We present a novel scheme for rapid quantitative analysis of debris generated during experiments with solid targets following relativistic laser–plasma interaction at high-power laser facilities. Results are supported by standard analysis techniques. Experimental data indicate that predictions by available modelling for non-mass-limited targets are reasonable, with debris of the order of hundreds of μg per shot. We detect for the first time two clearly distinct types of debris emitted from the same interaction. A fraction of the debris is ejected directionally, following the target normal (rear and interaction side). The directional debris ejection towards the interaction side is larger than on the side of the target rear. The second type of debris is characterized by a more spherically uniform ejection, albeit with a small asymmetry that favours ejection towards the target rear side.

Single-molecule localization microscopy (SMLM) provides nanoscale imaging, but pixel integration of acquired SMLM images limited the choice of sampling rate, which restricts the information content conveyed within each image. We propose an upsampled point spread function (PSF) inverse modeling method for large-pixel single-molecule localization, enabling precise three-dimensional superresolution imaging with a sparse sampling rate. Our approach could reduce data volume or expand the field of view by nearly an order of magnitude, while maintaining high localization accuracy and greatly improving the imaging throughput with the limited pixels available in existing cameras.

We present a high-power mid-infrared single-frequency pulsed fiber laser (SFPFL) with a tunable wavelength range from 2712.3 to 2793.2 nm. The single-frequency operation is achieved through a compound cavity design that incorporates a germanium etalon and a diffraction grating, resulting in an exceptionally narrow seed linewidth of approximately 780 kHz. Employing a master oscillator power amplifier configuration, we attain a maximum average output power of 2.6 W at 2789.4 nm, with a pulse repetition rate of 173 kHz, a pulse energy of 15 μJ and a narrow linewidth of approximately 850 kHz. This achievement underscores the potential of the mid-infrared SFPFL system for applications requiring high coherence and high power, such as high-resolution molecular spectroscopy, precision chemical identification and nonlinear frequency conversion.

Driven by advancements in artificial intelligence, end-to-end learning has become a key method for system optimization in various fields, including communications. However, applying learning algorithms such as backpropagation directly to communication systems is challenging due to their non-differentiable nature. Existing methods typically require developing a precise differentiable digital model of the physical system, which is computationally complex and can cause significant performance loss after deployment. In response, we propose a novel end-to-end learning framework called physics-guided learning. This approach performs the forward pass through the actual transmission channel while simplifying the channel model for the backward pass to a simple white-box model. Despite the simplicity, both experimental and simulation results show that our method significantly outperforms other learning approaches for digital pre-distortion applications in coherent optical fiber systems. It enhances training speed and accuracy, reducing the number of training iterations by more than 80%. It improves transmission quality and noise resilience and offers superior generalization to varying transmission link conditions such as link losses, modulation formats, and scenarios with different transmission distances and optical amplification. Furthermore, our new end-to-end learning framework shows promise for broader applications in optimizing future communication systems, paving the way for more flexible and intelligent network designs.

High-performance infrared emitters hold substantial importance in modern engineering and physics. Here, we introduce graphene/PZT (lead zirconate titanate) heterostructure as a new platform for the development of infrared source structure based on an electron–phonon coupling and emitting mechanism. A series of electrical characterizations including carrier mobility [11,361.55 cm2/(V·s)], pulse current (30 ms response time), and cycling stability (2000 cycles) modulated by polarized film was provided. Its maximum working temperature reaches ∼1041 K (∼768°C), and it was broken at 1173 K (∼900°C) within ∼1.2 s rise time and fall time. Based on Wien’s displacement law, the high temperature will lead to near–mid–far thermal infrared when the heterostructure is applied to external voltages, and obvious bright white light could be observed by the naked eye. The changing process has also been recorded by mobile phone. In subsequent infrared emitting applications, 11 V bias voltage was applied on the PZT/graphene structure to produce the temperature change of ∼299 to 445 K within ∼0.96 s rise time and ∼0.98 s fall time. To demonstrate its optical information transmission ability, we exhibited “N, U, C” letters by the time-frequency method at 3 mm×3 mm@20 m condition. Combining with spatial Morse code infrared units, alphabetic information could also be transmitted by infrared array images. Compared with the traditional infrared emitter, the electron–phonon enhancing mechanism and high-performance emission properties of the heterostructure demonstrated a novel and reliable platform for further infrared optical applications.

