The control of all of light's degrees of freedom and its harnessing for applications is captured by the emergent field of structured light. The modern toolkit includes external modulation of light with devices such as metasurfaces and spatial light modulators, their intra-cavity insertion for structured light directly at the source, and their deployment to engineer quantum structured light at the single photon and entangled state regimes. Historically, this control has involved linear optical elements, with nonlinear optics only recently coming to the fore. This has opened unprecedented functionality while revealing new paradigms for nonlinear optics beyond plane waves. In this review we look at the recent progress in structured light with nonlinear optics, covering the fundamentals and the powerful applications they are facilitating in both the classical and quantum domains.

With increasing demand for renewable energy, perovskite solar cells (PSCs) have emerged as a promising alternative due to their high efficiency and solution-based manufacturing processes. However, the fabrication of PSCs in ambient conditions, as opposed to inert environments, remains challenging due to environmental factors such as moisture and oxygen that degrade perovskite materials. Developing air-processed PSCs is therefore critical for reducing fabrication cost, simplifying manufacturing infrastructure, and enabling scalable production compatible with industrial processes. Moreover, air processing represents a key step toward realistic deployment, bridging the gap between laboratory demonstrations and commercial applications. This perspective discusses the progress of air-processed PSCs, highlights the environmental challenges related to stability and performance, and outlines potential strategies for future research, including precursor chemistry, solvent and additive engineering, and interface optimization. In addition, emerging scalable deposition techniques, automated platforms, and machine learning-assisted control are expected to accelerate device optimization and reproducibility. Despite remaining challenges, commercializing air-processed PSCs is increasingly viable, promising a sustainable and efficient approach for solar energy technology.

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.

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.

Periodic optical structures, such as diffraction gratings and numerous photonic crystals, are one of the staples of modern nanophotonics for the manipulation of electromagnetic radiation. The array of subwavelength dielectric rods is one of the simplest platforms, which, despite its simplicity exhibits extraordinary wave phenomena, such as diffraction anomalies and narrow reflective resonances. Despite the well-documented properties of infinite periodic systems, the behavior of these diffractive effects in systems incorporating a finite number of elements is studied to a far lesser extent. Here, we theoretically and numerically study the evolution of collective spectral features in finite arrays of dielectric rods. We develop an analytical model of light scattering by a finite array of circular rods based on the coupled dipoles approximation and analyze the spectral features of finite arrays within the developed model. Finally, we validate the results of the analytical model using full-wave numerical simulations.

Photonic crystals, often referred to as the ``semiconductors of light,'' have entered a new phase enabling exotic properties once exclusive to topological quantum matter such as topological insulators. While the development of the first three-dimensional (3D) photonic crystal marked the establishment of photonic crystals as an independent field, initial studies in topological photonic crystals focused mainly on one and two dimensions. Though a true photonic crystal counterpart of a 3D strong topological insulator remains elusive, significant progress has been made toward achieving 3D topological photonic crystals. Compared with their lower-dimensional counterparts, 3D topological photonic crystals reveal a richer variety of topological phases and surface manifestation, which enables more degrees of freedom for light manipulation. In this review, concentrating on the novel boundary states unique in 3D systems, we provide a brief survey of the 3D topological photonic crystals and recent advances in this field. We categorize and discuss various topological phases and associated phenomena observed in 3D photonic crystals, including both gapped and gapless phases. Additionally, we delve into some recent developments in this rapidly evolving area, including the realization of 3D topological phases through synthetic dimensions.

In this paper, we propose some suggestions for unsolved problems in classical and quantum electromagnetics. We aim to explain these problems in the simplest way possible. Some issues like the quantum computer may need a lot more work. The subject matter is interdisciplinary needing international collaboration in many different areas such as physics, math, engineering, and material science.

The fusion of electromagnetic (EM) waves and information theory in wireless and waveguide communication technologies has enjoyed a remarkable revival during the last few years. In particular, unlike traditional transceiver systems, the recently proposed information metasurface system directly links the controllable binary array sources with the scattered EM waves, making the combination of EM and information theories highly desirable and natural. Moreover, a traditional linear channel matrix cannot be directly used for such scattering reconfigurability enabled communication system, making the information characterization of such system a great challenge. In this paper, EM information characteristics of a direct digital modulation (DDM) system enabled by programmable information metasurface, also known as reconfigurable intelligent surface (RIS), are analyzed, in which RIS is used as a modulator of the illuminating field, while the scattered far-field amplitudes are measured and effectively treated as the received quantities. The posterior probability for a specific source coding pattern, conditioned over a given measured scattering fields, is obtained through the Bayesian analysis technique, from which the average mutual information (AMI) is obtained to estimate the RIS observation capability along any particular direction. The averaged receiver mutual information (ARMI) is then introduced to characterize the generated field correlation structures along different observation directions. Based on ARMI, the joint observation capability is also analyzed. Furthermore, the suggested techniques are employed in a noisy environment, and a code selection scheme is put forth to achieve efficient information transmission. The proposed configuration is validated through a simulated experiment. As a comprehensive evaluation of the system's performance, the channel capacity of the system is derived, and a set of relevant influencing factors are identified and analyzed from four different perspectives: 1) the observation direction, 2) the size of RIS, 3) potential joint observations in multiple directions, and 4) the noise level. The proposed method, together with the various related performance measure metrics introduced therein, are expected to provide the research community with guidelines for analyzing and designing the current and future RIS-based communication systems, which can also be extended to other aspects in the growing field of the EM information theory.

Compelling evidence suggests that the interaction between electromagnetic metasurfaces and deep learning gives rise to the proliferation of intelligent metasurfaces in the past decade. In general, deep learning offers a transformative force to reform the design and working style of metasurfaces. A majority of the inverse-design literature announce that, given a user-defined input, the pre-trained deep learning models can quickly output the metasurface candidates with high fidelity. However, they largely ignore an important fact, that is, the practical input is always semi-known. In this work, we introduce a generation-elimination network that is robust to semi-known input and information pollution. The network is composed of a generative network to generate a number of possible answers and then a discriminative network to eliminate suboptimal answers. We benchmark the feasibility via two scenes, the on-demand metasurface design of the reflection spectra and the far-field pattern. In the microwave experiment, we fabricated and measured the reconfigurable metasurfaces to automatically meet the semi-known beam steering requirement that widely exist in wireless communication. Our work for the first time answers the question of how to cope with semi-known input, which is ubiquitous in a panoply of real-world applications, such as imaging, sensing, and communication across noisy environment.