Serendipity has long shaped transformative scientific discoveries, from penicillin and microwave oven to cosmic microwave background. These advances were not accidents but arose when prepared minds encountered unexpected phenomena in environments that enabled recognition and follow-up. In today's research climate, which often emphasizes narrowly defined goals and short-term deliverables, the role of serendipity is undervalued and frequently left to chance. This review introduces the concept of serendipity engineering: the intentional design of technologies, analytical frameworks, and research cultures that enhance the probability of meaningful chance discoveries. We outline four core principles - (i) expanding the observable space with advanced measurement tools, (ii) preserving anomalies through unbiased data stewardship, (iii) applying analytical methods that surface rare or emergent patterns, and (iv) fostering openness to unexpected results. Emphasis is placed on applications in biology and medicine empowered by advanced photonics and electromagnetism, where system complexity and disease heterogeneity make serendipitous findings particularly impactful. We propose a roadmap for embedding serendipity as a strategic component of 21st-century science, transforming it from a passive hope into an active driver of discovery.

Photonic crystals (PhCs) play a crucial role in describing the quantized collective behavior of wave functions. However, the existing investigations into their eigenstates primarily rely on classical computational methods. Variational quantum algorithm (VQA) represents a promising quantum computing technology that can be implemented on noisy intermediate-scale quantum (NISQ) devices, potentially surpassing the classical computational capabilities. Here, we propose a method to analyze the band and eigenstate properties of PhCs based on variational quantum eigensolver (VQE). We firstly reformulate the Maxwell's equations into a Hermitian generalized eigenvalue problem. By appropriately selecting a loss function and employing the proposed quantum eigenvalue solver, we successfully obtain the generalized eigenvalues using a quantum gradient descent algorithm. To validate our approach, we perform simulations on two prototypical PhCs in square and hexagonal lattices. The results demonstrate that a complex Ansatz can effectively capture the optimal solution, successfully yielding the generalized eigenvalues, but a simpler Ansatz exhibits significant limitations. Our findings provide new insights into the application of VQAs in PhCs and other quantum topological systems.

Coarse discretization introduces significant errors in the solution of scattering problems, in part due to discretization errors in the contrast operator. We present a procedure for the automatic construction of a modified contrast operator for electromagnetic scattering problems by using trainable neural networks to represent a modified contrast operator. We achieve a higher accuracy on a coarse discretization while still keeping computation time down compared to a fine discretization. By using synthetic data from a full-wave Maxwell solver to train the network for one-dimensional slab scatterers and two-dimensional polygonal scatterers, we are able to use the techniques found in deep learning to improve accuracy in coarse-grid forward scattering problems.

With the increasing demand for high-capacity communication systems, vortex beams endowed with orbital angular momentum (OAM) have emerged as a promising candidate for enhancing channel capacity of communication systems. Persistent limitations of conventional OAM generators, such as narrow bandwidth, single-mode constraints, and decreased purity in high-order OAM modes are addressed. In this work, by combining Pancharatnam-Berry (PB) phase theory and equivalent circuit, we design a metasurface unit with gradient phase compensation. The metasurface unit overcomes the bandwidth limits of the resonant structures, achieving 360˚ linear phase modulation over 8-20 GHz (85.7% relative bandwidth) and allowing vortex waves with multiple OAM modes and high order mode purity. Quantitative assessment of modal purity via OAM spectral decomposition demonstrates exceptional agreement between experimental measurements and full-wave simulations, thereby corroborating the theoretical framework and underscoring the methodology's potential for practical implementation.

