理学最新文献

Higher-order topological insulators (HOTIs) are unique materials hosting topologically protected states, whose dimensionality is at least by 2 lower than that of the bulk. Topological states in such insulators may be strongly confined in their corners which leads to considerable enhancement of nonlinear processes involving such states. However, all nonlinear HOTIs demonstrated so far were built on periodic bulk lattice materials. Here, we demonstrate the first nonlinear photonic HOTI with the fractal origin. Despite their fractional effective dimensionality, the HOTIs constructed here on two different types of the Sierpiński gasket waveguide arrays, may support topological corner states for unexpectedly wide range of coupling strengths, even in parameter regions where conventional HOTIs become trivial. We demonstrate thresholdless spatial solitons bifurcating from corner states in nonlinear fractal HOTIs and show that their localization can be efficiently controlled by the input beam power. We observe sharp differences in nonlinear light localization on outer and multiple inner corners and edges representative for these fractal materials. Our findings not only represent a new paradigm for nonlinear topological insulators, but also open new avenues for potential applications of fractal materials to control the light flow.

Optical phenomena always display some degree of partial coherence between their respective degrees of freedom. Partial coherence is of particular interest in multimodal systems, where classical and quantum correlations between spatial, polarization, and spectral degrees of freedom can lead to fascinating phenomena (e.g., entanglement) and be leveraged for advanced imaging and sensing modalities (e.g., in hyperspectral, polarization, and ghost imaging). Here, we present a universal method to analyze, process, and generate spatially partially coherent light in multimode systems by using self-configuring optical networks. Our method relies on cascaded self-configuring layers whose average power outputs are sequentially optimized. Once optimized, the network separates the input light into its mutually incoherent components, which is formally equivalent to a diagonalization of the input density matrix. We illustrate our method with numerical simulations of Mach-Zehnder interferometer arrays and show how this method can be used to perform partially coherent environmental light sensing, generation of multimode partially coherent light with arbitrary coherency matrices, and unscrambling of quantum optical mixtures. We provide guidelines for the experimental realization of this method, including the influence of losses, paving the way for self-configuring photonic devices that can automatically learn optimal modal representations of partially coherent light fields.

Parity-Time (PT) symmetry is an emerging concept in quantum mechanics where non-Hermitian Hamiltonians can exhibit real eigenvalues. Now, PT symmetric optical microresonators have been demonstrated to break the bandwidth-efficiency limit for nonlinear optical signal processing.

Neural stimulation and modulation at high spatial resolution are crucial for mediating neuronal signaling and plasticity, aiding in a better understanding of neuronal dysfunction and neurodegenerative diseases. However, developing a biocompatible and precisely controllable technique for accurate and effective stimulation and modulation of neurons at the subcellular level is highly challenging. Here, we report an optomechanical method for neural stimulation and modulation with subcellular precision using optically controlled bio-darts. The bio-dart is obtained from the tip of sunflower pollen grain and can generate transient pressure on the cell membrane with submicrometer spatial resolution when propelled by optical scattering force controlled with an optical fiber probe, which results in precision neural stimulation via precisely activation of membrane mechanosensitive ion channel. Importantly, controllable modulation of a single neuronal cell, even down to subcellular neuronal structures such as dendrites, axons, and soma, can be achieved. This bio-dart can also serve as a drug delivery tool for multifunctional neural stimulation and modulation. Remarkably, our optomechanical bio-darts can also be used for in vivo neural stimulation in larval zebrafish. This strategy provides a novel approach for neural stimulation and modulation with sub-cellular precision, paving the way for high-precision neuronal plasticity and neuromodulation.

Thermochromic coatings hold promise in reducing building energy consumption by dynamically regulating the heat gain of windows, which are often regarded as less energy-efficient components, across different seasons. Vanadium dioxide (VO₂) stands out as a versatile thermochromic material for smart windows owing to its reversible metal-to-insulator transition (MIT) alongside correlated structural and optical properties. In this review, we delve into recent advancements in the phase-change VO₂-based thermochromic coatings for smart windows, spanning from the macroscopic crystal level to the microscopic structural level (including elemental doping and micro/nano-engineering), as well as advances in controllable fabrication. It is notable that hybridizing functional elements/materials (e.g., W, Mo/SiO₂, TiN) with VO₂ in delicate structural designs (e.g., core-shell, optical cavity) brings new degrees of freedom for controlling the thermochromic properties, including the MIT temperature, luminous transmittance, solar-energy modulation ability and building-relevant multi-functionality. Additionally, we provide an overview of alternative chromogenic materials that could potentially complement or surpass the intrinsic limitations of VO₂. By examining the landscape of emerging materials, we aim to broaden the scope of possibilities for smart window technologies. We also offer insights into the current challenges and prospects of VO₂-based thermochromic smart windows, presenting a roadmap for advancing this field towards enhanced energy efficiency and sustainable building design. In summary, this review innovatively categorizes doping strategies and corresponding effects of VO₂, underscores their crucial NIR-energy modulation ability for smart windows, pioneers a theoretical analysis of inverse core-shell structures, prioritizes practical engineering strategies for solar modulation in VO₂ films, and summarizes complementary chromogenic materials, thus ultimately advancing VO₂-based smart window technologies with a fresh perspective.

Natural selection has driven arthropods to evolve fantastic natural compound eyes (NCEs) with a unique anatomical structure, providing a promising blueprint for artificial compound eyes (ACEs) to achieve static and dynamic perceptions in complex environments. Specifically, each NCE utilises an array of ommatidia, the imaging units, distributed on a curved surface to enable abundant merits. This has inspired the development of many ACEs using various microlens arrays, but the reported ACEs have limited performances in static imaging and motion detection. Particularly, it is challenging to mimic the apposition modality to effectively transmit light rays collected by many microlenses on a curved surface to a flat imaging sensor chip while preserving their spatial relationships without interference. In this study, we integrate 271 lensed polymer optical fibres into a dome-like structure to faithfully mimic the structure of NCE. Our ACE has several parameters comparable to the NCEs: 271 ommatidia versus 272 for bark beetles, and 180^o field of view (FOV) versus 150–180^o FOV for most arthropods. In addition, our ACE outperforms the typical NCEs by ~100 times in dynamic response: 31.3 kHz versus 205 Hz for Glossina morsitans. Compared with other reported ACEs, our ACE enables real-time, 180^o panoramic direct imaging and depth estimation within its nearly infinite depth of field. Moreover, our ACE can respond to an angular motion up to 5.6×10⁶ deg/s with the ability to identify translation and rotation, making it suitable for applications to capture high-speed objects, such as surveillance, unmanned aerial/ground vehicles, and virtual reality.

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.