Microcombs have enabled a host of cutting-edge applications from metrology to communications that have garnered significant attention in the last decade. Nevertheless, due to the thermal instability of the microresonator, additional control devices like auxiliary lasers are indispensable for single-soliton generation in some scenarios. Specifically, the increased system complexity would be too overwhelming for dual-microcomb generation. Here, we put forward a novel approach to mitigate the thermal instability and generate the dual-microcomb using a compact system. This process is akin to mode-division multiplexing, as the dual-microcombs are generated by pumping the dual-mode of a single Si3N4 microresonator with a continuous-wave laser. Both numerical simulations and experimental measurements indicate that this innovative technique could offer a straightforward way to enlarge the soliton existence range, allowing entry into the multistability regime and triggering another microcomb alongside the main soliton pulse. This outcome not only shines new light on the interaction mechanism of microresonator modes but also provides an avenue for the development of dual-microcomb-based ranging and low phase noise microwave generation.

An adaptive microwave photonic angle-of-arrival (AOA) estimation approach based on a convolutional neural network with a bidirectional gated recurrent unit (BiGRU-CNN) is proposed and demonstrated. Compared with the previously reported AOA estimation methods based on phase-to-power mapping, the proposed method is unnecessary to know the frequency of the signal under test (SUT) in advance. The envelope voltage correlation matrix is obtained from dual-drive Mach–Zehnder modulator (N-DDMZM, N > 2) optical interferometer arrays first, and then AOA estimations are performed on different frequency signals with the aid of BiGRU-CNN. A three-DDMZM-based experiment is carried out to assess the estimation performance of microwave signals at three different frequencies, and the mean absolute error is only 0.1545°.

Recently, the metasurfaces for independently controlling the wavefront and amplitude of two orthogonal circularly polarized electromagnetic (EM) waves have been demonstrated to open a way toward spin-multiplexing compact metadevices. However, these metasurfaces are mostly restricted to a single operation frequency band. The main challenge to achieving multiple frequency manipulations stems from the complicated and time-consuming design caused by multifrequency cross talk. To solve this problem, we propose a deep-learning-assisted inverse design method for designing a dual-spin/frequency metasurface with flexible multiplexing of off-axis vortices. By analyzing the cross talk between different spin/frequency channels based on the deep-learning method, we established the internal mapping relationship between the physical parameters of a meta-atom and its phase responses in multichannels, realizing the rapid inverse design of the spin/frequency multiplexing EM device. As a proof of concept, we demonstrated in the microwave region a dual-frequency arbitrary spin-to-orbit angular momentum converter, a dual-frequency off-axis vector vortex multiplexer, and a large-capacity (16-channel) vortex beam generator. The proposed method may provide a compact and efficient platform for the multiplexing of vortices, which may further stimulate their applications in wireless communication and quantum information science.

Dissipative Kerr solitons (DKSs) with mode-locked pulse trains in high-Q optical microresonators possess low-noise and broadband parallelized comb lines, having already found plentiful cutting-edge applications. However, thermal bistability and thermal noise caused by the high microresonator power and large temperature exchange between microresonator and the environment would prevent soliton microcomb formation and deteriorate the phase and frequency noise. Here, a novel method that combines rapid frequency sweep with optical sideband thermal compensation is presented, providing a simple and reliable way to get into the single-soliton state. Meanwhile, it is shown that the phase and frequency noises of the generated soliton are greatly reduced. Moreover, by closing the locking loop, an in-loop repetition rate fractional instability of 5.5×10-15 at 1 s integration time and a triangular linear repetition rate sweep with 2.5 MHz could be realized. This demonstration provides a means for the generation, locking, and tuning of a soliton microcomb, paving the way for the application of single-soliton microcombs in low-phase-noise microwave generation and laser ranging.

We present a theoretical analysis of a novel multi-channel light amplification photonic system on chip, where the nonlinear Raman amplification phenomenon in the silicon (Si) wire waveguide is considered. Particularly, a compact and temperature insensitive Mach–Zehnder interferometer filter working as demultiplexer is also exploited, allowing for the whole Si photonic system to be free from thermal interference. The propagation of the multi-channel pump and Stokes lights is described by a rigorous theoretical model that incorporates all relevant linear and nonlinear optical effects, including the intrinsic waveguide optical losses, first- and second-order frequency dispersion, self-phase and cross-phase modulation, phase shift and two-photon absorption, free-carriers dynamics, as well as the inter-pulse Raman interaction. Notably, to prevent excessive drift of the transmission window of the demultiplexer caused by ambient temperature variations and high thermo-optical coefficient of Si, an asymmetric waveguide width is adopted in the upper and lower arms of each Mach–Zehnder interferometer lattice cell. A Chebyshev half-band filter is utilized to achieve a flat pass-band transmission, achieving a temperature sensitivity of <1.4pm/K and over 100 K temperature span. This all-Si amplifier shows a thermally robust behavior, which is desired by future Si-on-insulator (SOI) applications.

The application of machine learning to the field of ultrafast photonics is becoming more and more extensive. In this paper, for the automatic mode-locked operation in a saturable absorber-based ultrafast fiber laser (UFL), a deep-reinforcement learning algorithm with low latency is proposed and implemented. The algorithm contains two actor neural networks providing strategies to modify the intracavity lasing polarization state and two critic neural networks evaluating the effect of the actor networks. With this algorithm, a stable fundamental mode-locked (FML) state of the UFL is demonstrated. To guarantee its effectiveness and robustness, two experiments are put forward. As for effectiveness, one experiment verifies the performance of the trained network model by applying it to recover the mode-locked state with environmental vibrations, which mimics the condition that the UFL loses the mode-locked state quickly. As for robustness, the other experiment, at first, builds a database with UFL at different temperatures. It then trains the model and tests its performance. The results show that the average mode-locked recovery time of the trained network model is 1.948 s. As far as we know, it is 62.8% of the fastest average mode-locked recovery time in the existing work. At different temperatures, the trained network model can also recover the mode-locked state of the UFL in a short time. Remote algorithm training and automatic mode-locked control are proved in this work, laying the foundation for long-distance maintenance and centralized control of UFLs.

Metasurface plays a key role in various terahertz metadevices, while the designed terahertz metasurface still lacks flexibility and variety. On the other hand, inverse design has drawn plenty of attention due to its flexibility and robustness in the application of photonics. This provides an excellent opportunity for metasurface design as well as the development of multifunctional, high-performance terahertz devices. In this work, we demonstrate that, for the first time, a terahertz metasurface supported by the electromagnetically induced transparency (EIT) effect can be constructed by inverse design, which combines the particle swarm optimization algorithm with the finite-difference time-domain method. Incorporating germanium (Ge) film with inverse-designed metasurface, an ultrafast EIT modulation on the picosecond scale has been experimentally verified. The experimental results suggest a feasibility to build the terahertz EIT effect in the metasurface through an optimization algorithm of inverse design. Furthermore, this method can be further utilized to design multifunctional and high-performance terahertz devices, which is hard to accomplish in a traditional metamaterial structure. In a word, our method not only provides a novel way to design an ultrafast all-optical terahertz modulator based on artificial metamaterials but also shows the potential applications of inverse design on the terahertz devices.