arXiv subjects

Xiaoxue Xu

Publications and source records attributed to Xiaoxue Xu.

At least 19 recordsLinked to original sources

arXiv2026

Mid-infrared reconfiguration of population flow in lanthanide nanocrystals

Converting mid-infrared (MIR) radiation to visible or near-infrared wavelengths is essential for imaging and sensing, yet achieving sensitive, low-power, and scalable detection remains challenging. Lanthanide nanocrystals provide an alternative through ratiometric luminescence but are typically constrained by Boltzmann statistics, which tie population distributions to lattice temperature and limit signal contrast. Here we show that MIR irradiation rebalances dissipative relaxation pathways, driving lanthanide emitters into a non-Boltzmann steady state that enables non-thermal control of population distributions. This allows emission behaviors inaccessible under thermal equilibrium. We exploit this regime to achieve linear MIR detection with respect to MIR power across 6.8 to 8.6 micrometers. The ratiometric response is intrinsically independent of the pump power, enabling operation at an ultralow excitation power of 10 uW, several orders of magnitude lower than conventional approaches. Using standard silicon photodetectors, we then demonstrate room-temperature MIR imaging with detection limits approaching 4 nW um-2. Our results establish lanthanide nanoparticles as an efficient platform for MIR conversion and sensing in nanophotonic systems.

physics.optics↗

arXiv2026

Self-powered InAs nanowire detector arrays for extended-SWIR spectrometry at room temperature

Spectral sensing in the extended shortwave infrared (e-SWIR) is important for molecular analysis, infrared imaging, and machine vision, motivating the development of compact spectrometers for broader applications. However, conventional commercial off-the-shelf spectrometers in this wavelength region are expensive and bulky due to their reliance on external dispersive optics/filters and/or cryogenic accessories. Other emerging computational spectrometers are based on Si and InGaAs photodetectors that remain focused on the visible and near-infrared, with few detector platforms operating in the e-SWIR regime that simultaneously provide broadband sensitivity, low-noise room-temperature operation, and diverse spectral signatures for accurate identification and reconstruction. Here, we report a room-temperature e-SWIR computational spectrometer based on InAs/InP core-shell nanowire photodetector arrays with geometry-encoded spectral responses. The detectors exhibit self-powered broadband photoresponse across the 1--3 $μ$m range, with responsivity up to 0.215 A W$^{-1}$, detectivity up to $1.6 \times 10^{9}$ cm Hz$^{1/2}$ W$^{-1}$, and microsecond response times. The excellent detector performance is leveraged to demonstrate filter-free spectral reconstruction using a compact multipixel photodetector array device. This enables high-accuracy molecular absorption spectrum reconstruction and hyperspectral imaging. Our results indicate that InAs nanowire arrays are a promising platform for compact computational spectrometry and imaging in the e-SWIR at room temperature.

physics.optics↗

arXiv2026

Facile hBN-hBN Interfacial Overlap Engineering for Enhanced Quantum Emitter Formation

Quantum emitters in two-dimensional materials, particularly hBN, are promising platforms for quantum technologies. However, achieving high-density emitters at predetermined locations while preserving optical quality remains challenging. Here, we introduce a facile, cost-effective double-layer all-dry transfer approach to deterministically create overlap regions between hBN flakes. These pre-defined capped regions exhibit a significantly enhanced emitter density, with up to a 15-fold increase compared to uncapped areas. Importantly, this method does not compromise emitter quality: emitters within overlap regions demonstrate excellent optical performance, including high signal-to-background and signal-to-noise ratios, large Debye-Waller factors, high brightness, and strong spectral stability. Possible defect configurations are also discussed to contextualize the observed emission characteristics. This scalable strategy enables preferential formation of quantum emitters in targeted regions, achieving higher densities than simple treatments such as plasma irradiation while avoiding the complexity of advanced fabrication techniques. The approach provides a practical pathway for integrating high-quality quantum emitters into scalable quantum photonic platforms.

cond-mat.mtrl-sci↗

arXiv2026

Physics-Based versus Data-Driven Classification of Single-Photon Quantum Emitters from Sparse Autocorrelation Data

