-assisted covert wireless communication system with multiple access and enhanced capacity is proposed and experimentally demonstrated. In the scheme, signals in multiple channels are spread and mixed together to use a single transmitter and then received by individual receivers according to multiple access channels. The mixed signal is highly contaminated by noise to achieve high concealment in both the time and frequency domains, and then effectively recovered as different channels using the OFC assisted analog deep denoising technique. In experiments, mixed signals of 16 access channels with a signal-to-noise ratio (SNR) from -18 to -5 dB are accommodated, showing high covertness and 16× capacity enhancement (16×10 Mbit/s). Mutual interference among different channels is also analyzed and greatly eliminated by phases optimization in the spectral-spreading process. This scheme can greatly improve the time and spectrum utilization efficiency, which will be of great significance for enabling multiple access, large capacity, and high security for wireless communications.

Camera calibration tends to suffer from the low-quality target image acquisition, which would yield inaccurate or inadequate extracted features, resulting in imprecise or even failed parameter estimation. To address this problem, this Letter proposes a novel deep-learning-based adaptive calibration method robust to defocus and noise, which could significantly enhance the image quality and effectively improve the calibration result. Our work provides a convenient multi-quality target dataset generation strategy and introduces a multi-scale deep learning framework that successfully recovers a sharp target image from a deteriorated one. Free from capturing additional patterns or using special calibration targets, the proposed method allows for a more reliable calibration based on the poor-quality acquired images. In this study, an initial training dataset can be easily established containing only 68 images captured by a smartphone. Based on the augmented dataset, the superior performance and flexible transferable ability of the proposed method are validated on another camera in the calibration experiments.

When insufficient samples in the spatial frequency domain could be effectively compensated by the modified CLEAN algorithm, a novel aperture-synthetic scheme of ghost imaging takes advantage of a superior speed of modulation and an enhancement on the spatial resolution. However, there still exist some imperfections in the modified CLEAN reconstructions, such as the fact that some omitted scatter noise still remains or the object contour may be incomplete. Therefore, we optimize the modified CLEAN algorithm by proposing a density clustering algorithm to overcome these drawbacks and improve the visual quality.

As a new, to the best of our knowledge, alternative to the saturated vapor-cell-based Faraday anomalous dispersion optical filter (FADOF), the FADOF based on a hollow cathode lamp (HCL-FADOF) not only enables the FADOF to work normally at room temperature without heating, but also has some new features due to the inherent characteristics of the HCL. In this Letter, we implement an HCL-FADOF operating on the rubidium D2 line and experimentally investigate the effect of ambient temperature on its performance and cold-start characteristics. Results show that the HCL-FADOF can provide excellent stability within a large temperature range, even at temperatures below 0°C. A comparison of the start performance between the HCL-FADOF and FADOF using saturated vapor cells is also provided. This work shows unique features of the HCL-FADOF in a low-temperature environment and its quick-start advantage, which provides a solid foundation for extensive applications.

The past few years have witnessed the great success of artificial metamaterials with effective medium parameters to control electromagnetic waves. Herein, we present a scheme to achieve broadband microwave low specular reflection with uniform backward scattering by using a coding metasurface, which is composed of a rational layout of subwavelength coding elements, via an optimization method. We propose coding elements with high transparency based on ultrathin doped silver, which are capable of generating large phase differences (∼180°) over a wide frequency range by designing geometric structures. The electromagnetic diffusion of the coding metasurface originates from the destructive interference of the reflected waves in various directions. Numerical simulations and experimental results demonstrate that low reflection is achieved from 12 to 18 GHz with a high angular insensitivity of up to ±40° for both transverse electric and transverse magnetic polarizations. Furthermore, the excellent visible transparency of the encoding metasurface is promising for various microwave and optical applications such as electronic surveillance, electromagnetic interference shielding, and radar cross-section reduction.

The measurement accuracy of a Brillouin optical time domain analysis (BOTDA) fiber sensor is determined by the signal-to-noise ratio (SNR) of the received sensing signal. Here, a new hybrid aperiodic coding method is proposed to improve the SNR. In the proposed method, two pre-discovered short seed aperiodic codes (SA-codes) are used to construct a new hybrid aperiodic code (HA-code) in a nested way. The HA-code inherits the good denoising capabilities of the two SA-codes and features a high coding gain. In the proof-of-concept experiment, a SNR improvement up to 8 dB is obtained, which improves the measurement certainty to 1.67 MHz over a 117.46 km sensing range under a spatial resolution of 2.6 m.