A wide band, high gain 1 × 2 array Vivaldi shaped slot Substrate Integrated Waveguide (SIW) Multiple Input Multiple Output (MIMO) antenna with square shaped periodic Artificial Magnetic Conductor (AMC) placed beneath the antenna for applications in X band is presented. A two-port MIMO antenna backed by AMC patches is designed and realized for enhanced gain and bandwidth. The single antenna 1 × 2 array has electrical dimensions of 1.57λ_r × 1.13λ_r × 0.027λ_r. The designed antenna structure has bandwidth of 1.39 GHz (8.79 GHz-10.18 GHz) with a percentage bandwidth of 14.65% and Gain of 11.67 dBi. The edge to edge distance between the MIMO antenna elements is 5 mm (λ_r/4). The periodic AMC patches improve vital MIMO antenna performance metrics like Isolation, Envelope Correlation Coefficient (ECC), Diversity Gain (DG), Channel Capacity Loss (CCL) and radiation pattern. The unit cell analysis of periodic square AMC patch and a polynomial regression model to find the best goodness of fit for Gain-Bandwidth product versus square AMC patch size is studied. Antenna gain variation seen over the complete bandwidth is < 1 dBi which makes it a flat gain response antenna. The proposed high-gain, wide-band 1 × 2 Vivaldi-slot SIW MIMO antenna with AMC is suitable for X-band radar, point-to-point high-throughput wireless links, and compact platform communication systems requiring robust diversity performance.

In this paper, a new method is proposed for failure diagnosis of programmable metasurfaces, which jointly uses the single-point measurement strategy and Bernoulli-Gaussian (BG) prior. Specifically, leveraging the dynamic tuning property of programmable metasurfaces, the radiated fields is measured with a single fixed probe, therefore reducing the time and error of the measurement process. Moreover, the BG prior inherent in the programmable metasurface under test is exploited during the reconstruction process in order to perform the diagnosis with a small number of measurements without resorting to prior knowledge of the radiation pattern of the failure-free programmable metasurface. The accuracy, efficiency and robustness of the proposed method are verified through a set of representative numerical experiments, where the results are compared with those from existing diagnostic methods.

This paper presents a passive, structure-based approach for selective signal transmission and crosstalk suppression in dense radio frequency identification (RFID) tag environments. The proposed method employs a mechanically reconfigurable double-layer tag design based on the mirror-antenna principle, which enables dynamic switching between transmission and shielding modes by adjusting the interlayer spacing. Simulation results demonstrate pronounced differences in the reflection characteristics and radiation intensity of the tag under the two operating modes at 915 MHz. Experimental validation further confirms the effectiveness of the system in mitigating interference and ensuring reliable tag identification in multi-tag scenarios. The design is compact, energy-efficient, and cost-effective, supporting scalable applications in smart retail and automated inventory management.

This study suggests a coin-sized (10 × 8 × 0.64 mm³) millimetre-wave antenna that simultaneously resonates at 28 GHz and 38 GHz and is supported by a machine-learning surrogate for near-instant impedance evaluation. Realised on Rogers 6010 LM laminate (ε_r = 10.2), the radiator maintains |S₁₁| ≤ -10 dB across 26.5-29.9 GHz and 37.2-39.7 GHz while providing peak gains of 3.8 dBi and 4.1 dBi in the lower and upper bands, respectively. A design-of-experiments sweep, comprising 330 full-wave simulations, generated the training corpus for a random-forest regression model. The surrogate predicts frequency-resolved |S₁₁| with a mean-absolute error below 0.7 dB and coefficients of determination of 0.93 at 28 GHz and 0.84 at 38 GHz. The evaluation time is reduced from approximately 155 s per full-wave electromagnetic simulation to 0.1 s per surrogate query, enabling real-time design exploration. Eight-fold cross-validation confirms model stability, while feature-importance analysis identifies the geometric parameters most influential to dual-band matching. The learning-guided workflow therefore offers a fast and reliable alternative to exhaustive simulation, accelerating the optimisation of compact mmWave antennas for instrumentation, sensing, and future front-end modules.

This study addresses the challenge of detecting Autism Spectrum Disorder (ASD) in children, where clinical diagnostic scales used in practice suffer from subjectivity and high costs. Eye tracking (ET), as a non-contact sensing technology, offers the potential for objective ASD recognition. However, existing studies often use specially crafted visual stimuli, making them less reproducible, or rely on the construction of handcrafted features. Deep learning methods allow us to build more efficient models, but only a few studies simultaneously focused on visual behaviors of ASD in both temporal and spatial dimensions, and many studies compressed the temporal dimension, potentially losing valuable information. To address these limitations, this study employed a relatively lenient visual stimulus selection criterion to collect ET data of ASD in social scenes, enabling analyses to be conducted both temporally and spatially. Findings indicate that the spatial attention distribution of ASD is more dispersed, and gaze trajectories are more unstable in the temporal dimension. We also observed that children with ASD exhibit slower responses in gaze-following scenarios. Additionally, data loss emerges as an effective feature for ASD identification. We proposed an SP-Inception-Transformer network based on CNN and Transformer encoder architecture, which can simultaneously learn temporal and spatial features. It utilized raw eye-tracking data to prevent information loss, and employed Inception and Embedding to enhance the performance. Compared to benchmark methods, our model demonstrated superior results in accuracy (0.886), AUC (0.8972), recall (0.82), precision (0.95), and F1 score (0.8719).

