Altermagnetism features momentum-dependent spin splitting without net magnetization, extending spintronics beyond conventional ferromagnetism and antiferromagnetism. However, the photonic realization of altermagnetism has remained a formidable challenge due to the fundamental differences between fermionic electrons and bosonic photons. Here, we report the first experimental realization of an orbital altermagnetic photonic crystal, based on an antiunitary C_4z𝒯 symmetry enforced correspondence between a local p-orbital σ/π doublet and crystal momentum. We experimentally demonstrate that the resulting system exhibits momentum-dependent spin splitting with alternating pseudospin polarization and a d_xy-wave form factor, as confirmed by measured band structures and iso-frequency contours. Moreover, we show that the orbital altermagnetic photonic crystal supports unique pseudospin-selective transport of electromagnetic waves, including photonic pseudospin splitting and pseudospin filtering. Our results extend the field of alternagnetism to photonic systems, opening a new avenue for designing spinphotonic devices.

Broadcasting systems often suffer from coverage limitations and uneven service quality, particularly in nonline-of-sight (NLOS) environments. Reconfigurable intelligent surface (RIS) has emerged as a promising technology capable of reshaping electromagnetic propagation paths to enhance signal coverage in complex wireless environments. However, the inability of RIS to directly acquire channel state information (CSI) restricts its adaptability. In this article, we propose a novel hybrid RIS (HRIS)-assisted broadcasting scheme that maximizes the minimum signal-to-noise ratio (SNR) of users, where HRIS enables simultaneous signal reflection and real-time CSI acquisition. We formulate the problem as the maximization of the worst case SNR of users by optimizing the HRIS phase configuration based on directly acquired CSI. A gradient-based optimization algorithm is developed to iteratively update the phase matrix of HRIS while preserving the fairness among users in the broadcasting system. Simulation results demonstrate that the proposed scheme achieves considerable improvements in SNR and the sum rate of all users. Moreover, a prototype system is implemented with an $8 imes 8$ HRIS array. The measurement results show good consistency with the simulation results. The experimental validation further confirms the effectiveness of the proposed scheme, achieving up to 16.47 dB performance enhancement.

Achieving integrated sensing and communication (ISAC) via uplink transmission is challenging due to the unknown waveform and the coupling of communication and sensing echoes. In this paper, a joint uplink communication and imaging system is proposed for the first time, where a reconfigurable intelligent surface (RIS) is used to manipulate the electromagnetic signals for echo decoupling at the base station (BS). Aiming to enhance the transmission gain in desired directions and generate required radiation pattern in the region of interest (RoI), a phase optimization problem for RIS is formulated, which is high dimensional and nonconvex with discrete constraints. To tackle this problem, a back propagation based phase design scheme for both continuous and discrete phase models is developed. Moreover, the echo decoupling problem is tackled using the Bayesian method with the factor graph technique, where the problem is represented by a graph model which consists of difficult local functions. Based on the graph model, a message-passing algorithm is derived, which can efficiently cooperate with the adaptive sparse Bayesian learning (SBL) to achieve joint communication and imaging. Numerical results show that the proposed method approaches the relevant lower bound asymptotically, and the communication performance can be enhanced with the utilization of imaging echoes.

Programmability greatly enhances the degree of freedom to manipulate electromagnetic (EM) waves dynamically and lays crucial foundation for intelligent applications of metasurfaces. However, the traditional programmable metasurfaces need complicated biasing networks to control m×n digital meta-atoms independently to fulfill the reprogrammable functions in real time, which also results in large power consumption to drive the metasurface. To alleviate this problem, we propose an XOR-logic phase coding programmable metasurface to reduce the complexity of biasing network from m×n to m+n, which can reduce the power consumption significantly. The XOR-logic phase coding is achieved by path symmetry of surface currents on a Pancharatnam-Berry meta-atom loaded with two PIN diodes. By controlling 2×m×n PIN diodes on the whole metasurface in row-column manner, only m+n biasing lines are required to switch 0 and 1 states of all meta-atoms independently. As the proof of concept, a prototype of the XOR-logic phase coding programmable metasurface is designed and fabricated. Both simulation and measured results verify the reprogrammable functions of beam scanning and multi-beam scattering. This work provides a new type programmable metasurface with simple architecture and low power consumption, which will find wide applications in intelligent systems such as next-generation wireless communication, Internet of Things, and radar.

