arXiv subjects

Ding Xu

Publications and source records attributed to Ding Xu.

At least 19 recordsLinked to original sources

arXiv2026

Giant optical spin-orbit interactions in ferroelectric van der Waals waveguides

Optical spin-orbit interactions (SOI) link photonic spin to momentum, offering a route toward on-chip polarization control and beam steering. Nevertheless, achieving sufficient optical SOI and nonlinearities on sub-micrometer scales - a prerequisite for dense photonic integration - remains an outstanding challenge. Here, we show that highly birefringent van der Waals (vdW) waveguides provide an ideal, chip-compatible platform to address this limitation. We focus on the ferroelectric semiconductor NbOI2, which exhibits record optical nonlinearities and dielectric anisotropy. Using femtosecond optical microscopy, we image light propagation and harmonic conversion beyond the total internal reflection barrier over tens of micrometers in NbOI2 slab waveguides. We report giant optical spin-splitting through the optical spin Hall effect, which facilitates spatial separation of optical spin currents on sub-micrometer scales, in quantitative agreement with a microscopic light-matter interaction model. We further leverage optical spin-momentum locking to realize polarization-controlled waveguide steering. We generalize these observations across various vdW waveguides and empirically confirm a scaling law linking dielectric anisotropy to geometric spin-splitting. Our results establish highly anisotropic vdW waveguides as an ideal platform for densely integrated opto-spintronic technologies.

cond-mat.mtrl-sci↗

arXiv2026

On-demand steering of hyperbolic chiral polaritons

Control of light polarization and propagation in sub-wavelength architectures is foundational to nanophotonic technologies. A frontier direction is to leverage strong optical spin-orbit interactions to realize polarization-selective light steering, known as the photonic spin Hall effect. In this context, hyperbolic plasmon polaritons (HPPs) are of particular interest as they offer large optical spin-orbit coupling from strong confinement and dielectric anisotropy, as well as ray-like propagation. Despite theoretical predictions, however, the hyperbolic spin Hall effect in natural materials has remained elusive. Here, we demonstrate the hyperbolic spin Hall effect in the visible and near-infrared range in the natural hyperbolic van der Waals metal MoOCl2. Enabling this discovery is a novel far-field pump-probe microscope that facilitates the launching and imaging of HPPs with exceptional sensitivity through interference with a high-momentum reference field. This approach preserves excellent control over light polarization, overcoming a key barrier to polarization-selective interrogation of hyperbolic materials. We show that both hyperbolic and surface plasmons in MoOCl2 display chiral fields, and that their propagation direction can be completely switched upon light helicity reversal. Our results demonstrate on-demand steering of chiral plasmons, firmly establishing natural hyperbolic materials as ideal components for reconfigurable nanophotonics and chiral light-matter coupling.

cond-mat.mtrl-sci↗

arXiv2026

Multiscale simulations guided advances for all-optical phase-change waveguides

Photonic computing using chalcogenide phase-change materials (PCMs) is under active development for energy-efficient artificial intelligence (AI) applications. A key requirement is to enable as many optically programmable levels per device as possible, while maintaining relatively low optical loss. In this work, we carry out multiscale simulations using density functional theory and finite-difference time-domain methods, proposing a "the shorter the better" strategy to optimize the performance of Sb2Te photonic waveguide devices. Our subsequent experimental characterizations of Sb2Te thin films and optical device measurements fully verify our theoretical predictions. In particular, we reveal the unconventional optical properties of metastable crystalline Sb2Te, and utilize these features for device design, yielding a simultaneous improvement in both the programming window and the optical loss. Overall, an optical programming precision exceeding 7-bit is achieved using a single waveguide cell, setting a new record for all-optical phase-change memory devices. Our work serves as a compelling example of computational material design, which demonstrates the predictive power of multiscale simulations in guiding the design of phase-change photonic devices for enhanced performance.