Identifying single photon emitters from large, inhomogeneous candidate populations is key to realizing many quantum applications. This requires measuring the emitters second order autocorrelation function, whose statistical reliability is fundamentally limited by acquisition time. Machine learning classifiers can accelerate identification from sparse data, but their performance relative to physics-based inference has not been systematically examined. Here, we introduce sequential Bayesian inference for single photon emitter classification and benchmark it against Levenberg-Marquardt fitting and a feedforward neural network. We use synthetic training and test data calibrated against real Hanbury Brown-Twiss measurements from hexagonal boron nitride emitters, enabling evaluation against an exactly known ground-truth emitter number under realistic noise and background conditions. All three approaches achieve high, near-perfect accuracy with sufficient integration time, but differ greatly in convergence rate and robustness under sparse photon statistics. The neural network is most robust at short integration times. The Bayesian classifier reaches near-perfect accuracy fastest, while retaining full physical interpretability. Levenberg-Marquardt fitting remains a valuable, fully interpretable method, achieving the highest recall despite being the slowest to converge. These results lead to several key conclusions. No single method dominates across all performance metrics. Relying on any one metric alone can give a misleading picture of classifier performance, particularly under sparse photon statistics. Physics-based and data-driven methods are complementary rather than competing approaches. Together, these findings provide practical guidance for selecting and combining classification strategies for scalable single-photon-source screening and other quantum-emitter characterization tasks.

quant-ph↗

arXiv2026

Nanoscale Fluorescence Thermometry: Probes, Recent Advances and Emerging Directions

The transition of materials and devices to nanometer, atomic, and quantum scales makes thermal characterization increasingly challenging, driving the need for advanced nanoscale thermometry. Fluorescence nanothermometry has emerged as a powerful approach, enabling remote, spatially resolved temperature measurements with sub-micrometer-to-nanometer precision across applications in nanoelectronics, microfluidics, and biological systems. In these systems, temperature is inferred from variations in fluorescence observables, including spectral position, intensity, linewidth, and excited-state dynamics. This review provides a comprehensive and critical overview of fluorescence nanothermometry, covering fundamental mechanisms, material platforms, recent advances, and emerging applications. It further presents a critical evaluation of key challenges and discusses emerging strategies and future research directions toward achieving robust, real-time thermometry. It is anticipated that this review will stimulate further advances in material platforms and system design, accelerating the development of accurate, scalable, and application-ready nanoscale thermometers.

physics.optics↗

arXiv2025

Seasonal thermal stress analysis of defective mass concrete sidewalls based on the average forming temperature method

Thermal cracking in urban underground sidewalls is frequently observed when structures are cast in summer and enter service in winter, as seasonal temperature gradients act under structural restraint. To quantify the local stress field associated with pre-existing cracks, an orthogonal finite-element simulation matrix of 16 combinations is constructed. Distributions of maximum principal stress () at the surface crack tip and along the upper half of the crack bottom are evaluated using steady-state thermal loading and a linear-elastic constitutive model. Across all cases, pronounced tensile stress concentration occurs at both locations: the maximum ranges from 19.2 to 34.1 MPa at the crack surface end and from 17.2 to 29.4 MPa at the crack bottom. These concentrated values are consistently higher than the stress level at the same locations in an otherwise identical uncracked wall, clarifying how seasonal temperature gradients under restraint amplify local stresses around existing defects. The quantitative ranges reported here provide a basis for risk screening and for formulating practical mitigation measures (e.g., joint spacing and insulation strategies) in the design and operation of urban underground enclosure walls. In addition, three-dimensional simulations of randomly distributed internal voids show that adopting average forming temperature increases the peak tensile stress on void surfaces from 3.42 to 4.40 MPa at 10 deg C and from 5.98 to 6.96 MPa at -5 deg C, further highlighting the risk amplification effect of AFT under cold service conditions.

physics.comp-ph↗

arXiv2025

Machine Learning Based Optical Thermometry Using Photoluminescence and Raman Spectra of Diamonds Containing SiV Centers

Micro- and nanothermometry enable precise temperature monitoring and control at the micro- and nanoscale, and have become essential diagnostic tools in applications ranging from high-power microelectronics to biosensing and nanomedicine. Most existing techniques rely on secondary micro- and nanothermometers that require individual calibration of each sensor, ideally both off- and in-situ, before use. We present an alternative approach that overcomes this limitation by employing fluorescent diamonds containing silicon-vacancy centers, where the thermo-sensitive physical quantities are the centers' photoluminescence and the diamond host's Raman signals. The photoluminescence and Raman data are analyzed using two multi-feature regression algorithms that leverage a minimal number of calibration diamonds and temperature set points to predict the temperature of previously unseen diamonds. Using this approach, the models achieve accuracies as low as 0.7 K, resolutions down to 0.6 K Hz$^{-1/2}$, and sensitivity as high as 0.04 K$^{-1}$. These correspond to improvements of roughly 70 percent (over threefold) in accuracy, 50 percent (twofold) in resolution, and 567 percent (sevenfold) in sensitivity compared with traditional single-feature models. Our approach is particularly suited to applications where pre-deployment calibration of every thermosensor is impractical, and it is generalizable to any thermometry platform with two or more simultaneously measurable temperature-dependent observables.