Abstract The rapid development of artificial intelligence (AI) has revolutionized traditional design and optimization approaches for metamaterials. By leveraging AI techniques, the time required for the metamaterial design process is significantly reduced, thus improving the overall efficiency. On the other hand, the advancement of AI has placed extremely high demands on computational power. In exploring high-speed and energy- efficient next-generation computing hardware, metasurface-based intelligent computing technologies such as diffractive neural networks have attracted widespread attention. In this work, we focus on two main aspects: intelligent design of metasurfaces and intelligent computing based on metasurfaces. In the field of intelligent design, we analyze how deep learning-based inverse design methods overcome the efficiency bottleneck of traditional electromagnetic simulations and enable high-precision and automated generation of subwavelength structures. In intelligent computing, we comprehensively explore the implementation mechanisms of optical diffractive neural networks and microwave programmable neural networks based on metamaterials. By comparing the application performance of physical neural networks with different architectures in scenarios such as image recognition and wireless communication, we reveal the crucial role of deep integration of the metasurfaces and AI in driving new computing paradigms, providing a theoretical framework and technological roadmap for next-generation intelligent electromagnetic systems.

To satisfy the increasing demands for wireless transmission rates, it is necessary to exploit spatial resources of electromagnetic (EM) waves. In this context, EM information theory (EIT) has emerged as a hot topic by integrating the theoretical framework of deterministic mathematics and stochastic statistics to explore the transmission mechanisms of continuous EM waves. However, the previous studies were primarily focused on the analysis of the spatial degrees of freedom, with limited exploration of a comprehensive understanding of the essential physical characteristics of EIT. In this paper, a three-dimensional (3D) line-of-sight channel capacity formula is proposed, which captures the vector EM physics and accommodates both near- and far-field scenes. A novel channel model is established based on the rigorous mathematical equation and the physical mechanism of fast multipole algorithm, and it is revealed that the scattered EM waves have finite angular spectral bandwidth, which determines the eigenvalue distributions of the communication system. Furthermore, a series of orthogonal basis are constructed for the currents on the transmitter and the fields on the receiving aperture, thus supporting the optimal design of the spatial precoder and combiner. Comprehensive analyses are made to investigate the relationship among the noise, transmitted power, and spatial degree of freedom, thereby establishing a rigorous upper bound of channel capacity. Finally, a series of simulations are conducted to validate the theoretical model and numerical method. This work offers a novel perspective and methodology for comprehending and leveraging spatial resources of wireless channels, and provides a theoretical foundation for the design and optimization of the holographic communications.

Abstract New-generation windows require advanced multi-physics modulation capability to accommodate diverse functions, including optical transparency, thermal insulation, and wireless communication compatibility. In response to these demands, metasurfaces have emerged as a promising solution owing to their versatile and energy-efficient electromagnetic (EM) wave manipulations. However, the existing prototypes suffer from fixed functionalities and limited intelligence, restricting their practicality and sustainability. Here, we show a green-smart window based on programmable metasurface to simultaneously achieve high visible transparency, low infrared (IR) emissivity, and reconfigurable EM responses. By integrating a compact RFID (radio frequency identification) tag, three intelligent functions are remotely reconfigured in a self-powering manner: EM transmission enhancement, selective EM shielding, and polarization filtering. For verification, a prototype is fabricated to validate its visible-IR-EM multi-physics controls, remote-sensing range, self-powering capability, and thermal management. Indoor-to-indoor (I2I) and outdoor-to-indoor (O2I) communication scenarios are established, demonstrating significant improvement in communication quality by using the green-smart window.