cond-mat.mtrl-sci↗

arXiv2026

Hydrodynamic Modeling of Odd Nematic Elasticity in Liquid Crystals

There is a recent interest in studying odd elasticity in soft solids. Current focus has been on simple solids. However, many soft solids are structured and can exhibit nematic elasticity or viscoelasticity. Here we generalize the concept of odd elasticity to nematic elasticity. By rewriting the governing equation for two-dimensional nematic liquid crystals (LCs) in terms of complex Ginzburg--Landau equation, we propose an odd nematic elastic term and its stress term in the hydrodynamic model of nematic LCs. The odd nematic elasticity can be physically interpreted as non-reciprocal interactions between neighboring directors. In odd nematics we find that domain walls become self-propelled and are accompanied by a bidirectional flow, and point defects can self-spin, develop a spiral pattern, and induce a vortical flow. Interactions of a pair of defects show rich dynamics that are distinct from those in active nematics. As such, we have developed an odd general elasticity, which can be further generalized to other viscoelastic materials, and proposed a novel way to manipulate topological defects in nematic LCs.

cond-mat.soft↗

arXiv2026

Low-loss phase-change material based programmable mode converter for photonic computing

Phase-change materials (PCMs)-based integrated photonic memory offers a viable pathway for the development of neuromorphic computing chip. The sizable optical contrast in the telecom band between amorphous and crystalline phases of PCM, in particular, Ge2Sb2Te5 (GST), is used for multilevel programming. However, the high extinction coefficient k of crystalline GST leads to high optical loss, posing a serious challenge for scaling up the device array for practical use. In this work, we focus on the atomic understanding and application of the so-called low-loss PCM, Sb2Se3, through multiscale simulations. First, we elucidate the bonding origin of the wavelength dependent optical properties of amorphous and crystalline Sb2Se3 via ab initio calculations. Given the suppressed k in the telecom band, we design a programable mode converter (PMC) waveguide device that utilizes only the contrast in refractive index n between amorphous and crystalline Sb2Se3 to encode multiple optical levels per waveguide device. The finite-difference time-domain simulations show that a single PMC device can achieve 5-bit programming precision (32 levels) via direct laser writing, and the photonic tensor core formed by the PMC array could possibly be scaled to 128*128. Finally, a thorough comparison between low-loss PCM and conventional PCM is provided.

cond-mat.mtrl-sci↗

arXiv2025

Tunable Narrowband Terahertz Radiation from van der Waals Ferroelectrics

The terahertz (THz) spectral range is central to high-speed communication, precision metrology, sensing technologies, and a range of fundamental scientific investigations. Achieving these capabilities in practical systems increasingly demands chip-scale integration of THz photonic components that are typically bulky. In this context, van der Waals (vdW) materials provide a unique platform for integrated nonlinear photonics in the visible and near-infrared regimes, and extending this framework into the THz domain would constitute a significant advance. Here, we report tunable, intense, and narrowband THz radiation from ferroelectric niobium oxyhalides. Through halogen substitution and alloying, we achieve continuous and precise control over the emission frequency from 3.1 to 5.8 THz. We show that the narrowband THz radiation is driven by phonons associated with the ferroelectric polarization. We further demonstrate dynamic and nonvolatile control of the polarity of the coherent THz wave with external electric field. This work demonstrates efficient narrowband THz emission from vdW ferroeletrics and provides microscopic insight into its origin, paving the way for on-chip THz technology for a broad range of applications.

physics.optics↗

arXiv2025

Effects of thermal annealing and film thickness on the structural and optical properties of indium-tin-oxide thin films

Indium-tin oxide (ITO) is a crucial functional layer for the optoelectronic applications, such as non-volatile color display thin films based on the ITO/phase-change material (PCM)/ITO/reflective metal multilayer structures on a silicon substrate. In addition to non-volatile color tuning by PCMs, thermally induced crystallization may alter the optical properties of ITO layers as well. But the potential change in color of the ITO layers is not considered so far. In this work, we investigate the structural and optical properties of ITO thin films via X-ray diffraction, spectroscopic ellipsometry and ultraviolet-visible spectrophotometry measurements. After thermal annealing at 250 {\deg}C, the ITO thin films of 15-100 nm get crystallized with strong changes in refractive index n and extinction coefficient k in the visible light range. However, for the 5-nm ITO thin film, crystallization is only observed after thermal annealing at 350 {\deg}C and the change in color is limited upon phase transition. We provide a colormap of the ITO/platinum/silicon structure in terms of the annealing temperature (150-350 {\deg}C) and ITO film thickness (5-100 nm). Our work suggests that the intrinsic change in colors of ITO layers should also be considered for the PCM-based reconfigurable display application.

