We propose and experimentally demonstrate the programmable photonic radio frequency (RF) filters based on an integrated Fabry–Pérot laser with a saturable absorber (FP-SA). Owing to the high output power and the relative flatness spectrum of the FP-SA laser, only a waveshaper and an erbium-doped fiber amplifier (EDFA) were needed, which can greatly reduce the complexity of the system. The sinc filter employed 87 taps, representing a record-high tap number and resulting in a 3-dB bandwidth of 0.27 GHz and a quality factor of 148. Furthermore, Gaussian apodization enabled the out-of-band rejection of the filter to reach 34 dB and the center frequency to be finely tuned over a wide range, spanning from 4 to 14 GHz. These results indicate that the proposed scheme could provide a promising guideline for the photonic RF filters that demand both high reconfigurability and greatly reduced size and complexity.

The stable long-distance transmission of radio-frequency (RF) signals holds significant importance from various aspects, including the comparison of optical frequency standards, remote monitoring and control, scientific research and experiments, and RF spectrum management. We demonstrate a scheme where an ultrastable frequency signal was transmitted over a 50 km coiled fiber. The optical RF signal is generated using a two-section distributed feedback (DFB) laser for direct modulation based on the reconstruction equivalent chirp (REC) technique. The 3-dB modulation bandwidth of the two-section DFB laser is 18 GHz and the residual phase noise of -122.87dBc/Hz is achieved at 10-Hz offset frequency. We report a short-term stability of 1.62×10-14 at an average time of 1 s and a long-term stability of 6.55×10-18 at the measurement time of 62,000 s when applying current to the front section of the DFB laser. By applying power to both sections, the stability of the system improves to 4.42×10-18 within a testing period of 56,737 s. Despite applying temperature variations to the transmission link, long-term stability of 8.63×10-18 at 23.9 h can still be achieved.

Neuromorphic photonic computing has emerged as a competitive computing paradigm to overcome the bottlenecks of the von-Neumann architecture. Linear weighting and nonlinear spike activation are two fundamental functions of a photonic spiking neural network (PSNN). However, they are separately implemented with different photonic materials and devices, hindering the large-scale integration of PSNN. Here, we propose, fabricate and experimentally demonstrate a photonic neuro-synaptic chip enabling the simultaneous implementation of linear weighting and nonlinear spike activation based on a distributed feedback (DFB) laser with a saturable absorber (DFB-SA). A prototypical system is experimentally constructed to demonstrate the parallel weighted function and nonlinear spike activation. Furthermore, a four-channel DFB-SA laser array is fabricated for realizing matrix convolution of a spiking convolutional neural network, achieving a recognition accuracy of 87% for the MNIST dataset. The fabricated neuro-synaptic chip offers a fundamental building block to construct the large-scale integrated PSNN chip.

提出了一种无波长校正的光纤布拉格光栅（FBG）传感系统，可在未对基于重构等效啁啾（REC）技术制造的扫频DFB激光器进行波长线性校正的情况下，识别波长变化，并解调出光栅传感器的温度变化。所提无波长校正FBG传感系统可以在200 ℃范围内进行精确的温度检测，测得的波长与温度的线性系数1－R²仅为0.004 4。该传感系统光源在1 kHz的锯齿波调制下，调谐范围可达2.5 nm，且测量过程中无需额外波长校正器件。

Spiking neural networks (SNNs) utilize brain-like spatiotemporal spike encoding for simulating brain functions. Photonic SNN offers an ultrahigh speed and power efficiency platform for implementing high-performance neuromorphic computing. Here, we proposed a multi-synaptic photonic SNN, combining the modified remote supervised learning with delay-weight co-training to achieve pattern classification. The impact of multi-synaptic connections and the robustness of the network were investigated through numerical simulations. In addition, the collaborative computing of algorithm and hardware was demonstrated based on a fabricated integrated distributed feedback laser with a saturable absorber (DFB-SA), where 10 different noisy digital patterns were successfully classified. A functional photonic SNN that far exceeds the scale limit of hardware integration was achieved based on time-division multiplexing, demonstrating the capability of hardware-algorithm co-computation.

Modulation bandwidth enhancement in a directly modulated two-section distributed feedback (TS-DFB) laser based on a detuned loading effect is investigated and experimentally demonstrated. The results show that the 3-dB bandwidth of the TS-DFB laser is increased to 17.6 GHz and that chirp parameter can be reduced to 2.24. Compared to the absence of a detuned loading effect, there is a 4.6 GHz increase and a 2.45 reduction, respectively. After transmitting a 10 Gb/s non-return-to-zero (NRZ) signal through a 5-km fiber, the modulation eye diagram still achieves a large opening. Eight-channel laser arrays with precise wavelength spacing are fabricated. Each TS-DFB laser in the array has side mode suppression ratios (SMSR) > 49.093 dB and the maximum wavelength residual < 0.316 nm.

