The cold atom qubit platform emerges as an attractive choice for the next stage of quantum computation research, where a special family of synthetic analytical pulses has considerably improved the experimental performance of Controlled-PHASE Rydberg blockade gates in recent studies. The success of Controlled-PHASE Rydberg blockade gates triggers the intriguing question of whether the two-qubit Rydberg blockade gate SWAP gate exists. Via investigating the transition linkage structure, we provide a definitive answer to this question and establish the method of fast SWAP Rydberg blockade gates with synthetic continuously modulated driving. These gate protocols use careful analysis to properly generate coherent population transfer and phase accumulation of the wave function in the atom-laser interaction process. They can adapt to finite Rydberg blockade strengths and bear considerable resistance to some major adverse effects such as laser fluctuations. Further examinations reveal that we can anticipate satisfying performances of the method with currently available experimental techniques in relevant research areas.

AlGaN-based deep-ultraviolet (DUV) light-emitting diodes (LEDs) still face challenges in achieving high-quality AlGaN material and extracting the strong transverse magnetic (TM) mode emission (which is influenced by valence band splitting inversion). Particularly, these challenges impact devices with wavelengths shorter than 250 nm on their optical power and wall-plug efficiency (WPE) due to an increased proportion of TM mode. Here, the plasmonic omni-directional reflective pad arrays were designed and introduced into the p-contact layer to enhance the light extraction for sub-250 nm DUV LEDs. Meanwhile, a novel device structure, to our knowledge, was put forward, integrating uniformly distributed n-type contact rods as an efficient light guide channel. The theoretical simulation demonstrated a light extraction improvement since these embedded plasmonic reflective pad arrays effectively altered the wavevector of transverse electric (TE) and TM mode photons from the quantum wells. An average enhancement of 12.5% in optical output power was attained in 249.5 nm DUV LEDs through the usage of the optimized diameter of the plasmonic pads. Furthermore, a quartz lens bonded with fluorine resin was introduced to improve refractive index matching at the light output interface, and a high optical power of 3.45 mW was achieved from the original 2.55 mW at a driven current of 100 mA.

The transportable optical clock can be deployed in various transportation vehicles, including aviation, aerospace, maritime, and land-based vehicles; provides remote time standards for geophysical monitoring and distributed coherent sensing; and promotes the unmanned and lightweight development of global time network synchronization. However, the current transportable version of laboratory optical clocks is still limited by factors such as environmental sensitivity, manual maintenance requirements, and high cost. Here we report a single-person portable optical frequency standard using the recently proposed atomic-filter-based laser “Voigt laser” as the local oscillator. It is worth mentioning that due to the inherent characteristics of Voigt lasers, the Voigt optical frequency standard can maintain turn-key functionality under harsh environmental impacts without any manual maintenance requirement. In our experiment, conducted over a duration of 12 min, we subjected the laser diode to multiple temperature shocks, resulting in a cumulative temperature fluctuation of 15°C. Following each temperature shock event, the Voigt optical frequency standard automatically relocked and restored the frequency output. Therefore, this demonstration marks a significant technological breakthrough in automatic quantum devices and might herald the arrival of fully automated time network systems.

On-chip superconducting nanowire single-photon detectors (SNSPDs) are gaining traction in integrated quantum photonics due to their exceptional performance and the elimination of fiber coupling loss. However, off-chip high-rejection filters are commonly required to remove the intense pump light employed in quantum states generation, thus remaining the obstacle for embedding SNSPDs into quantum photonic circuits. Here, we explore the integration of SNSPDs with passive pump rejection filters, achieved by cascaded silicon Bragg gratings, on a single substrate. Serving as an entanglement receiver chip, the integrated components show a system detection efficiency of 20.1% and a pump rejection ratio of approximately 56 dB. We successfully verify energy-time entangled photon pairs from a microring resonator with raw visibilities of 92.85%±5.95% and 91.91%±7.34% under two nonorthogonal bases, with use of standard fiber wavelength demultiplexers. Our results pave the way for entanglement resource distribution, offering a promising approach toward the construction of large-scale quantum photonic systems.

The rapid advancement of artificial intelligence (AI) has significantly impacted photonics, creating a symbiotic relationship that accelerates the development and applications of both fields. From the perspective of AI aiding photonics, deep-learning methods and various intelligent algorithms have been developed for designing complex photonic structures, where traditional design approaches fall short. AI’s capability to process and analyze large data sets has enabled the discovery of novel materials, such as for photovoltaics, leading to enhanced light absorption and efficiency. AI is also significantly transforming the field of optical imaging with improved performance. In addition, AI-driven techniques have revolutionized optical communication systems by optimizing signal processing and enhancing the bandwidth and reliability of data transmission. Conversely, the contribution of photonics to AI is equally profound. Photonic technologies offer unparalleled advantages in the development of AI hardware, providing solutions to overcome the bottlenecks of electronic systems. The implementation of photonic neural networks, leveraging the high speed and parallelism of optical computing, demonstrates significant improvements in the processing speed and energy efficiency of AI computations. Furthermore, advancements in optical sensors and imaging technologies not only enrich AI applications with high-quality data but also expand the capabilities of AI in fields such as autonomous vehicles and medical imaging. We provide comprehensive knowledge and a detailed analysis of the current state of the art, addressing both challenges and opportunities at the intersection of AI and photonics. The multifaceted interactions between AI and photonics will be explored, illustrating how AI has become an indispensable tool in the development of photonics and how photonics, in turn, facilitates advancements in AI. Through a collection of case studies and examples, we underscore the potential of this interdisciplinary approach to drive innovation, proposing challenges and future research directions that could further harness the synergies between AI and photonics for scientific and technological breakthroughs.

