Pu-Kun Liu

Optical computing, renowned for its light-speed processing and low power consumption, typically relies on the coherent control of two light sources. However, there are challenges in stabilizing and maintaining high optical spatiotemporal coherence, especially for large-scale computing systems. The coherence requires rigorous feedback circuits and numerous phase shifters, introducing system instability and complexity. Here we propose an innovative logic gate using a single light source, with frequency and polarization serving as two virtual inputs. Our design leverages frequency-polarization multiplexed metasurfaces to achieve all basic logic operations by selectively routing surface plasmon polaritons. This single-channel logic gate maintains inherent coherence between frequency and polarization, thereby considerably eliminating stringent light-source specifications and numerous rigid phase controls and resulting in higher stability. Our device showcases unique application potentials in on-chip readout of encryption information by using random sequences as a one-time pad, unlocking fresh prospects for information protection and optical computing with other simple light sources.

With the rapid development of nanophotonics for enhancing free-electron radiation, bound states in the continuum (BICs) have emerged as a promising approach for emitting intense Smith–Purcell radiation (SPR) with enhanced intensity. However, current BIC-based methods are limited to single-frequency operation, thereby restricting their applications requiring spectral and angular tunability, such as particle detectors and light sources. To overcome this limitation, this work proposes an approach for constructing plasmonic BICs over a broad spectral range in symmetry-broken systems. By leveraging the high-Q resonances near the BICs, we achieve intense SPR with broadband tunability, potentially improving the radiation intensity by six orders compared to traditional methods. Experimentally, we validate the construction of BIC using plasmonic antennas and achieve broadband demonstration. Our proposed concept can be extended to other plasmonic or guided-wave systems, paving the way toward compact and efficient free-electron sources in hard-to-reach frequency regimes.

Metasurfaces have recently experienced revolutionary progress in sensing and super-resolution imaging fields, mainly due to their manipulation of electromagnetic waves on subwavelength scales. However, on the one hand, the addition of metasurfaces can multiply the complexity of retrieving target information from detected electromagnetic fields. On the other hand, many existing studies utilize deep learning methods to provide compelling tools for electromagnetic problems but mainly concentrate on resolving one single function, limiting their versatilities. In this work, a multifunctional deep learning network is demonstrated to reconstruct diverse target information in a metasurface-target interactive system. First, a preliminary experiment verifies that the metasurface-involved scenario can tolerate the system noises. Then, the captured electric field distributions are fed into the multifunctional network, which can not only accurately sense the quantity and relative permittivity of targets but also generate super-resolution images precisely. The deep learning network, thus, paves an alternative way to recover the targets' information in metasurface-target interactive systems, accelerating the progression of target sensing and superimaging areas. Besides, another new network that allows forward electromagnetic prediction is also proposed and demonstrated. To sum up, the deep learning methodology may hold promise for inverse reconstructions or forward predictions in many electromagnetic scenarios.

Investigation of absolute instability (AI) and convective instability (CI) of the electron cyclotron maser has independently led to the birth of gyrotron oscillators and amplifiers. Here, it is demonstrated that these instabilities can form a cooperative relationship owing to the nonlinear behavior of the stimulated electron beam. The CI can be induced in a zero‐drive system with the assistance of AI, and the ohmic losses of all the excited waves inside the system are greatly reduced, which is called “instability entanglement” here. According to the theoretical and experimental study of a 167/330 GHz gyrotron, when instability entanglement occurs, the ohmic dissipation decreases to one‐ninth of the AI‐only condition, and the output power is enhanced by 20%. This discovery is promising for surpassing the ceiling of output power and frequency of gyrodevices placed by ohmic losses.

Recently, metasurfaces have experienced revolutionary growth in the sensing and superresolution imaging field, due to their enabling of subwavelength manipulation of electromagnetic waves. However, the addition of metasurfaces multiplies the complexity of retrieving target information from the detected fields. Besides, although the deep learning method affords a compelling platform for a series of electromagnetic problems, many studies mainly concentrate on resolving one single function and limit the research's versatility. In this study, a multifunctional deep neural network is demonstrated to reconstruct target information in a metasurface targets interactive system. Firstly, the interactive scenario is confirmed to tolerate the system noises in a primary verification experiment. Then, fed with the electric field distributions, the multitask deep neural network can not only sense the quantity and permittivity of targets but also generate superresolution images with high precision. The deep learning method provides another way to recover targets' diverse information in metasurface based target detection, accelerating the progression of target reconstruction areas. This methodology may also hold promise for inverse reconstruction or forward prediction problems in other electromagnetic scenarios.