Dendrites, branches of neurons that transmit signals between synapses and soma, play a vital role in spiking information processing, such as nonlinear integration of excitatory and inhibitory stimuli. However, the investigation of nonlinear integration of dendrites in photonic neurons and the fabrication of photonic neurons including dendritic nonlinear integration in photonic spiking neural networks (SNNs) remain open problems. Here, we fabricate and integrate two dendrites and one soma in a single Fabry–Perot laser with an embedded saturable absorber (FP-SA) neuron to achieve nonlinear integration of excitatory and inhibitory stimuli. Note that the two intrinsic electrodes of the gain section and saturable absorber (SA) section in the FP-SA neuron are defined as two dendrites for two ports of stimuli reception, with one electronic dendrite receiving excitatory stimulus and the other receiving inhibitory stimulus. The stimuli received by two electronic dendrites are integrated nonlinearly in a single FP-SA neuron, which generates spikes for photonic SNNs. The properties of frequency encoding and spatiotemporal encoding are investigated experimentally in a single FP-SA neuron with two electronic dendrites. For SNNs equipped with FP-SA neurons, the range of weights between presynaptic neurons and postsynaptic neurons is varied from negative to positive values by biasing the gain and SA sections of FP-SA neurons. Compared with SNN with all-positive weights realized by only biasing the gain section of photonic neurons, the recognition accuracy of Iris flower data is improved numerically in SNN consisting of FP-SA neurons. The results show great potential for multi-functional integrated photonic SNN chips.

We proposed and experimentally demonstrated a simple and novel photonic spiking neuron based on a distributed feedback (DFB) laser chip with an intracavity saturable absorber (SA). The DFB laser with an intracavity SA (DFB-SA) contains a gain region and an SA region. The gain region is designed and fabricated by the asymmetric equivalent π-phase shift based on the reconstruction-equivalent-chirp technique. Under properly injected current in the gain region and reversely biased voltage in the SA region, periodic self-pulsation was experimentally observed due to the Q-switching effect. The self-pulsation frequency increases with the increase of the bias current and is within the range of several gigahertz. When the bias current is below the self-pulsation threshold, neuronlike spiking responses appear when external optical stimulus pulses are injected. Experimental results show that the spike threshold, temporal integration, and refractory period can all be observed in the fabricated DFB-SA chip. To numerically verify the experimental findings, a time-dependent coupled-wave equation model was developed, which described the physics processes inside the gain and SA regions. The numerical results agree well with the experimental measurements. We further experimentally demonstrated that the weighted sum output can readily be encoded into the self-pulsation frequency of the DFB-SA neuron. We also benchmarked the handwritten digit classification task with a simple single-layer fully connected neural network. By using the experimentally measured dependence of the self-pulsation frequency on the bias current in the gain region as an activation function, we can achieve a recognition accuracy of 92.2%, which bridges the gap between the continuous valued artificial neural networks and spike-based neuromorphic networks. To the best of our knowledge, this is the first experimental demonstration of a photonic integrated spiking neuron based on a DFB-SA, which shows great potential to realizing large-scale multiwavelength photonic spiking neural network chips.

In this Letter, we proposed and experimentally demonstrated a directly modulated tunable laser based on the multi-wavelength distributed feedback (DFB) laser array. The lasers are placed in series to avoid the usage of an optical combiner and additional power loss. A three-section design is utilized to reduce the interference from other lasers and improve the electro-optic response bandwidth. Besides, the reconstruction-equivalent-chirp technique is used to simplify the grating fabrication and precisely control the grating phase. We realized 12 channels with 100 GHz spacing with high side mode suppression ratios of above 50 dB. The output power of all the channels is above 14 mW. The 3 dB electro-optic bandwidth is above 20 GHz at a bias current of 100 mA for all four lasers. A 25 Gb/s data transmission over a standard single-mode fiber of up to 10 km is demonstrated for all 12 channels, and 50 Gb/s data per wavelength is obtained through the four-level pulse amplitude modulation. The proposed directly modulated tunable in-series DFB laser array shows the potential for a compact and low-cost light source for wavelength division multiplexing (WDM) systems, such as next-generation front-haul networks and passive optical networks.