Imaging in the solar blind ultraviolet (UV) region offers significant advantages, including minimal interference from sunlight, reduced background noise, low false-alarm rate, and high sensitivity, and thus has important applications in early warning or detection of fire, ozone depletion, dynamite explosions, missile launches, electric leakage, etc. However, traditional imaging systems in this spectrum are often hindered by the bulkiness and complexity of conventional optics, resulting in heavy and cumbersome setups. The advent of metasurfaces, which use a two-dimensional array of nano-antennas to manipulate light properties, provides a powerful solution for developing miniaturized and compact optical systems. In this study, diamond metalenses were designed and fabricated to enable ultracompact solar-blind UV imaging. To prove this concept, two representative functionalities, bright-field imaging and spiral phase contrast imaging, were demonstrated as examples. Leveraging diamond’s exceptional properties, such as its wide bandgap, high refractive index, remarkable chemical inertness, and high damage threshold, this work not only presents a simple and feasible approach to realize solar-blind imaging in an ultracompact form but also highlights diamond as a highly capable material for developing miniaturized, lightweight, and robust imaging systems.

We propose a modular designed over-coupled (OC) metasurface for the broadband surface-enhanced infrared absorption spectroscopy (SEIRAS) by analyzing the combined properties in the far field and near field. The customized sensors can independently modify the coupling mode, the resonance frequency, and the coupling efficiency by adjusting the vertical and horizontal structures and hybrid dielectric layers of the metasurface, respectively. Based on the independent regulation of the sensor properties, the influence of the detuning properties, the level of OC coupling, and the coupling efficiency of the signal amplification can be clearly presented through the single variable-controlling approach. These design principles are universal for customized sensors and herald possibilities for machine-learning-aided surface-enhanced infrared absorption (SEIRA) biosensing.

With the rapid advancement of three-dimensional (3D) scanners and 3D point cloud acquisition technology, the application of 3D point clouds has been increasingly expanding in various fields. However, due to the limitations of 3D sensors, the collected point clouds are often sparse and non-uniform. In this work, we introduce local tactile information into the point cloud super-resolution task to aid in enhancing the resolution of the point cloud using fine-grained local details. Specifically, the local tactile point cloud is denser and more accurate compared to the low-resolution point cloud. By leveraging tactile information, we can obtain better local features. Therefore, we propose a feature extraction module that can efficiently fuse visual information with dense local tactile information. This module leverages the features from both modalities to achieve improved super-resolution results. In addition, we introduce a point cloud super-resolution dataset that includes tactile information. Qualitative and quantitative experiments show that our work performs much better than existing similar works that do not include tactile information, both in terms of handling low-resolution inputs and revealing high-fidelity details.

Fiber specklegram sensors are widely studied for their high sensitivity and compact design. However, as the number of modes in the fiber increased, the speckle sensitivity heightened along with the correlation diminished, lowering the sensing performance. In this paper, an innovative method is introduced based on digital aperture filtering (DAF) that adopts physical principle analysis, which reduces the collection aperture by computationally screening out the energy of higher-order modes within the speckle, therefore enhancing the correlation among speckles. Subsequently, a multi-layer convolutional neural network is designed to accurately and efficiently identify the measurands represented from the filtered speckles. By comparing the experimental results of the speckle demodulation method on different multimode fibers in light field direction sensing, the DAF method has shown outstanding performance in sensing accuracy, sensing range, stability, resolution, and generalizability, fully demonstrating its tremendous potential in the advancement of fiber sensing technology.

Coupled-waveguide devices are essential in photonic integrated circuits for coupling, polarization handling, and mode manipulation. However, the performance of these devices usually suffers from high wavelength and structure sensitivity, which makes it challenging to realize broadband and reliable on-chip optical functions. Recently, topological pumping of edge states has emerged as a promising solution for implementing robust optical couplings. In this paper, we propose and experimentally demonstrate broadband on-chip mode manipulation with very large fabrication tolerance based on the Rice–Mele modeled silicon waveguide arrays. The Thouless pumping mechanism is employed in the design to implement broadband and robust mode conversion and multiplexing. The experimental results prove that various mode-order conversions with low insertion losses and intermodal crosstalk can be achieved over a broad bandwidth of 80 nm ranging from 1500 to 1580 nm. Thanks to such a topological design, the device has a remarkable fabrication tolerance of ±70 nm for the structural deviations in waveguide width and gap distance, which is, to the best of our knowledge, the highest among the coupled-waveguide mode-handling devices reported so far. As a proof-of-concept experiment, we cascade the topological mode-order converters to form a four-channel mode-division multiplexer and demonstrate the transmission of a 200-Gb/s 16-quadrature amplitude modulation signal for each mode channel, with the bit error rates below the 7% forward error correction threshold of 3.8 × 10 - 3. We reveal the possibility of developing new classes of broadband and fabrication-tolerant coupled-waveguide devices with topological photonic approaches, which may find applications in many fields, including optical interconnects, quantum communications, and optical computing.