Surface waves (SWs) are of great importance in terahertz (THz) photonics applications due to their subwavelength properties. Hence, it is crucial to develop surface wavefront shaping techniques, which is urgent in modern information technologies. In this paper, a new scheme is proposed to realize SW excitation and spin-decoupled wavefront shaping with an ultracompact planar meta-device working in the THz range. The meta-device is composed of two parts: meta-atoms (in the center) and plasmonic metals (on the left and right sides). By carefully setting the geometry size and rotation angle of each meta-atom, the encoded spin-decoupled phase distributions for both left circularly polarized (LCP) and right circularly polarized (RCP) incident THz waves are determined. In this way, circularly polarized (CP) incident THz waves can be converted to SWs propagating along plasmonic metals with unique wavefront profiles, i.e., Bessel and focusing profiles. Full-wave simulations and THz near-field scanning experiments were performed to verify the functionalities of the meta-device, both of which are in great agreement with theoretical predictions. Our findings may provide more solutions to design THz integrated photonic devices and systems.

As an active microwave coherent imaging technology, synthetic aperture radar (SAR) images suffer from severe speckle noise and low-resolution problems due to the limitations of the imaging system, which cause difficulties in image interpretation and target detection. However, the existing SAR super-resolution (SR) methods usually reconstruct the images by a determined degradation model and hardly consider multiplicative speckle noise, meanwhile, most SR models are trained with synthetic datasets in which the low-resolution (LR) images are down-sampled from their high-resolution (HR) counterparts. These constraints cause a serious domain gap between the synthetic and real SAR images. To solve the above problems, this paper proposes an unsupervised blind SR method for SAR images by introducing SAR priors in a cycle-GAN framework. First, a learnable probabilistic degradation model combined with SAR noise priors was presented to satisfy various SAR images produced from different platforms. Then, a degradation model and a SR model in a unified cycle-GAN framework were trained simultaneously to learn the intrinsic relationship between HR–LR domains. The model was trained with real LR and HR SAR images instead of synthetic paired images to conquer the domain gap. Finally, experimental results on both synthetic and real SAR images demonstrated the high performance of the proposed method in terms of image quality and visual perception. Additionally, we found the proposed SR method demonstrates the tremendous potential for target detection tasks by reducing missed detection and false alarms significantly.

Based on the principle of electron cyclotron maser (ECM), gyrotrons are among the most promising devices to generate powerful coherent terahertz (THz) radiation and play a vital role in numerous advanced THz applications. Unfortunately, THz ECM systems using a conventional high-Q cavity were theoretically and experimentally demonstrated to suffer from strong ohmic losses, and, accordingly, the wave output efficiency was significantly reduced. A scheme to alleviate such a challenging problem is systematically investigated in this paper. The traveling-wave operation concept is employed in a 1-THz third harmonic gyrotron oscillator, which strengthens electron-wave interaction efficiency and reduces the ohmic dissipation, simultaneously. A lossy belt is added in the interaction circuit to stably constitute the traveling-wave interaction, and a down-tapered magnetic field is employed to further amplify the forward-wave (FW) component. The results demonstrate that the proportion of ohmic losses is nearly halved, and output efficiency is nearly doubled, which is promising for further advancement of high-power continuous-wave operation of the ECM-based devices.

In this article, the design of a fourth-harmonic gyrotron with 1-kW-level output power at 1 terahertz (THz) is presented. A unique advantage of this design is that, with a well-optimized magnetic-cusp large-orbit electron gun, the designed gyrotron can operate from first-harmonic to fourth-harmonic in multiple discrete bands by varying the confining magnetic field strength. By carefully balancing the competing modes, the gyrotron can be tuned to operate at six candidate modes, including TE _1,2 for fundamental harmonic, TE _2,3 and TE _2,4 for second-harmonic, TE _3,5 and TE _3,6 for third-harmonic, and TE _4,8 for fourth-harmonic interactions. As the main operating mode, the TE _4,8 can generate a peak output power of 1.68 kW, with an output efficiency of about 2.1%, and a magnetically controlled frequency tuning range of about 1.5 GHz around 1 THz. The impact of the longitudinal nonuniformity of the cavity at high-harmonic interaction was also studied. It shows that a radial tolerance of several micrometers will significantly elevate the start-oscillation current and deteriorate output performance. This design is to produce a THz source with ultra-wideband tuning capability ranging from the submillimeter-wave to 1-THz bands.