ABSTRACT The explosive growth of the low‐altitude economy has positioned drones as essential components of modern airspace. However, the reliable identification and tracking of “low‐altitude, small, and slow” objects remain challenging. Existing monitoring approaches often rely on active cooperation with high energy consumption, or degrade under adverse environmental conditions, constraining their applicability in complex urban environments. Here we propose MetaLicPlate, a low‐cost, zero‐power, and multifunctional metasurface license plate for joint drone identification and motion tracking. Mounted passively on a drone, MetaLicPlate simultaneously encodes identity and motion information into its electromagnetic time–frequency response. A time–frequency multiplexing framework allows a ground station to extract drone identity from frequency‐domain echoes using a convolutional neural network, while estimating distance and velocity from time‐domain signals in real time. Indoor and outdoor experiments demonstrate high identification accuracy and precise motion estimation, highlighting MetaLicPlate as a potential passive platform for integrated drone monitoring in dense low‐altitude airspace.

Programmable metasurfaces bring new opportunities for modern acoustic and electromagnetic technologies by dynamically tailoring wave-matter interactions at subwavelength scales. Due to differences in physical properties and tuning mechanisms of acoustic and electromagnetic waves, current programmable metasurfaces typically manipulate only one type of wave, while concurrent and programmable controls of both waves remain elusive. Here, we propose a dual-physics programmable metasurface capable of simultaneous, independent and dynamic manipulations of acoustic and electromagnetic waves. The presented metasurface consists of 324 micromotor-driven elements that are individually addressable and wirelessly controlled. Each element can achieve 1-bit reflection phase modulation of both acoustic and electromagnetic waves by dynamic geometric rotation, allowing the metasurface to realize on-demand and decoupled reconfiguration of acoustic and electromagnetic functionalities. The intriguing features of the metasurface are demonstrated by simultaneously achieving local audio enhancement and radio-frequency relay communications, as well as acoustic-electromagnetic dual-channel information camouflage. This work offers significant promise for future metasurface-based multi-physics wireless communications and information security.

This article proposes a zero static power consumption, enhanced gain, and 2-D reconfigurable antenna assembly based on liquid metal. The edge-truncated patches are integrated with triangular microfluidic chips and liquid metal. This integration facilitates the polarization reconfiguration among left-hand circular polarization (LHCP), right-hand circular polarization (RHCP), and linear polarization (LP). Furthermore, while reconstructing the top edge-truncated patches, it is possible to reconfigure the feeding networks at the bottom. Specifically, the feeding networks within the antenna assembly are integrated with U-shaped microfluidic chips and liquid metal. This integration is designed to achieve a phase difference of $180<^>{\mathbf {o}}$ for each unit. Consequently, the antenna assembly can simultaneously achieve polarization and directivity reconfiguration. This liquid metal-based approach opens a new paradigm for designing antenna systems with low power consumption, enhanced gain performance, and adaptive beamforming capabilities, while offering significant potential for applications in 5G/6G communications and intelligent wireless communication systems.

Reconfigurable intelligent surface (RIS) technology is believed to effectively solve the dilemma of terahertz wireless communication in non-line-of-sight scenarios. Notably, the deployment of large-scale RIS arrays at high frequencies brings about significant near-field effects, resulting in extensive near-field areas, which provides the possibility for the application of near-field communication. In this paper, a pixelated liquid crystal programmable metasurface (PLCPM) is proposed to effectively manipulate terahertz waves in the near-field region. Leveraging the tunability of liquid crystal (LC) materials, the proposed PLCPM achieves 1-bit phase coding capability within the 104-110 GHz frequency band. Subsequently, by combining lithography machining with printed circuit board (PCB) manufacturing technology, the pixelated controllability of the PLCPM is realized. The simulation and experimental results demonstrate that the proposed PLCPM can perform multifunctional near-field beam control for terahertz waves, including focusing beams for different distances and positions, near-field orbital angular momentum (OAM) beams for large-capacity communication, and Bessel beams for long-distance propagation. These results verify the effectiveness of the proposed PLCPM in flexibly controlling near-field beams, paving the way for the application of RIS in terahertz near-field communication. (c) 2026 Chinese Laser Press

