arXiv subjects

Bo Yang

Publications and source records attributed to Bo Yang.

At least 145 records · Page 8Linked to original sources

arXiv2025

Spatially-bounded rogue waves in the Davey-Stewartson I equation

Spatially-bounded rogue waves, i.e., rogue waves that arise in a limited region of a multi-dimensional space, are interesting and important from both theoretical and applied points of view. In this paper, we determine spatially-bounded rogue waves in the Davey-Stewartson I equation. We show that these rogue waves can be obtained when a single or multiple internal parameters in the higher-order rational solution of the Davey-Stewartson I equation are real and large, and the order-index vector of this higher-order rational solution has even length and comprises pairs of the form (2n, 2n+1), where n is a positive integer. Under these conditions and another nondegeneracy condition on the root curve of a certain double-real-variable polynomial, the higher-order rational solution will exhibit spatially-bounded rogue waves that arise from a uniform background with some time-varying lumps on it, reach high amplitude in limited space, and then disappear into the same background again. The crests of these rogue waves form a single or multiple closed curves that are generically disconnected from each other on the spatial plane, and are analytically predicted by the root curve mentioned above. We also derive uniformly-valid asymptotic approximations for these spatially-bounded rogue waves in the large-parameter regime. Near the crests of these rogue waves, these asymptotic approximations reduce to simple expressions. Our asymptotic approximations of these rogue waves are compared to true solutions and good agreement is demonstrated.

nlin.SI↗

arXiv2025

Use as Many Surrogates as You Want: Selective Ensemble Attack to Unleash Transferability without Sacrificing Resource Efficiency

In surrogate ensemble attacks, using more surrogate models yields higher transferability but lower resource efficiency. This practical trade-off between transferability and efficiency has largely limited existing attacks despite many pre-trained models are easily accessible online. In this paper, we argue that such a trade-off is caused by an unnecessary common assumption, i.e., all models should be \textit{identical} across iterations. By lifting this assumption, we can use as many surrogates as we want to unleash transferability without sacrificing efficiency. Concretely, we propose Selective Ensemble Attack (SEA), which dynamically selects diverse models (from easily accessible pre-trained models) across iterations based on our new interpretation of decoupling within-iteration and cross-iteration model diversity. In this way, the number of within-iteration models is fixed for maintaining efficiency, while only cross-iteration model diversity is increased for higher transferability. Experiments on ImageNet demonstrate the superiority of SEA in various scenarios. For example, when dynamically selecting 4 from 20 accessible models, SEA yields 8.5% higher transferability than existing attacks under the same efficiency. The superiority of SEA also generalizes to real-world systems, such as commercial vision APIs and large vision-language models. Overall, SEA opens up the possibility of adaptively balancing transferability and efficiency according to specific resource requirements.

cs.CV↗

arXiv2025

A High-Efficiency Microwave Power Combining System Based on Frequency-Tuning Injection-Locked Magnetrons

To increase the power level and energy utilization rate of injection-locked magnetron sources, a dual way 1-kW S-band magnetron microwave power combining system with high combining efficiency was proposed and validated. A waveguide magic-Tee was used to achieve power combining and to provide a pathway for the reference signal. This system utilizes the power-dividing characteristic of a magic-Tee to lock two magnetrons. Frequency tuning is applied to adjust the phase difference between the two magnetrons' signals so as to achieve a high combining efficiency. Experimental results indicate that the microwave power combining efficiency of the proposed system reaches 94.5%. The attenuation of microwave power is caused only by the waveguides and magic-Tee. Our investigation provides a guideline for future high-power microwave combining systems with low losses.

physics.app-ph↗

arXiv2025

Air-Chamber Based Soft Six-Axis Force/Torque Sensor for Human-Robot Interaction

Soft multi-axis force/torque sensors provide safe and precise force interaction. Capturing the complete degree-of-freedom of force is imperative for accurate force measurement with six-axis force/torque sensors. However, cross-axis coupling can lead to calibration issues and decreased accuracy. In this instance, developing a soft and accurate six-axis sensor is a challenging task. In this paper, a soft air-chamber type six-axis force/torque sensor with 16-channel barometers is introduced, which housed in hyper-elastic air chambers made of silicone rubber. Additionally, an effective decoupling method is proposed, based on a rigid-soft hierarchical structure, which reduces the six-axis decoupling problem to two three-axis decoupling problems. Finite element model simulation and experiments demonstrate the compatibility of the proposed approach with reality. The prototype's sensing performance is quantitatively measured in terms of static load response, dynamic load response and dynamic response characteristic. It possesses a measuring range of 50 N force and 1 Nm torque, and the average deviation, repeatability, non-linearity and hysteresis are 4.9$\%$, 2.7$\%$, 5.8$\%$ and 6.7$\%$, respectively. The results indicate that the prototype exhibits satisfactory sensing performance while maintaining its softness due to the presence of soft air chambers.