In the present work, we introduced a highly sensitive vibration sensor, which is based on the dispersion turning point (DTP) microfiber Mach-Zehnder interferometer. The axial strain and vibration sensing characteristics of the microfiber Mach-Zehnder interferometer were investigated. First, we theoretically analyzed the spectrum evolution characteristics of the microfiber Mach-Zehnder interferometer caused by axial strain. Second, the microfiber with different diameters was fabricated using the electrode discharge and fused taper method, and the axial strain experiments were conducted; the maximum sensitivity of the DTP microfiber with a diameter of ∼2.2 µm reached -45.55 pm/µɛ at ∼1550 nm. Finally, based on the axial strain principle of the microfiber, we designed a highly sensitive vibration sensor using a DTP microfiber integrated into a rectangular through-hole cantilever beam. The 30-3500 Hz vibration signal monitoring could be realized, the maximum signal-to-noise ratio (SNR) was ∼75 dB at 52 Hz, and the acceleration sensitivity reached as high as 0.764 V/g at 45Hz. These results suggested the high performance of the microfiber in axial strain and micro-vibration sensing fields.

Highly reliable wireless train-ground communication immune to the electromagnetic interferences (EMIs) is of critical importance for the security and efficiency of high-speed railways (HSRs). However, the rapid development of HSRs (>52,000 km all over the world) brings great challenges on the conventional EMIs mitigation strategies featuring non-real-time and passive. In this paper, the convergence of radio-over-fiber distributed antenna architecture (RoF-DAA) and reinforcement learning technologies is explored to empower a real-time, cognitive and efficient wireless communication solution for HSRs, with strong immunity to EMIs. A centralized communication system utilizes the RoF-DAA to connect the center station (CS) and distributed remote radio units (RRUs) along with the railway track-sides to collect electromagnetic signals from environments. Real-time recognition of EMIs and interactions between the CS and RRUs are enabled by the RoF link featuring broad bandwidth and low transmission loss. An intelligent proactive interference avoidance scheme is proposed to perform EMI-immunity wireless communication. Then an improved Win or learn Fast-Policy Hill Climbing (WoLF-PHC) multi-agent reinforcement learning algorithm is adopted to dynamically select and switch the operation frequency bands of RRUs in a self-adaptive mode, avoiding the frequency channel contaminated by the EMIs. In proof-of-concept experiments and simulations, EMIs towards a single RRU and multiple RRUs in the same cluster and towards two adjacent RRUs in distinct clusters are effectively avoided for the Global System for Mobile communications-Railway (GSM-R) system in HSRs. The proposed system has a superior performance in terms of circumventing either static or dynamic EMIs, serving as an improved cognitive radio scheme to ensuring high security and high efficiency railway communication.

The erbium-doped-fiber-amplifier (EDFA), generally served as a pre-amplifier, could effectively raise the signal-to-noise ratio (SNR) of a Brillouin optical time-domain analysis (BOTDA) sensor. However, it also induces a distortion in the Brillouin gain spectrum and Brillouin frequency shift measurement errors due to the slow transient effect (STE) in the coded-BOTDA. We propose a distributed depletion mapping (DDM) method to overcome such an effect. A continuous light wave with a particular wavelength is injected to map the STE-induced depletion to compensate for the distortion. The proposed scheme is experimentally demonstrated along a 120-km sensing fiber with 2-m spatial resolution. Experimental results show that the conventional tail-alignment (TA) method cannot compensate for the STE over the whole fiber link, while the proposed DDM method compensates for over 7.69-MHz measurement errors.

Radio-over-fiber (RoF) transmission is a quite reliable technology to support the current and future demands of rapidly progressing broadband wireless network with large capacity and high spectral efficiency. In this paper, we report and demonstrate a digital RoF transmission system using two-dimensional discrete cosine transform with vector quantization (2D-DCT-VQ). By employing the 2D-DCT-VQ technique, the spectral efficiency can be greatly improved, while the system performance is comparable to the traditional approach without compression. The proposed method is experimentally demonstrated in a 20-km 5-Gbaud/λ four-level pulse modulation intensity-modulation/direct-detection optical link. In the orthogonal frequency-division multiplexing -modulated downlink illustrated experimentally, the transmission rate rises by 69.49% on account of the compressed samples by using the proposed method.

Time transfer based on phase modulation schemes has attracted extensive attention in recent years. We propose and experimentally demonstrate an adjustable and stable Michelson interferometer (MI) with a DC phase tracking algorithm for two-way time transfer. Time signal with one pulse per second (1 PPS) is loaded on an optical carrier modulated in phase and demodulated by a Michelson interferometer. The whole compact and cost-effective demodulator is symmetrical with a single coupler to split and recombine optical waves, flexible with one photodetector and a bias tee to separate the DC signal and recovery pulses and stable with a phase modulator to compensate for the drift-phase noise. We show the implementation of modulation and demodulation of the time signal and obtain the stability of 2.31 × 10 -11 at 1000 s averaging time. We then demonstrate two-way time transfer over 1556 km lab fibers. The experimental result shows time interval stability of 1 PPS with 5.62 × 10 -11 at 1000 s averaging time. It has the potential to transfer time signals in long-distance fiber optic links.

