arXiv subjects

Liangyu Deng

Publications and source records attributed to Liangyu Deng.

4 recordsLinked to original sources

arXiv2026

Defects encode high-dimensional topological information

In polarization fields, Stokes skyrmions are continuous vectorial textures that encode integer-valued topological invariants across real space, enabling robust optical information encoding under complex perturbations. This topological resilience, however, fails when singular points occur where the Stokes vector has no unique limiting value, placing a fundamental constraint on skyrmion-based information manipulation. Here, we show, paradoxically, that the very defects that destroy conventional resilience can become the carriers of topological information. We introduce the resulting structures as Stokes defect skyrmions, in which singular Stokes responses constitute measurable topological degrees of freedom with theoretically minimal size. We design and realize one class of them using all-dielectric metasurfaces that combine arbitrarily controlled distinguished fast-axis singularities with customized retardance profiles. The resulting fields are then described by high-dimensional integer-valued topological tuples, providing theoretically unbounded information capacity at the nanoscale. As a proof-of-concept demonstration, selected tuple components are mapped to represent predefined alphabetic symbols, realizing controlled high-dimensional information representation within a single optical field. Our results establish Stokes defects as functional units for higher-dimensional topological encoding, expanding the role of defects from failure points to engineerable carriers of optical information.

physics.optics↗

arXiv2026

Integrated photonic computing: towards high-dimensional information processing

The rapid growth of artificial intelligence, coupled with the slowing of Moore's law, is straining computing infrastructure, as CMOS electronics face inherent limits in bandwidth, energy efficiency, and parallelism. Integrated photonic computing encodes and processes information using the phase, amplitude, spatial modes, wavelength channels, and polarisation of guided optical fields, offering a scalable and energy-efficient route beyond charge-based signalling. Here, we review on-chip photonic computing, emphasising the progression from low-dimensional to high-dimensional architectures. At the foundational level, low-dimensional approaches manipulate the phase and amplitude of guided light through Mach-Zehnder interferometers, diffractive structures, microring resonators, and absorptive elements, forming a programmable basis for optical matrix-vector multiplication. Crucially, high-dimensional architectures exploit spatial modes and wavelength channels to carry multiple independent data streams through a single waveguide, achieving higher throughput with moderate hardware overhead. Practical deployment, however, demands more than device innovation. We examine how system-level techniques, from time-wavelength interleaving to hardware-aware training, address energy efficiency, precision, and algorithm-hardware co-design. Five challenges nevertheless remain: electro-optic conversion efficiency, computing parallelism, spatial integration, reconfigurability, and robustness. We highlight emerging topological structures, such as optical skyrmions, as a promising route to fault-tolerant, topologically protected encoding that exploits the largely untapped polarisation degree of freedom. We argue that, by embracing the higher dimensionality of light, photonic computing can offer not merely an incremental improvement but a new paradigm for high-performance, energy-efficient information processing.

physics.optics↗

arXiv2026

Drop-on-demand printed negative dielectric anisotropy liquid crystal droplets for adaptive complex beam manipulation and assessment

Adaptive manipulation of vectorial optical fields are important for optical metrology, imaging, and structured light related applications, yet existing approaches often rely on bulky or sequentially operated systems. Here we demonstrate an inkjet-printed negative dielectric anisotropy nematic liquid crystal droplet platform that unifies adaptive complex beam generation and full vectorial optical field sensing within a single printed architecture. For complex beam generation, voltage-driven director reconfiguration in the droplets produces tunable birefringence and wavelength-dependent polarization textures, including skyrmionic like optical fields. For adaptive full vectorial optical field sensing, the same droplet array enables spectral and polarization retrieval through wavelength-dependent intensity patterns and division-of-wavefront polarimetry, while also functioning as a microlens array for Shack Hartmann wavefront sensing to reconstruct phase. These results establish negative dielectric anisotropy liquid crystal droplets as a scalable soft-matter photonic system for adaptive beam manipulation and multidimensional optical field characterization.

physics.optics↗

arXiv2026

Unsupervised dimensionality reduction of polarimetric data for pixel-wise pathological tissue differentiation

Extracellular matrix (ECM) constitutes a key basement structure to human organisms by acting as a complex network of large proteins and carbohydrates that provide structural support to surrounding cells. Remodeling in the extracellular matrix's structural fibers leads to insight into the development of diseases such as cancer, fibrosis and carcinoma. While standard tissues visualization in the ECM involves multiple lengthy histopathological staining protocols, Mueller matrix-based polarimetry provides label-free tissue slices' microstructural information and optical properties. This work aims to identify three types of fiber tissues commonly found in the ECM of gastrointestinal tissue specimens by analyzing their polarization properties. To address decomposition methods' reliance on restrictive hypotheses and inability with an individual polarization-based parameter to determine the nature of a given biological tissue; this study employs Uniform Manifold Approximation and Projection (UMAP) method to offer greater discriminative power and flexibility. Subsequently, polarization-based features will be extracted and compared between fiber regions statistically to discern potential diagnostic differences. By providing colorized images, this work aims to demonstrate the feasibility of distinguishing different fibers with polarization approach, offering insights for future clinical development while complementing existing staining methods for pathological tissue specimens.

physics.optics↗