physics.optics↗

arXiv2025

Flat band excitons in a three-dimensional supertwisted spiral transition metal dichalcogenide

A new frontier in van der Waals twistronics is the development of three-dimensional (3D) supertwisted materials, where each successive atomic layer rotates by the same angle. While two-dimensional (2D) moire systems have been extensively studied, the unique phenomena arising from 3D twistronics remain largely unexplored. In this work, we report the discovery of flat-band excitons in 3D supertwisted WS2, revealed by systematic photoluminescence (PL) experiments and electronic structure calculations. These excitons retain key features of 2D moire transition metal dichalcogenides (TMDs)-such as layer confinement, moire-driven localization, and strong Coulomb interactions-while also offering advantages in scalability and enhanced optical responses in three dimensions. Beyond the PL signatures reminiscent of 2D A excitons, we observe novel direct and indirect exciton emission uniquely tied to the supertwist geometry. Using generalized Bloch band theory and local density of states calculations that incorporate screw rotational symmetry, we uncovered the coexistence of 2D and 3D flatband gaps. These flat-band excitons serve as sensitive probes of the electronic properties of 3D supertwisted semiconductors and open new pathways for applications in quantum optoelectronics.

physics.app-ph↗

arXiv2025

Exciton Delocalization Suppresses Polariton Scattering

Exciton-polaritons (EPs) are part-light part-matter quasiparticles that combine large exciton-mediated nonlinearities with long-range coherence, ideal for energy harvesting and nonlinear optics. Optimizing EPs for these applications is predicated on a still-elusive understanding of how disorder affects their propagation and dephasing times. Here, using cutting-edge femtosecond spatiotemporal microscopy, we directly image EP propagation at light-like speeds in systems ranging from two-dimensional semiconductors to amorphous molecular films with systematically varied exciton-phonon coupling, exciton delocalization, and static disorder. Despite possessing similar EP dispersions, we observe dramatically different transport velocities and scattering times across systems. We establish a robust scaling law linking EP scattering to exciton transfer integral, demonstrating that polaritons based on materials with large exciton bandwidths are immune to disorder even for highly excitonic EPs. This observation cannot be deduced from the systems' linear optical properties, including EP dispersion and linewidth disorder. Our work highlights the critical and often-overlooked role of the matter component in dictating polariton properties, and provides precise guidelines for simultaneously optimizing EP propagation and nonlinearities.

physics.optics↗

arXiv2025

Observation of Coherent Ferron Emission and Propagation

Excitation of ordered quantum phases gives rise to collective modes and quasiparticles, as exemplified by spin waves and magnons emerging from magnetic order. Extending this paradigm to ferroelectric materials suggests the existence of polarization waves and their fundamental quanta, ferrons. Here, we report the generation and transport of polarization waves, i.e., coherent ferrons, in the van der Waals ferroelectric material NbOI2. Upon excitation by a short laser pulse, the polarization wave emits intense and narrow-band terahertz (THz) radiation at the ferroelectric transverse optical phonon frequency, modulates the ferroelectric order parameter, and propagates uniaxially along the polar axis at hypersonic velocities of ~105 m/s. These long-lived, uniaxial, and dipole-carrying polarization waves may find applications in narrow-band THz emission, ferronic information processing, and coherent electric control.

cond-mat.mtrl-sci↗

arXiv2025

FreCT: Frequency-augmented Convolutional Transformer for Robust Time Series Anomaly Detection

Time series anomaly detection is critical for system monitoring and risk identification, across various domains, such as finance and healthcare. However, for most reconstruction-based approaches, detecting anomalies remains a challenge due to the complexity of sequential patterns in time series data. On the one hand, reconstruction-based techniques are susceptible to computational deviation stemming from anomalies, which can lead to impure representations of normal sequence patterns. On the other hand, they often focus on the time-domain dependencies of time series, while ignoring the alignment of frequency information beyond the time domain. To address these challenges, we propose a novel Frequency-augmented Convolutional Transformer (FreCT). FreCT utilizes patch operations to generate contrastive views and employs an improved Transformer architecture integrated with a convolution module to capture long-term dependencies while preserving local topology information. The introduced frequency analysis based on Fourier transformation could enhance the model's ability to capture crucial characteristics beyond the time domain. To protect the training quality from anomalies and improve the robustness, FreCT deploys stop-gradient Kullback-Leibler (KL) divergence and absolute error to optimize consistency information in both time and frequency domains. Extensive experiments on four public datasets demonstrate that FreCT outperforms existing methods in identifying anomalies.