A new on-chip light source configuration has been proposed, which utilizes the interaction between a microwave or laser and a dielectric nanopillar array to generate a periodic electromagnetic near-field and applies periodic transverse acceleration to relativistic electrons to generate high-energy photon radiation. The dielectric nanopillar array interacting with the driving field acts as an electron undulator, in which the near-field drives electrons to oscillate. When an electron beam propagates through this nanopillar array in this light source configuration, it is subjected to a periodic transverse near-field force and will radiate X-ray or even γ-ray high-energy photons after a relativistic frequency up-conversion. Compared with the undulator which is based on the interaction between strong lasers and nanostructures to generate a plasmonic near-field, this configuration is less prone to damage during operation.

Free electron radiation, particularly Smith-Purcell radiation, provides a versatile platform for exploring light-matter interactions and generating light sources. A fundamental characteristic of Smith-Purcell radiation is the monotonic decrease in radiation frequency as the observation angle increases relative to the direction of the free electrons’ motion, akin to the Doppler effect. Here, we demonstrate that this fundamental characteristic can be altered in Smith-Purcell radiation generated by photonic crystals with left-handed properties. Specifically, we have achieved, to our knowledge, a novel phenomenon that the lower-frequency components propagate forward, while the higher-frequency components propagate backward, which we define as reverse Smith-Purcell radiation. Additionally, this reverse Smith-Purcell radiation can confine the radiation to a narrow angular range, which provides a way to obtain broadband light sources in a specific observation angle. Furthermore, by precisely adjusting the grating geometry and the kinetic energy of the free electrons, we can control both the radiation direction and the output frequencies. Our results provide a promising platform to study unexplored light-matter interactions and open avenues to obtain tunable, broadband light sources.

Polarization-based detection technologies have broad applications across various fields. Integrating polarization with interferometric imaging holds significant promise for simultaneously capturing three-dimensional structure and polarization information. However, existing interferometric polarization measurement methods often rely on complex setups and sacrifice the acquisition rate or axial imaging range for parameter diversity. In this study, we presented an efficient and compact interferometric polarization measurement method based on spectral-polarization-modulation (SPM) and integrated it with optical coherence tomography (OCT) to construct an advancing interferometric imaging system called SPM-OCT. This method can extract birefringent and dichroic parameters from the polarization-modulated signal without reducing the acquisition rate or the axial imaging range. Imaging experiments on standard polarization elements, biological tissues, and gold nanorod (GNR) phantoms demonstrated that our proposed method provided accurate birefringent and dichroic parameters and avoided phase jump errors. Especially, the dichroic parameters obtained from our system can distinguish GNRs from biological tissues with high contrast. Overall, the rapid and simple polarization measurement of the SPM method is expected to advance the interferometric imaging method and inspire new research directions in polarization measurement technology.

Photonic devices that exhibit both sensitivity and robustness have long been sought; yet, these characteristics are thought to be mutually exclusive; through sensitivity, a sensor responds to external stimuli, whereas robustness embodies the inherent ability of a device to withstand weathering by these same stimuli. This challenge stems from the inherent contradiction between robustness and sensitivity in wave dynamics, which require the coexistence of noise-immune sensitive states and modulation-sensitive transitions between these states. We report and experimentally demonstrate a subwavelength phase singularity in a chiral medium that is resilient to fabrication imperfections and disorder while remaining highly responsive to external stimuli. The combination of subwavelength light confinement and its robustness lays the foundation for the development of hitherto unexplored chip-scale photonics devices, enabling a simultaneous development of high-sensitivity and robust devices in both quantum and classical realms.

Distributed acoustic sensors (DASs) can effectively monitor acoustic fields along sensing fibers with high sensitivity and high response speed. However, their data processing is limited by the performance of electronic signal processing, hindering real-time applications. The time-wavelength multiplexed photonic neural network accelerator (TWM-PNNA), which uses photons instead of electrons for operations, significantly enhances processing speed and energy efficiency. Therefore, we explore the feasibility of applying TWM-PNNA to DAS systems. We first discuss processing large DAS system data for compatibility with the TWM-PNNA system. We also investigate the effects of chirp on optical convolution in complex tasks and methods to mitigate its impact on classification accuracy. Furthermore, we propose a method for achieving an optical full connection and study the influence of pruning on the full connection to reduce the computational burden of the model. Experimental results indicate that decreasing the ratio of Δλchirp / Δλ or choosing push–pull modulation can eliminate the impact of chirp on recognition accuracy. In addition, when the full connection parameter retention rate is no less than 60%, it can still maintain a classification accuracy of over 90%. TWM-PNNA provides an innovative computational framework for DAS systems, paving the way for the all-optical fusion of DAS systems with computational systems.