Amplitude-phase programmable metasurfaces (APPMs) have attracted significant attention in recent years for their real-time control of electromagnetic (EM) waves. However, existing APPMs often face challenges such as low energy efficiency, limited amplitude-tuning range, and low phase-modulation resolution. Additionally, achieving high-precision amplitude and phase modulations simultaneously requires complex control circuits, thereby increasing the system cost and complexity. To address these challenges, an amplifying APPM (AAPPM) is proposed that achieves independent wide-range amplitude tuning and high-precision phase control through a novel and simplified architecture. Specifically, the designed AAPPM is embedded with gain-tunable amplifiers, achieving over 5 dB EM-energy amplification and approximate to 30 dB dynamic amplitude-tuning range. Meanwhile, the AAPPM provides the 1-bit phase modulations by controlling the states of integrated PIN diodes. With the introduction of time-coding techniques, it can further achieve wide-range and high-precision phase controls of harmonics. To demonstrate its capability, a 6x6 AAPPM prototype is designed, simulated, and measured. The results indicate that AAPPM can achieve EM energy amplification, wide-range dynamic amplitude control, and high-precision phase modulation. By implementing various time-coding strategies, the AAPPM facilitates flexible harmonic beam manipulations. With these distinctive features, the AAPPM shows great potential in wireless communication and radar systems.

ABSTRACT Resonance‐mode manipulation is a fundamental and critical issue in electromagnetic science, underpinning diverse functions including energy localization, wave modulation, nonlinear interactions, and information processing across frequencies from microwaves to optics. Here, we propose to manipulate the mode resonance and coupling based on spoof localized surface plasmon (SLSP) on metallic spiral structures (MSS) with low‐symmetry, which are composed of four spiral arms with two different lengths. By extending group representation theory to low‐symmetry configurations and introducing the concept of current order, the resonance and coupling behaviors can be analytically predicted, showing excellent agreement with numerical simulations and measured results. Two distinct magnetic dipole modes are discovered, supported by the first‐order and second‐order current distributions, respectively. Tuning the length difference between spiral arms enables lower resonance frequencies and greater flexibility in coupling control. These findings help understand mode manipulation by symmetry in electromagnetic metamaterials, enrich the toolbox for resonance and coupling engineering, and open new avenues to develop advanced resonance devices.

Information metamaterials are digital coding electromagnetic structures that connect wave control with information processing, offering programmable routes to beam shaping, focusing and holographic imaging. Their inverse design remains challenging because both meta-atoms and spatial coding arrays must be selected from a vast combinatorial space, and existing optimization or learning methods are often tailored to specific tasks, bit resolutions or field patterns. Here we show a generative model for information metamaterial design that learns a shared design prior and transfers it across diverse electromagnetic functions. The model combines a pretrained diffusion backbone with lightweight functionality-oriented adapters, enabling the generation of multibit meta-atoms with prescribed responses and nonuniform arrays for beam steering, near-field focusing and holography. Numerical simulations and experiments validate high-performance meta-atoms and functional 1-bit and 3-bit meta-arrays. For holographic design, the model reaches Gerchberg-Saxton-level fidelity while reducing runtime by over three orders of magnitude, establishing a scalable route to information-metamaterial discovery.

