Nonlinear nanostructured surfaces provide a paradigm shift in nonlinear optics with new ways to control and manipulate frequency conversion processes at the nanoscale, also offering novel opportunities for applications in photonics, chemistry, material science, and biosensing. Here, we develop a general approach to employ sharp resonances in metasurfaces originated from the physics of bound states in the continuum for both engineering and enhancing the nonlinear response. We study experimentally the third-harmonic generation from metasurfaces composed of symmetry-broken silicon meta-atoms and reveal that the harmonic generation intensity depends critically on the asymmetry parameter. We employ the concept of the critical coupling of light to the metasurface resonances to uncover the effect of radiative and nonradiative losses on the nonlinear conversion efficiency.
Rapid progress in the development of metamaterials and metaphotonics allowed bulky optical assemblies to be replaced with thin nanostructured films, often called metasurfaces, opening a broad range of novel and superior applications of flat optics to the generation, manipulation and detection of classical light. Recently, these developments started making headway in quantum photonics, where novel opportunities arose for the control of non-classical nature of light, including photon statistics, quantum state superposition, quantum entanglement and single-photon detection. In this Perspective, we review recent progress in the emerging field of quantum-photonics applications of metasurfaces, focusing on innovative and promising approaches to create, manipulate and detect non-classical light. Progress in the field of quantum-photonics applications of metasurfaces is reviewed. Cutting-edge research, including the development of optical chips supporting high-dimensional quantum entanglement and advanced quantum tomography, is summarized.
Adaptive optics is becoming a valuable tool for high resolution microscopy, providing correction for aberrations introduced by the refractive index structure of specimens. This is proving particularly promising for applications that require images from deep within biological tissue specimens. We review recent developments in adaptive microscopy, including methods and applications. A range of advances in different microscope modalities is covered and prospects for the future are discussed. Adaptive optics is used to improve image quality across a wide range of microscopy techniques. Martin Booth from the University of Oxford in the UK reviews how technologies such as deformable mirrors and spatial light modulators, which compensate for aberrations by locally controlling the wavefront of a light wave, are now improving the performance of multiphoton, confocal, widefield and super-resolution microscopes. The benefits of such improvements are especially appealing for images captured from within biological tissue (focal distances of tens to hundreds of micrometres), where low-order aberrations associated with smooth phase variations occur. One future challenge is the development of efficient measurement and correction schemes for higher-order phase variations.
The numerical aperture (NA) of a lens determines its ability to focus light and its resolving capability. Having a large NA is a very desirable quality for applications requiring small light-matter interaction volumes or large angular collections. Traditionally, a large NA lens based on light refraction requires precision bulk optics that ends up being expensive and is thus also a specialty item. In contrast, metasurfaces allow the lens designer to circumvent those issues producing high-NA lenses in an ultraflat fashion. However, so far, these have been limited to numerical apertures on the same order of magnitude as traditional optical components, with experimentally reported NA values of 0.99) and subwavelength thickness (∼λ/3), operating with unpolarized light at 715 nm. To demonstrate its imaging capability, the designed lens is applied in a confocal configuration to map color centers in subdiffractive diamond nanocrystals. This work, based on diffractive elements that can efficiently bend light at angles as large as 82°, represents a step beyond traditional optical elements and existing flat optics, circumventing the efficiency drop associated with the standard, phase mapping approach.
Optical techniques using developed laser and optical devices have made a profound impact on modern medicine, with "biomedical optics" becoming an emerging field. Sophisticated technologies have been developed in cancer nanomedicine, such as photothermal therapy and photodynamic therapy, among others. However, single-mode phototherapy cannot completely treat persistent tumors, with the challenges of relapse or metastasis remaining; therefore, combinatorial strategies are being developed. In this review, the role of light in cancer therapy and the challenges of phototherapy are discussed. The development of combinatorial strategies with other therapeutic methods, including chemotherapy, immunotherapy, gene therapy, and radiotherapy, is presented and future directions are further discussed. This review aims to highlight the significance of light in cancer therapy and discuss the combinatorial strategies that show promise in addressing the challenges of phototherapy.