cond-mat.mtrl-sci↗

arXiv2025

Laser-Induced Heating in Diamonds: Influence of Substrate Thermal Conductivity and Interfacial Polymer Layers

Diamonds hosting color centers possess intrinsically high thermal conductivity; therefore, laser-induced heating has often received little attention. However, when placed on substrates with low thermal conductivity, localized heating of diamonds under laser excitation can become significant, and the presence of an interfacial polymer layer between substrate and diamond further amplifies this effect. Yet, the relationship between substrate thermal conductivity, polymer thickness, and laser heating remains to be established. Here, a systematic investigation is presented on laser-induced heating of silicon-vacancy diamond on substrates with varying thermal conductivity and interfacial polymer thickness. Results reveal that even at a low excitation power of 737~$μ$W/$μ$m$^2$, thin amorphous holey carbon -- the lowest-conductivity substrate ($\sim$0.2~W~m$^{-1}$~K$^{-1}$) studied -- exhibits substantial heating, while glass ($\sim$1.4~W~m$^{-1}$~K$^{-1}$) and polydimethylsiloxane (PDMS, $\sim$0.35~W~m$^{-1}$~K$^{-1}$) show noticeable heating only above 2.95~mW/$μ$m$^2$. For polymer interlayers, a thickness of just 2.2~$μ$m induces significant heating at 2.95~mW/$μ$m$^2$ and above, highlighting strong influence of both substrate and polymer thickness on local heating response. Experimental findings are further validated using COMSOL Multiphysics simulations with a steady-state 3D heat transfer model. These results provide practical guidance for substrate selection and sample preparation, enabling optimization of conditions for optical thermometry and quantum sensing applications.

cond-mat.mtrl-sci↗

arXiv2025

Preemptive Spatiotemporal Trajectory Adjustment for Heterogeneous Vehicles in Highway Merging Zones

Aiming at the problem of driver's perception lag and low utilization efficiency of space-time resources in expressway ramp confluence area, based on the preemptive spatiotemporal trajectory Adjustment system, from the perspective of coordinating spatiotemporal resources, the reasonable value of safe space-time distance in trajectory pre-preparation is quantitatively analyzed. The minimum safety gap required for ramp vehicles to merge into the mainline is analyzed by introducing double positioning error and spatiotemporal trajectory tracking error. A merging control strategy for autonomous driving heterogeneous vehicles is proposed, which integrates vehicle type, driving intention, and safety spatiotemporal distance. The specific confluence strategies of ramp target vehicles and mainline cooperative vehicles under different vehicle types are systematically expounded. A variety of traffic flow and speed scenarios are used for full combination simulation. By comparing the time-position-speed diagram, the vehicle operation characteristics and the dynamic difference of confluence are qualitatively analyzed, and the average speed and average delay are used as the evaluation indices to quantitatively evaluate the performance advantages of the preemptive cooperative confluence control strategy. The results show that the maximum average delay improvement rates of mainline and ramp vehicles are 90.24 % and 74.24 %, respectively. The proposed strategy can effectively avoid potential vehicle conflicts and emergency braking behaviors, improve driving safety in the confluence area, and show significant advantages in driving stability and overall traffic efficiency optimization.

eess.SY↗

arXiv2025

Holistic view of the road transportation system based on real-time data sharing mechanism

Traditional manual driving and single-vehicle-based intelligent driving have limitations in real-time and accurate acquisition of the current driving status and intentions of surrounding vehicles, leading to vehicles typically maintaining appropriate safe distances from each other. Yet, accidents still frequently occur, especially in merging areas; meanwhile, it is difficult to comprehensively obtain the conditions of road infrastructure. These limitations not only restrict the further improvement of road capacity but also result in irreparable losses of life and property. To overcome this bottleneck, this paper constructs a space-time global view of the road traffic system based on a real-time sharing mechanism, enabling both road users and managers to timely access the driving intentions of nearby vehicles and the real-time status of road infrastructure.