cs.LG↗

arXiv2025

Addressing Noise and Stochasticity in Fraud Detection for Service Networks

Fraud detection is crucial in social service networks to maintain user trust and improve service network security. Existing spectral graph-based methods address this challenge by leveraging different graph filters to capture signals with different frequencies in service networks. However, most graph filter-based methods struggle with deriving clean and discriminative graph signals. On the one hand, they overlook the noise in the information propagation process, resulting in degradation of filtering ability. On the other hand, they fail to discriminate the frequency-specific characteristics of graph signals, leading to distortion of signals fusion. To address these issues, we develop a novel spectral graph network based on information bottleneck theory (SGNN-IB) for fraud detection in service networks. SGNN-IB splits the original graph into homophilic and heterophilic subgraphs to better capture the signals at different frequencies. For the first limitation, SGNN-IB applies information bottleneck theory to extract key characteristics of encoded representations. For the second limitation, SGNN-IB introduces prototype learning to implement signal fusion, preserving the frequency-specific characteristics of signals. Extensive experiments on three real-world datasets demonstrate that SGNN-IB outperforms state-of-the-art fraud detection methods.

cs.LG↗

arXiv2025

Amorphous phase-change memory alloy with no resistance drift

Spontaneous structural relaxation is intrinsic to glassy materials due to their metastable nature. For phase-change materials (PCMs), the resultant temporal change in electrical resistance seriously hamper in-memory computing (IMC) applications. Here, we report an ab-initio-calculation-informed design of amorphous PCM composed of robust "molecule-like" motifs with minimal Peierls distortion, depriving the amorphous alloy of structural ingredients that would gradually evolve upon aging to entail resistance drift. We demonstrate amorphous CrTe3 thin films that display practically no resistance drift at any working temperature from -200 to 165 degree C. We achieve multilevel programming of CrTe3 through both step-wise crystallization and step-wise amorphization using a hybrid opto-electronic device at various temperatures. Moreover, the application potential of CrTe3 in neuromorphic computing is testified by its incorporation in a vehicle with automatic path-tracking function. Our work opens a new avenue to achieving IMC-requisite properties via judicious design of the composition and atomic-level structure of disordered PCM alloys.

cond-mat.mtrl-sci↗

arXiv2024

Spatiotemporal imaging of nonlinear optics in van der Waals waveguides

Van der Waals (vdW) semiconductors have emerged as promising platforms for efficient nonlinear optical conversion, including harmonic and entangled photon generation. Although major efforts are devoted to integrating vdW materials in nanoscale waveguides for miniaturization, the realization of efficient, phase-matched conversion in these platforms remains challenging. To address this challenge, we develop a far-field ultrafast imaging method to track the propagation of both fundamental and harmonic waves within vdW waveguides with extreme spatiotemporal resolution. Our approach allows systematic optimization of nonlinear conversion by determining the phase-matching angles, mode profiles, and losses in waveguides without a priori knowledge of material properties. We focus on light propagation in slab waveguides of rhombohedral-stacked MoS2, an emerging vdW semiconductor with giant nonlinear susceptibility. Our results reveal that these waveguides support birefringent phase-matching, demonstrating the material's potential for efficient on-chip nonlinear optics. This work establishes spatiotemporal imaging of light propagation in waveguides as an incisive and general method to identify new materials and architectures for efficient nonlinear nanophotonics.

cond-mat.mtrl-sci↗

arXiv2024

Event USKT : U-State Space Model in Knowledge Transfer for Event Cameras

Event cameras, as an emerging imaging technology, offer distinct advantages over traditional RGB cameras, including reduced energy consumption and higher frame rates. However, the limited quantity of available event data presents a significant challenge, hindering their broader development. To alleviate this issue, we introduce a tailored U-shaped State Space Model Knowledge Transfer (USKT) framework for Event-to-RGB knowledge transfer. This framework generates inputs compatible with RGB frames, enabling event data to effectively reuse pre-trained RGB models and achieve competitive performance with minimal parameter tuning. Within the USKT architecture, we also propose a bidirectional reverse state space model. Unlike conventional bidirectional scanning mechanisms, the proposed Bidirectional Reverse State Space Model (BiR-SSM) leverages a shared weight strategy, which facilitates efficient modeling while conserving computational resources. In terms of effectiveness, integrating USKT with ResNet50 as the backbone improves model performance by 0.95%, 3.57%, and 2.9% on DVS128 Gesture, N-Caltech101, and CIFAR-10-DVS datasets, respectively, underscoring USKT's adaptability and effectiveness. The code will be made available upon acceptance.