Mastering invisible electromagnetic (EM) environment and sculpting radio waves with the dexterity of manipulating light or matter have long been aspirations in physics and information science. While information metasurfaces (IMSs) provide the physical interface to program EM wavefields, their real-world autonomy is fundamentally limited by environmental 'blindness' and the prohibitive overhead of site-specific and trial-and-error retraining. Here we propose metasurface embodied intelligence through world model (metaEI-WM), a universal and out-of-the-box paradigm that achieves expert-level performance without on-site fine-tuning. In contrast to purely data-driven agents, metaEI-WM establishes a fundamental understanding of the EM dynamics by integrating fully automated semantic environment modelling with embedded electrodynamic priors. By anticipating future scenarios in silico, it optimizes the IMS coding configurations to dynamically shape EM environments on demand. We show that metaEI-WM successfully enables zero-latency non-line-of-sight signal enhancements, symbiotic communications, and contactless physiological sensing across highly complex and unseen indoor scenarios. To the best of our knowledge, metaEI-WM is the first paradigm to achieve end-to-end automation of complex spatial channel manipulation tasks ab initio, requiring neither human-annotated data nor online training. This framework bridges the gap between digital intelligence and physical-layer wave dynamics, offering a scalable solution for robust and self-managing wireless ecosystems.

Plasmonic skyrmions are electromagnetic counterparts of topologically stable quasiparticles and could potentially be used as robust information carriers. However, practical applications require tunable devices that can encode the topological structures. Here we report a programmable platform that can encode plasmonic skyrmions with diverse topologies, including N & eacute;el-type skyrmions and merons. We synthesize harmonic skyrmions in the temporal dimension using ultrafast coding and apply the skyrmions in communication and sensing applications. In particular, we show that the programmable topological skyrmions can be used in robust and multichannel wireless communications, suggesting that the approach could provide communications in turbulent noise channels and extreme conditions. Together with a convolutional neural network, we also show that the platform can be used in the intelligent sensing of 20 animal figurines, achieving high recognition accuracy.

Diffraction is a fundamental wave phenomenon that describes the spreading of waves when they encounter an obstacle or aperture comparable to their wavelength. Beyond the conventional spatial diffraction, waves can also exhibit diffraction-like behavior in temporal and spatiotemporal domains. In microwave regime, the diffraction plays a crucial role in shaping electromagnetic fields; however, its time and space-time counterparts with reprogrammable characteristics remain largely unexplored. Here, we investigate the time and space-time diffraction in the microwave band using a transmission-reflection-integrated programmable metasurface (TRPM). The physical feasibility of time and space-time diffraction is first established by theoretical analyses and numerical simulations. To enable experimental realization, a 1 bit amplitude-programmable element capable of switching between the reflection and transmission modes is presented, from which a TRPM prototype is fabricated and measured. Experimental results demonstrate that distinct time diffraction phenomena are observed in the frequency domain, while space-time diffraction effects emerge in the momentum-frequency domain by appropriately reconfiguring the time and space-time coding matrices of TRPM. The good agreement between experimental and numerical results illustrates the feasibility and flexibility of the proposed TRPM in realizing the programmable space-time diffraction, highlighting its potential as a versatile platform to explore fundamental physics and exotic functions in space-time metamaterials and metasurfaces.

Intelligent metasurfaces have demonstrated great promise in revolutionizing wireless communications. One notable example is the two-dimensional (2D) programmable metasurface, which is also known as reconfigurable intelligent surfaces (RIS) to manipulate the wireless propagation environment to enhance network coverage. More recently, three-dimensional (3D) stacked intelligent metasurfaces (SIM) have been developed to substantially improve signal processing efficiency by directly processing analog electromagnetic signals in the wave domain. Another exciting breakthrough is the flexible intelligent metasurface (FIM), which possesses the ability to morph its 3D surface shape in response to dynamic wireless channels and thus achieve diversity gain. In this paper, we provide a comprehensive overview of these emerging intelligent metasurface technologies. We commence by examining recent experiments of RIS and exploring its applications from four perspectives. Furthermore, we delve into the fundamental principles underlying SIM, discussing relevant prototypes as well as their applications. Numerical results are also provided to illustrate the potential of SIM for analog signal processing. Finally, we review the state-of-the-art of FIM technology, discussing its impact on wireless communications and identifying the key challenges of integrating FIMs into wireless networks.