We propose a frequency splicing code-based Brillouin optical time domain collider (FSC-BOTDC) for fast dynamic sensing. By delicately designing the frequency splicing code (FSC), multiple collision modes with controllable characteristics are realized for probing multiple target areas with a high sampling rate. Moreover, the sensing system is simpler and more robust than the previous BOTDC. In the experiment, the FSC-BOTDC with 10-time enhanced sampling rate is implemented for single and multiple target areas measurements. Results demonstrate that tailorable measurements can be achieved by the tunable FSC. Furthermore, the FSC-BOTDC is executed to measure periodic mechanical vibrations over 7.9-km sensing range with the sampling rate of 625 Hz.

An optic-fiber vibration sensor based on the reflected 81° tilted fiber grating (81° TFG) integrated with a symmetrical flexible hinge is proposed and experimentally demonstrated in this paper. The vibration sensor is composed of a symmetrical flexible hinge and a reflected 81° TFG, the ends of which are simply fixed on the upper surface of the mass. The theoretical model of the proposed vibration sensor is analyzed, by which the important parameters related to the resonant frequency of the sensor are simulated and discussed; then, the vibration sensing experiments are conducted. Experiment results show that TE/TM mode of the 81° TFG can provide the maximal acceleration sensitivity of 338.28 and 299.94 mV/g at 400 Hz in the flat area of the amplitude-frequency response (50-400 Hz), which is increased by 9.95 and 11.5 times as compared with the optical fiber cantilever beam structure, respectively. Further, the signal-to-noise ratio in the flat area (50-400 Hz) is about ∼66.275 d B under the acceleration of 2 g, which is increased by ∼20 d B . Furthermore, it can be used for detecting mechanical vibration of medium-high frequency ranging from 50 to 3500 Hz. The proposed 81° TFG vibration sensor has the characteristics of small volume, simple package, high acceleration sensitivity, and wide vibration signal response range, which will ensure it has broad application prospects in the field of mechanical vibration.

In this Letter, a chirped-pulse conversion algorithm (CPCA) is proposed to convert a normal probe pulse into an equivalent chirped probe pulse by convolving a chirp factor on the received signal in coherent phase-sensitive optical time-domain reflectometry ( Φ -OTDR). With this algorithm, the Rayleigh interference pattern (RIP) demodulation once applied to chirped-pulse Φ -OTDR can be adopted to quantify the dynamic strain in the traditional coherent Φ -OTDR. Since the equivalent chirped pulse is generated by digital processing, complex and costly chirp modulation is not required. The proposed scheme is capable of fully quantifying perturbations with spatial resolution of 4 m, a sensing range of 8 km, frequency response of 5 kHz, and strain resolution of 56 p ε/√ H z .

Single beam intracavity optical tweezers characterizes a novel optical trapping scheme where the laser operation is nonlinearly coupled to the motion of the trapped particle. Here, we first present and establish a physical model from a completely new perspective to describe this coupling mechanism, using transfer matrices to calculate the loss of the free-space optical path and then extracting the scattering loss that caused by the 3D motions of the particle. Based on this model, we discuss the equilibrium position in the single beam intracavity optical tweezers. The influences of the numerical aperture, pumping power, particle radius and refractive index on the optical confinement efficiency are fully investigated, compared with standard optical tweezers. Our work is highly relevant for guiding the experiments on the single beam intracavity optical tweezers to achieve higher optical confinement efficiency.

When the spatial frequencies of the object are insufficiently sampled, the reconstruction of ghost imaging will suffer from repetitive visual artifacts, which cannot be effectively tackled by existing ghost imaging reconstruction techniques. In this Letter, extensions of the CLEAN algorithm applied in ghost imaging are explored to eliminate those artifacts. Combined with the point spread function estimation using the second-order coherence measurement in ghost imaging, our modified CLEAN algorithm is demonstrated to have a fast and noteworthy improvement against the spatial-frequency insufficiency, even for the extreme sparse sampling cases. A brief explanation of the algorithm and performance analysis are given.

Multimode entanglement is essential for the generation of quantum networks, which plays a central role in quantum information processing and quantum metrology. Here, we study the spatial multimode entanglement characteristics of the large scale quantum states via a dual-pumped four-wave-mixing (FWM) process of Rubidium atomics vapors. A linear mode transform approach is applied to solve the four- and six-mode Gaussian states and the analytical input-output relations are presented. Moreover, via reconstructing the full covariance matrix of the produced states, versatile entanglement with from two up to six modes is analyzed. The results show that most of the 1 versus n-mode and m versus n-mode states are entangled, and the amount of entanglement can be regulated due to the competitions of mode components caused by different interaction strengths of co-existing FWMs. Our study could be applied for any multimode Gaussian states with a quadratic Hamiltonian.