cs.CV↗

arXiv2024

Order metrics of jammed solids: Structures, hyperuniformity, and implications for ultra-stable glasses

Due to the lack of long-range order, it remains challenging to characterize the structure of disordered solids and understand the nature of the glass transition. Here we propose a new structural order parameter by taking into account multiple rotational symmetries. By studying its statistics for two-dimensional disordered packings of hard particles along the jamming transition line, we observe the evolution from disordered-particle-rich states to ordered-particle-rich states with the increase of packing fraction, together with the unusual non-monotonic change of the degree of hyperuniformity. At the high packing fraction end of the jamming transition line, the packings are mostly composed of ordered particles and are nearly hyperuniform beyond a finite length. Our work links the local order fluctuations to the thermodynamic stability and density fluctuations of disordered solids. Taking advantage of the order parameter, we propose the structural characteristic of ultra-stable glasses: Although globally disordered evaluated by any single symmetry, they are rich of ordered particles and effectively `globally ordered' with crystal-like density fluctuations.

cond-mat.soft↗

arXiv2024

When NOMA Meets AIGC: Enhanced Wireless Federated Learning

Wireless federated learning (WFL) enables devices to collaboratively train a global model via local model training, uploading and aggregating. However, WFL faces the data scarcity/heterogeneity problem (i.e., data are limited and unevenly distributed among devices) that degrades the learning performance. In this regard, artificial intelligence generated content (AIGC) can synthesize various types of data to compensate for the insufficient local data. Nevertheless, downloading synthetic data or uploading local models iteratively takes a lot of time, especially for a large amount of devices. To address this issue, we propose to leverage non-orthogonal multiple access (NOMA) to achieve efficient synthetic data and local model transmission. This paper is the first to combine AIGC and NOMA with WFL to maximally enhance the learning performance. For the proposed NOMA+AIGC-enhanced WFL, the problem of jointly optimizing the synthetic data distribution, two-way communication and computation resource allocation to minimize the global learning error is investigated. The problem belongs to NP-hard mixed integer nonlinear programming, whose optimal solution is intractable to find. We first employ the block coordinate descent method to decouple the complicated-coupled variables, and then resort to our analytical method to derive an efficient low-complexity local optimal solution with partial closed-form results. Extensive simulations validate the superiority of the proposed scheme compared to the existing and benchmark schemes such as the frequency/time division multiple access based AIGC-enhanced schemes.

eess.SP↗

arXiv2024

Fair Computation Offloading for RSMA-Assisted Mobile Edge Computing Networks

Rate splitting multiple access (RSMA) provides a flexible transmission framework that can be applied in mobile edge computing (MEC) systems. However, the research work on RSMA-assisted MEC systems is still at the infancy and many design issues remain unsolved, such as the MEC server and channel allocation problem in general multi-server and multi-channel scenarios as well as the user fairness issues. In this regard, we study an RSMA-assisted MEC system with multiple MEC servers, channels and devices, and consider the fairness among devices. A max-min fairness computation offloading problem to maximize the minimum computation offloading rate is investigated. Since the problem is difficult to solve optimally, we develop an efficient algorithm to obtain a suboptimal solution. Particularly, the time allocation and the computing frequency allocation are derived as closed-form functions of the transmit power allocation and the successive interference cancellation (SIC) decoding order, while the transmit power allocation and the SIC decoding order are jointly optimized via the alternating optimization method, the bisection search method and the successive convex approximation method. For the channel and MEC server allocation problem, we transform it into a hypergraph matching problem and solve it by matching theory. Simulation results demonstrate that the proposed RSMA-assisted MEC system outperforms current MEC systems under various system setups.

eess.SP↗