D. Chang, James S. Douglas, A. González-Tudela
et al.
This Colloquium describes a new paradigm for creating strong quantum interactions of light and matter by way of single atoms and photons in nanoscopic lattices. Beyond the possibilities for quantitative improvements for familiar phenomena in atomic physics and quantum optics, there is a growing research community that is exploring novel quantum phases and phenomena that arise from atom-photon interactions in one- and two-dimensional nanophotonic lattices. Nanophotonic structures offer the intriguing possibility to control atom-photon interactions by engineering the medium properties through which they interact. An important aspect of these new research lines is that they have become possible only by pushing the state-of-the-art capabilities in nanophotonic device fabrication and by the integration of these capabilities into the realm of ultracold atoms. This Colloquium attempts to inform a broad physics community of the emerging opportunities in this new field on both theoretical and experimental fronts. The research is inherently multidisciplinary, spanning the fields of nanophotonics, atomic physics, quantum optics, and condensed matter physics.
The so‐called ‘flat optics’ that shape the amplitude and phase of light with high spatial resolution are presently receiving considerable attention. Numerous journal publications seemingly offer hope for great promises for ultra‐flat metalenses with high efficiency, high numerical aperture, broadband operation… We temperate the expectation by referring to the current status of metalenses against their historical background, assessing the technical and scientific challenges recently solved and critically identifying those that still stand in the way.
Monochromatic light can be characterized by its three fundamental properties: amplitude, phase, and polarization. In this work, we propose a versatile, transmission-mode all-dielectric metasurface platform that can independently manipulate the phase and amplitude for two orthogonal states of polarization in the visible frequency range. For proof-of-concept experimental demonstration, various single-layer metasurfaces composed of subwavelength-spaced titanium-dioxide nanopillars are designed, fabricated, and characterized to exhibit the ability of polarization-switchable multidimensional light-field manipulation, including polarization-switchable grayscale nanoprinting, nonuniform cylindrical lensing, and complex-amplitude holography. We envision the metasurface platform demonstrated here to open new possibilities toward creating compact multifunctional optical devices for applications in polarization optics, information encoding, optical data storage, and security.
Adaptive optics can be used to mitigate the effects of atmospheric turbulence on imaging systems, but the correction is only partial, and deconvolution is often required to improve the resolution. This results in entire optical/digital systems, which are traditionally designed sequentially, i.e. , the adaptive optics system is optimised first, and the restoration algorithms are designed a second time. Studies on optical/digital systems have shown that jointly optimizing the whole system is a better alternative. We propose to extend these co-design strategies to the design of an adaptive optics-assisted imaging system. We derive a simple criterion that takes into account the source properties and the entire optical/ digital system performance. To illustrate its interest, we use it to optimize the wavelength distribution between the wavefront sensor and the imaging camera. In addition, we explore the potential of using multiple imaging channels operating at different wavelengths as a means of making an imaging system robust to turbulence strength and source magnitude variations. Later, any parameter of the optical/digital system, if not the entire system itself, could be optimized this way.
Photonic integrated circuits have intrinsic merits of high integration, large bandwidth, and flexible design, which play an important role in optical communication systems for the interconnect. To increase the integration and routing of photonic circuits for manipulating the guide modes, we propose a simple and effective fiber compatible crossing waveguide to optimize the device layouts. To demonstrate the idea, we fabricated the device through optical lithography, and then optimized the processing parameters based on the analysis of image processing after fabrication, where the fabricated device shows an insertion loss lower than a maximum 1.0 dB with the crossing waveguides perpendicular to each other and operation wavelength from 1450 nm to 1630 nm for the operation of the E<sub>21</sub> and E<sub>11</sub> modes. The device offers the ability to manipulate guide modes without being affected by the waveguide crossing, which can provide a powerful way to form fiber compatible integrated photonic circuits.
Abstract A spectro-polarimetric imaging approach leverages optical rotatory dispersion in natural crystals to encode spectral information into polarization states. The system demonstrates effectiveness in laboratory and outdoor field experiments, showing potential for biological microscopy, machine vision, and remote sensing applications.