cs.CY↗

arXiv2025

Algebro-geometric integration to the discrete Chen-Lee-Liu system

Algebro-geometric solutions for the discrete Chen-Lee-Liu (CLL) system are derived in this paper. We construct a nonlinear integrable symplectic map which is used to define discrete phase flows. Compatibility of the maps with different parameters gives rise to the discrete CLL system whose solutions (discrete potentials) can be formulated through the discrete phase flows. Baker-Akhiezer functions are introduced and their asymptotic behaviors are analyzed. Consequently, we are able to reconstruct the discrete potentials in terms of the Riemann theta functions. These results can be extended to 3-dimensional case and algebro-geometric solutions of the discrete modified Kadomtsev-Petviashvili equation are obtained. Some solutions of genus one case are illustrated.

nlin.SI↗

arXiv2025

Preemptive Holistic Collaborative System and Its Application in Road Transportation

Numerous real-world systems, including manufacturing processes, supply chains, and robotic systems, involve multiple independent entities with diverse objectives. The potential for conflicts arises from the inability of these entities to accurately predict and anticipate each other's actions. To address this challenge, we propose the Preemptive Holistic Collaborative System (PHCS) framework. By enabling information sharing and collaborative planning among independent entities, the PHCS facilitates the preemptive resolution of potential conflicts. We apply the PHCS framework to the specific context of road transportation, resulting in the Preemptive Holistic Collaborative Road Transportation System (PHCRTS). This system leverages shared driving intentions and pre-planned trajectories to optimize traffic flow and enhance safety. Simulation experiments in a two-lane merging scenario demonstrate the effectiveness of PHCRTS, reducing vehicle time delays by 90%, increasing traffic capacity by 300%, and eliminating accidents. The PHCS framework offers a promising approach to optimize the performance and safety of complex systems with multiple independent entities.

eess.SY↗

arXiv2025

Enhancing Expressway Ramp Merge Safety and Efficiency via Spatiotemporal Cooperative Control

In the context of autonomous driving on expressways, the issue of ensuring safe and efficient ramp merging remains a significant challenge. Existing systems often struggle to accurately assess the status and intentions of other vehicles, leading to a persistent occurrence of accidents despite efforts to maintain safe distances. This study proposes a novel spatiotemporal cooperative control approach integrating vehicle-road coordination to address this critical issue. A comprehensive methodology is developed, beginning with the calculation of safe distances under varying spatiotemporal conditions. This involves considering multiple factors, including vehicle speed differentials, positioning errors, and clock synchronization errors. Subsequently, an advanced vehicle conflict risk evaluation model is constructed. By incorporating collision acceleration and emergency acceleration as key parameters, this model offers a more accurate and detailed evaluation of potential risks during the ramp merging process. Based on the calculated safe distances and conflict risk evaluations, a mainline priority coordinated control method is formulated. This method enables the pre-planning of vehicle trajectories, effectively reducing conflicts among vehicles. Through rigorous simulations using diverse traffic volume and speed scenarios, the efficacy of the proposed strategy is validated. The results demonstrate remarkable improvements, with the average delay time reduced by an impressive 97.96% and fuel consumption decreased by 6.01%. These outcomes indicate that the proposed approach not only enhances the speed of vehicle merging but also significantly reduces latency and fuel consumption, thereby enhancing the overall performance of ramp merging operations.

eess.SY↗

arXiv2025

Spatiotemporal Trajectory Tracking Method for Vehicles Incorporating Lead-Lag Judgement

In the domain of intelligent transportation systems, especially within the context of autonomous vehicle control, the preemptive holistic collaborative system has been presented as a promising solution to bring a remarkable enhancement in traffic efficiency and a substantial reduction in the accident rate, demonstrating a great potential of development. In order to ensure this system operates as intended, accurate tracking of the spatiotemporal trajectory is of crucial significance. Moreover, minimizing the tracking error is a necessary step in this process. To this end, a novel lead-lag judgment mechanism is proposed. This mechanism precisely quantifies the longitudinal positional deviation between the vehicle and the target trajectory over time, then the deviation is corrected with a real - time acceleration compensation strategy, as a result, the accuracy and reliability of trajectory tracking are significantly enhanced. Real - vehicle experiments were conducted in a dedicated test field to validate the feasibility of this innovative approach empirically. Subsequently, the obtained tracking data was subsequent processed using the lead-lag judgment mechanism. In this step, we carefully analyzed the spatiotemporal error patterns between the vehicle and the target trajectory under different alignments and speeds. Finally, using real highway speed and alignment data, we conducted comprehensive spatiotemporal trajectory tracking simulations. Through experiments and simulations, tracking errors maintained in an acceptable range and reasonable spatiotemporal distance is given during the preemptive merging process on highway ramps. Overall, this study offers valuable insights for highway ramp emerging safety. Future work can expand on these findings.