In this paper, a novel compact dual open-sleeve multiband monopole omnidirectional antenna specifically designed for coal mine communication is proposed. Its core innovation lies in the structural optimization that enables multiband operation across a wide frequency range. To adapt to the confined mine tunnel environment, the antenna employs an ultra-small diameter design, which poses significant challenges for impedance matching below 1 GHz. Additionally, the substantial electrical size disparity between the sub-1 GHz and above-5 GHz bands further complicates multiband matching. The proposed open-sleeve monopole antenna consists of top and bottom dual open-sleeve structures along with resistive loads. Four length-adjustable thin copper columns replace the conventional sleeve, forming an open-sleeve structure. Through coordinated tuning of the two longest columns in the bottom open-sleeve structure together with the resistor loads, the antenna achieves favorable impedance matching in the low-frequency band (0.515-0.845 GHz). Furthermore, by adjusting the dimensions of the second-longest and shortest columns in the bottom open-sleeve, the antenna covers the 1.370-1.485 GHz and 4.660-6.000 GHz bands, respectively, while tuning the central monopole enables matching in the 2.210-2.525 GHz band. Ultimately, through independent adjustment of the four bottom column lengths and coordinated optimization of the resistor loads, the antenna effectively operates in four bands: 0.515-0.845 GHz, 1.370-1.485 GHz, 2.210-2.525 GHz, and 4.660-6.000 GHz, with the ratio between the lowest and highest operating frequencies reaching 10:1. Simultaneously, the top open-sleeve structure enhances the antenna's gain in the low-frequency band. Measured results show good agreement with simulation, demonstrating a gain of 1.21-4.59 dBi and radiation efficiency of 44%-77.7%. Moreover, the antenna exhibits omnidirectional radiation characteristics. This antenna shows potential for coal mine communication applications and also supports WLAN (2.4/5.2/5.8 GHz), WiMAX (2.3/5.8 GHz), and 5G NR (n5/n12/n28/n71/n79).

This article proposes a novel polarization-reconfigurable metasurface converter with multi-functional operation capabilities for flexible polarization manipulation of electromagnetic waves. By integrating PIN diodes into a strategically designed unit cell, the converter achieves dynamic switching among all fundamental polarization conversion modes, including linear-to-linear (co- and cross-polarization), circular-to-circular (co- and cross-polarization), linear to circular polarization (LP-CP), and circular to linear polarization (CP-LP) conversions under both linearly and circularly polarized incidence. When the diodes are switched ON, the structure performs linear-to-cross-linear polarization conversion in the 9.5-16.4 GHz band and circular-to-co-circular polarization conversion in the 9.3-16.6 GHz band. Dual-band LP-CP and CP-LP conversions are attained in the 8.0-9.3/16.6-17.7 GHz and 8.1-9.4/16.8-17.9 GHz bands, respectively. When the diodes are OFF, the converter maintains co-polarized reflection under linearly polarized (LP) wave incidence, while reversing the handedness of the incident circularly polarized (CP) wave. Both full-wave simulations and experimental measurements demonstrate consistent performance across a broad bandwidth. This work provides a versatile and efficient solution for modern wireless communication and radar systems requiring adaptive polarization control.