Abstract Marine vessels play a vital role in the global economy; however, their negative impact on the marine atmospheric environment is a growing concern. Quantifying marine vessel emissions is an essential prerequisite for controlling these emissions and improving the marine atmospheric environment. Optical imaging remote sensing is a vital technique for quantifying marine vessel emissions. However, the available imaging techniques have suffered from insufficient detection accuracy and inadequate spatiotemporal resolution. Herein, we propose a fast-hyperspectral imaging remote sensing technique that achieved precise imaging of nitrogen dioxide (NO2) and sulfur dioxide (SO2) from marine vessels. Several key techniques are developed, including the coaxial design of three camera systems (hyperspectral camera, visible camera, and multiwavelength filters) and a high-precision temperature control system for a spectrometer (20 °C ± 0.5 °C). Moreover, based on the variation of O4 within them, plumes are categorized as aerosol-present and aerosol-absent, with different air mass factor (AMF) calculation schemes developed accordingly. Multiwavelength filters combined with spectral analysis enable precise identification of the plume outline and a detailed observation of the trace gas distribution inside the plume emitted from marine vessels. In addition, we focuse on the emission characteristics of NO2 and SO2 from large ocean cargo ships and small offshore cargo ships. Although there are still many emerging issues, such as measurement of cross-sections of trace gases at different temperature, nighttime imaging, and greenhouse gas imaging, this study opens a gate for synergies in pollution and carbon reductions and the continuous improvement of the marine atmospheric environment.
Abstract The ultimate goal of understanding the structure of matter has spurred a constant search for composite particles, especially high-order correlated entities for nearly all forms of matter, from elementary particles, nuclei, and cold atoms, to condensed matter. So far, composite particles involving two or three constituent particles and their weak-coupling combinations have been experimentally studied, such as the Cooper pairs, excitons, trions, and bi-excitons in condensed matter physics, or diquarks, mesons, and di-mesons in quantum chromodynamics. Although genuine four-particle correlated entities have long been theorized in various materials, alternatively known as quadruplons (Rausch and Potthoff in New J. Phys. 18, 2016), quadrons (Quang et al. in Physica B 602, 2021), or quartets (Jiang et al. in Phys. Rev. B 95, 2017), the only closely related experimental evidence is the tetraquark observation at CERN (LHCb in Nat. Phys. 18, 751–754, 2022). In this article, we present for the first time the experimental evidence for the existence of a four-body entity in condensed matter, the quadruplon, involving two electrons and two holes in a monolayer of Molybdenum Ditelluride. Using the optical pump–probe technique, we discovered a series of new spectral features in addition to those of excitons and trions. Furthermore, we found that all these spectral features could be reproduced theoretically using transitions between the two-body and four-body complexes based on the Bethe–Salpeter equation. Interestingly, we found that the fourth-order irreducible cluster is necessary and sufficient for the new spectral features by using the corresponding cluster expansion technique. Thus, our experimental results combined with theoretical explanation provide strong evidence for the existence of a genuine four-particle entity, the quadruplon. In contrast to a bi-exciton which consists of two weakly interacting excitons, a quadruplon involves tightly bound four-particle entity without the presence of well-defined excitons. Our results could impact the understanding of the structure of materials in a wide range of physical systems and potentially lead to new photonic applications based on quadruplons.
The geometric phase in optics (GPIO) is directly associated with the polarization of light. We investigate the physical principles underlying the occurrence of the GPIO for a single-mode light beam propagating in a single-mode optical fiber wound into a circular helix configuration, with and without stress-induced birefringence. The effects of the curvature and torsion of the helical fiber on the rotation of the polarization vector and the associated GPIO are discussed. Analytic expressions are derived for the polarization vector and Stokes parameters for any initial polarization state of the light entering the helical fiber, as well as for the GPIO of the light as a function of helix arc-length. Additionally, the intensity of a superposition of the initial and final beams, which depends on the final GPIO, is derived. Furthermore, the relationship between the GPIO and the solid angle subtended by the tangent vector of the helix plotted on the Poincaré sphere is analyzed, and the effects of fluctuations of the parameters specifying the geometry and the material characteristics of the helical fiber on the GPIO are considered.