eess.SY↗

arXiv2025

Quantum Emitters in Hexagonal Boron Nitride: Principles, Engineering and Applications

Solid-state quantum emitters, molecular-sized complexes releasing a single photon at a time, have garnered much attention owing to their use as a key building block in various quantum technologies. Among these, quantum emitters in hexagonal boron nitride (hBN) have emerged as front runners with superior attributes compared to other competing platforms. These attributes are attainable thanks to the robust, two-dimensional lattice of the material formed by the extremely strong B-N bonds. This review discusses the fundamental properties of quantum emitters in hBN and highlights recent progress in the field. The focus is on the fabrication and engineering of these quantum emitters facilitated by state-of-the-art equipment. Strategies to integrate the quantum emitters with dielectric and plasmonic cavities to enhance their optical properties are summarized. The latest developments in new classes of spin-active defects, their predicted structural configurations, and the proposed suitable quantum applications are examined. Despite the current challenges, quantum emitters in hBN have steadily become a promising platform for applications in quantum information science.

cond-mat.mtrl-sci↗

arXiv2024

Spatio-temporal cooperative control Method of Highway Ramp Merge Based on Vehicle-road Coordination

The merging area of highway ramps faces multiple challenges, including traffic congestion, collision risks, speed mismatches, driver behavior uncertainties, limited visibility, and bottleneck effects. However, autonomous vehicles engaging in depth coordination between vehicle and road in merging zones, by pre-planning and uploading travel trajectories, can significantly enhance the safety and efficiency of merging zones.In this paper,we mainly introduce mainline priority cooperation method to achieve the time and space cooperative control of highway merge.Vehicle-mounted intelligent units share real-time vehicle status and driving intentions with Road Section Management Units, which pre-plan the spatiotemporal trajectories of vehicle travel. After receiving these trajectories, Vehicle Intelligent Units strictly adhere to them. Through this deep collaboration between vehicles and roads, conflicts in time and space during vehicle travel are eliminated in advance.

eess.SY↗

arXiv2024

Design and Testing for Steel Support Axial Force Servo System

Foundation excavations are deepening, expanding, and approaching structures. Steel supports measure and manage axial force. The study regulates steel support structure power during deep excavation using a novel axial force management system for safety, efficiency, and structural integrity. Closed-loop control changes actuator output to maintain axial force based on force. In deep excavation, the servo system regulates unstable soil, side pressure, and structural demands. Modern engineering and tech are used. Temperature changes automatically adjust the jack to maintain axial force. Includes hydraulic jacks, triple-acting cylinders, temperature, and deformation sensors, and automatic control. Foundation pit excavation is dynamic, yet structure tension is constant. There is no scientific way to regulate axial force foundation pit excavation. The revolutionary Servo system adjusts temperature, compression, and axial force to deform pits. System control requires foundation pit direction detection and modification. This engineering method has performed effectively for deep foundation pit excavation at railway crossings and other infrastructure projects. The surrounding protective structure may reduce the steel support's axial stress, making deep foundation excavation safe and efficient. Keywords: Servo systems, Steel strut support design, Deformation control, Monitoring and control, Deep excavation projects.

eess.SY↗

arXiv2024

Multi-photon super-linear image scanning microscopy using upconversion nanoparticles

Super-resolution fluorescence microscopy is of great interest in life science studies for visualizing subcellular structures at the nanometer scale. Among various kinds of super-resolution approaches, image scanning microscopy (ISM) offers a doubled resolution enhancement in a simple and straightforward manner, based on the commonly used confocal microscopes. ISM is also suitable to be integrated with multi-photon microscopy techniques, such as two-photon excitation and second-harmonic generation imaging, for deep tissue imaging, but it remains the twofold limited resolution enhancement and requires expensive femtosecond lasers. Here, we present and experimentally demonstrate the super-linear ISM (SL-ISM) to push the resolution enhancement beyond the factor of two, with a single low-power, continuous-wave, and near-infrared laser, by harnessing the emission nonlinearity within the multiphoton excitation process of lanthanide-doped upconversion nanoparticles (UCNPs). Based on a modified confocal microscope, we achieve a resolution of about 120 nm, 1/8th of the excitation wavelength. Furthermore, we demonstrate a parallel detection strategy of SL-ISM with the multifocal structured excitation pattern, to speed up the acquisition frame rate. This method suggests a new perspective for super-resolution imaging or sensing, multi-photon imaging, and deep-tissue imaging with simple, low-cost, and straightforward implementations.

physics.optics↗