To enhance the disturbance rejection capability and robust stability of PMSM under time-varying disturbances, an improved super-twisting higher-order sliding mode active disturbance rejection cascade control strategy is proposed. Firstly, a second-order mathematical model of the PMSM speed-current dual-loop system is established. Secondly, to address the oscillation issues caused by differentiation of the reference speed in conventional linear error feedback control, a composite sliding mode error feedback control law is designed by integrating the fast super-twisting (FST) algorithm and the fast non-singular terminal sliding mode control (FNFTSMC) method. The control law effectively suppresses system chattering and improves dynamic response. Meanwhile, an improved extended state observer (IESO) is constructed based on deviation control theory, which enhances real-time compensation of the cascade controller by optimizing convergence speed and disturbance estimation accuracy. Finally, hardware-in-the-loop (HIL) simulation results on an RT-LAB platform demonstrate that the proposed method outperforms traditional strategies in both dynamic performance and disturbance rejection, providing a viable solution for high-performance PMSM drive applications.

This paper presents a design method for circularly polarized metasurface antennas by integrating waveguide-fed metasurfaces with optical holography principles. Two interleaved linear slot elements on the metasurface top layer are excited by a reference wave from the feed, generating a circularly polarized beam. Simply adjusting the position of each slot element steers the beam in the desired direction. To enhance gain, metal vias are added around the antenna perimeter, reducing reference wave leakage. To validate this method, two 24 GHz circularly polarized holographic metasurfaces were simulated and experimentally characterized. Measurements show a 1.23 dB gain enhancement in the metasurface antenna with metal vias. Simulated and measured results validate the antenna's performance. This approach yields compact, low-profile antennas without requiring a separate feed network. Furthermore, the structure can be extended to create reconfigurable circularly polarized antennas, demonstrating significant potential in this field.

Ultrashort pulse semiconductor lasers represent a groundbreaking advancement in photonics by simultaneously overcoming the fundamental constraints of temporal duration, spatial confinement, and energy efficiency. These triple breakthroughs enable unprecedented applications in ultrafast spectroscopy, high-density optical storage, optical atomic clocks, photonic computing, and minimally invasive biomedicine, establishing a new paradigm for precision light-matter interaction in both scientific and industrial domains. This paper analyzes the principle and cutting-edge research progress of ultrashort pulse semiconductor lasers, discusses the implementation difficulties and optimization methods in integrated design, and looks forward to the challenges and future development trends.

This paper presents a reconfigurable multilayer graphene antenna for terahertz sensing, machine learning-based frequency and bandwidth estimation. The antenna utilizes the tunable electromagnetic properties of graphene, enabling dynamic reconfiguration of the resonant frequency and bandwidth. By adjusting key physical parameters including chemical potential, relaxation time, and temperatur, the antenna achieves frequency tuning from 1.542 THz to 1.562 THz, with an improved return loss reaching -30.8 dB and a bandwidth range from 91 GHz to 96 GHz. Furthermore, the resonance frequency and bandwidth are predicted using machine learning algorithms, including Random Forest and XGBoost, with results that closely match simulation data. These results highlight the potential of the proposed structure not only for adaptive communication systems but also for terahertz sensing platforms requiring frequency agility and environmental responsiveness.

A hybrid machine-learning-based optimization method is proposed for quick optimization of antenna shape design. The hybrid optimization method combines self-supervised learning and transfer learning. The application of self-supervised learning avoids the requirement to obtain labeled simulation data for electromagnetic samples, thereby reducing the difficulty of sample construction. The introduction of transfer learning further improves the sample utilization and optimizes efficiency in electromagnetic tasks. The proposed method enables rapid and high-degree-of-freedom optimization of antennas. To validate its effectiveness, a reflectarray antenna design incorporating distinct elements is employed as a case study. Simulation results indicate that the designed antenna exhibits a realized gain of 26.3 dBi and 46% aperture efficiency at the center frequency, and each element has a highly flexible independent structural design. During the optimization process, the proposed hybrid method demonstrates higher optimization efficiency than traditional methods, while significantly reducing sample construction time.