Gordon H. Y. Li, Christian R. Leefmans, James Williams
et al.
Abstract Rapid advancements in deep learning over the past decade have fueled an insatiable demand for efficient and scalable hardware. Photonics offers a promising solution by leveraging the unique properties of light. However, conventional neural network architectures, which typically require dense programmable connections, pose several practical challenges for photonic realizations. To overcome these limitations, we propose and experimentally demonstrate Photonic Neural Cellular Automata (PNCA) for photonic deep learning with sparse connectivity. PNCA harnesses the speed and interconnectivity of photonics, as well as the self-organizing nature of cellular automata through local interactions to achieve robust, reliable, and efficient processing. We utilize linear light interference and parametric nonlinear optics for all-optical computations in a time-multiplexed photonic network to experimentally perform self-organized image classification. We demonstrate binary (two-class) classification of images using as few as 3 programmable photonic parameters, achieving high experimental accuracy with the ability to also recognize out-of-distribution data. The proposed PNCA approach can be adapted to a wide range of existing photonic hardware and provides a compelling alternative to conventional photonic neural networks by maximizing the advantages of light-based computing whilst mitigating their practical challenges. Our results showcase the potential of PNCA in advancing photonic deep learning and highlights a path for next-generation photonic computers.
Abstract Quantum entanglement has emerged as a great resource for studying the interactions between molecules and radiation. We propose a new scheme of stimulated Raman scattering with entangled photons. A quantum ultrafast Raman spectroscopy is developed for condensed-phase molecules, to monitor the exciton populations and coherences. Analytic results are obtained, showing an entanglement-enabled time-frequency scale not attainable by classical light. The Raman signal presents an unprecedented selectivity of molecular correlation functions, as a result of the Hong-Ou-Mandel interference. Our work suggests a new paradigm of using an unconventional interferometer as part of spectroscopy, with the potential to unveil advanced information about complex materials.
Abstract Diagnostic pathology, historically dependent on visual scrutiny by experts, is essential for disease detection. Advances in digital pathology and developments in computer vision technology have led to the application of artificial intelligence (AI) in this field. Despite these advancements, the variability in pathologists’ subjective interpretations of diagnostic criteria can lead to inconsistent outcomes. To meet the need for precision in cancer therapies, there is an increasing demand for accurate pathological diagnoses. Consequently, traditional diagnostic pathology is evolving towards “next-generation diagnostic pathology”, prioritizing on the development of a multi-dimensional, intelligent diagnostic approach. Using nonlinear optical effects arising from the interaction of light with biological tissues, multiphoton microscopy (MPM) enables high-resolution label-free imaging of multiple intrinsic components across various human pathological tissues. AI-empowered MPM further improves the accuracy and efficiency of diagnosis, holding promise for providing auxiliary pathology diagnostic methods based on multiphoton diagnostic criteria. In this review, we systematically outline the applications of MPM in pathological diagnosis across various human diseases, and summarize common multiphoton diagnostic features. Moreover, we examine the significant role of AI in enhancing multiphoton pathological diagnosis, including aspects such as image preprocessing, refined differential diagnosis, and the prognostication of outcomes. We also discuss the challenges and perspectives faced by the integration of MPM and AI, encompassing equipment, datasets, analytical models, and integration into the existing clinical pathways. Finally, the review explores the synergy between AI and label-free MPM to forge novel diagnostic frameworks, aiming to accelerate the adoption and implementation of intelligent multiphoton pathology systems in clinical settings.
EditorialProf. Eric Mazur is a great influencer over and beyond the optics community. As a physicist, he is a pioneer of ultrafast optics and was one of the inventors of colliding-pulse mode-locked laser. As an educator, he not only gave talks to thousands, but also revolutionized teaching with his globally renowned methodology “Peer Instruction”. As a leader and entrepreneur, he co-founded several companies and was President of Optica (formerly the Optical Society) and currently is the Chair of the Optica Foundation. Here, Light: Science & Applications talked with Prof. Eric Mazur about his opinions on research, education and industry. The full interview video can be found in the Supplementary File.