Quantum repeaters are essential for long-distance quantum communication, surmounting challenges like signal attenuation and decoherence. Nonetheless, current quantum repeater networks are constrained by static cutoff times for low-fidelity connections, suboptimal resource allocation, and the absence of quantum-classical integration. This paper introduces a hybrid quantum-classical method to tackle these issues by employing dynamic cutoff times contingent upon real-time fidelity decay and decoherence rates. Markov Decision Process (MDP) is used to characterize the system with the aim to optimize the entanglement generation processes, waiting and swapping. In this study, the objective is to reduce the time which is needed to realize end-to-end entanglement while fulfilling the requirements of classical channel capacity. To manage constraints such as classical user demands, quantum memory limits, and network congestion, Lagrangian optimization has been applied. The combined approach improves the use of both classical resources and quantum, providing a simplified solution that is adaptable to different users needs and different network conditions. The effectiveness of the model is tested via simulations processes, along with the mathematical process. This demonstrated important gains in fidelity preservation, resource efficiency, and latency minimization compared to the state-of-the-art traditional methods. This study makes a valuable contribution tackling the development of quantum networks, providing a rigid establishment to build a quantum capable for internet to support the security in distributed quantum computing and global communications.

This paper proposes a stacked slotted microstrip antenna (MSA) using multiple meta-surfaces that offers high gain and stable radiation patterns for 5G applications. A metal plated suspended MSA (SMSA) in air is designed to enhance gain and band width (BW). However, impedance becomes inductive and cross-polarization level (CPL) increases with increase in probe feed length. To decrease the inductive impedance and increase the capacitance, a slot in SMSA is etched. A parasitic patch with meta-surfaces on a superstrate is placed above the slotted SMSA and a rectangular ring around the slotted MSA is designed to increase the inductance. To compensate it, substrate height is decreased. The decrease in probe feed length/substrate height, decreases the CPL. Parasitic patch, rectangular ring around slotted SMSA and meta-surfaces, electro-magnetically couple with SMSA and enhance the BW of antenna. The low-profile (0.979λ₀ × 1.03λ₀ × 0.064λ₀, λ₀ - wavelength in free-space at 3.3 GHz) antenna offers peak gain of 9.8 dBi, antenna efficiency > 80%; SLL and CPL are < -22 dB; and the gain variation is < 0.5 dB over the 3.3-3.6 GHz frequency band for 5G application. The substrate height of the proposed novel structure is 2.5 times less than SMSA, and it offers an improvement of 8.1 dB in CPL as compared to SMSA.

Frequency-Selective Surfaces (FSSs) are structures designed to selectively transmit or reflect electromagnetic waves, making them essential for applications requiring precise control over frequency bands and wave propagation characteristics. However, traditional FSS designs face challenges such as fixed geometries, limited scalability, and poor bandwidth efficiency, often requiring compromises between size reduction and performance. To address these limitations, this work introduces the use of Stepped Impedance Resonators (SIRs) to synthesize miniaturized FSS structures with four-legged elements (FLEs). By combining transmission line theory, SIR equations, and parallel coplanar stripline models, an innovative synthesis method is proposed, enabling precise control over spurious frequencies and resulting in a 54% reduction in unit-cell size without sacrificing performance. This approach significantly enhances the feasibility of compact FSS applications. To further improve performance, an arrow-bending technique was introduced to reduce the coupling between adjacent cells, yielding a 30% improvement in isolation. Three distinct surface designs have been fabricated and tested under both normal incidence and oblique angles for TE and TM modes. These designs include the SIR-based FSS cell, an enhanced design featuring arrow bending, and a reverse arrow formation intended to reduce edge effects between adjacent cells. Additionally, measurements demonstrate excellent performance stability, with tolerance maintained for incident angles up to 60°. Experimental validation confirms effective blocking at 10 GHz and highlights the robustness of the design across varying incident angles. Prototypes fabricated from the miniaturized FSS elements show excellent agreement with simulations, underscoring the potential of this method for advanced applications in communications, radar, and electromagnetic shielding.

In this paper, the dielectric constant distribution of concrete was determined, which is consistent with the experimental values, and the complex dielectric constants obtained were evaluated. Numerical results are given by resulting complex dielectric constant distributions of four types, the time response waveforms and frequency spectra of a composite dispersive medium consisting of concrete using these dielectric constant distributions, and the time response waveforms and frequency spectra separated by each reflection component. A fast inversion of the Laplace transform method was used for the numerical analysis. Consequently, we were able to clarify the dielectric constant distribution suitable for the analysis by using these time response waveforms and frequency spectra.