cs.RO↗

arXiv2025

Negatively curved Kähler metrics on total spaces of a class of vector bundles

In this paper we show an abundance of complete Kähler metrics with negative holomorphic bisectional curvature on total spaces of certain vector bundles. Assume that such total spaces are endowed with a wider class of nonpositively curved Kähler metrics. We prove dimension estimates on holomorphic functions on these manifolds, as well as Liouville theorems for holomorphic mappings between them.

math.DG↗

arXiv2025

Innovative Design of Multi-functional Supernumerary Robotic Limbs with Ellipsoid Workspace Optimization

Supernumerary robotic limbs (SRLs) offer substantial potential in both the rehabilitation of hemiplegic patients and the enhancement of functional capabilities for healthy individuals. Designing a general-purpose SRL device is inherently challenging, particularly when developing a unified theoretical framework that meets the diverse functional requirements of both upper and lower limbs. In this paper, we propose a multi-objective optimization (MOO) design theory that integrates grasping workspace similarity, walking workspace similarity, braced force for sit-to-stand (STS) movements, and overall mass and inertia. A geometric vector quantification method is developed using an ellipsoid to represent the workspace, aiming to reduce computational complexity and address quantification challenges. The ellipsoid envelope transforms workspace points into ellipsoid attributes, providing a parametric description of the workspace. Furthermore, the STS static braced force assesses the effectiveness of force transmission. The overall mass and inertia restricts excessive link length. To facilitate rapid and stable convergence of the model to high-dimensional irregular Pareto fronts, we introduce a multi-subpopulation correction firefly algorithm. This algorithm incorporates a strategy involving attractive and repulsive domains to effectively handle the MOO task. The optimized solution is utilized to redesign the prototype for experimentation to meet specified requirements. Six healthy participants and two hemiplegia patients participated in real experiments. Compared to the pre-optimization results, the average grasp success rate improved by 7.2%, while the muscle activity during walking and STS tasks decreased by an average of 12.7% and 25.1%, respectively. The proposed design theory offers an efficient option for the design of multi-functional SRL mechanisms.

cs.RO↗

arXiv2025

Kähler geometry on total spaces of vector bundles over elliptic curves

We study function theory and Kähler geometry on total spaces of vector bundles on an elliptic curve. For rank two vector bundles of degree zero, we show that any two total spaces are biholomorphic if and only if the corresponding vector bundles are isomorphic. We also construct complete Gauduchon Hermitian metrics with flat Chern-Ricci curvature on these total spaces. These metrics are natural in the sense that the corresponding spaces of holomorphic functions of polynomial growth coincide with `polynomials' on these spaces. Moreover, we characterize all complete Kähler metrics with nonnegative bisectional curvature on total spaces of line bundles over an elliptic curve.

math.DG↗

arXiv2025

Long-range Entanglement and Role of Realistic Interaction in Braiding of Non-Abelian Quasiholes in Fractional Quantum Hall Phases

Parity conservation dictates that when fusing pairs of Moore-Read (MR) quasiholes, such that each pair of charge-$e/4$ anyon forms a charge-$e/2$ anyon, the parity of the numbers of $1$-anyon and $ψ$-anyon must be conserved within a given system. This idea is illustrated here using the Jack polynomial formalism, which also provides a basis to numerically study the dynamics of MR anyons. In particular, we examine the effect of two-body electron-electron interaction on the degeneracy of two anyon fusion channels, which affects their mutual statistics of the MR anyons. We find that parity conservation gives rise to a long-range ``entanglement" which affect the experimental measurement of exchange statistics under realistic electron interaction. It is therefore important to account for all quasiholes in an experimental systems in order to accurately predict the outcome of a certain measurement. We also show how understanding the quasihole dynamics can help to fine-tune two-body interactions in order to stabilize any given fusion channel in experiments.

cond-mat.str-el↗

arXiv2025

Strain-engineered nanoscale spin polarization reversal in diamond nitrogen-vacancy centers

The ability to control solid-state quantum emitters is fundamental to advancing quantum technologies. The performance of these systems is fundamentally governed by their spin-dependent photodynamics, yet conventional control methods using cavities offer limited access to key non-radiative processes. Here we demonstrate that anisotropic lattice strain serves as a powerful tool for manipulating spin dynamics in solid-state systems. Under high pressure, giant shear strain gradients trigger a complete reversal of the intrinsic spin polarization, redirecting ground-state population from $|0\rangle$ to $|\pm 1\rangle$ manifold. We show that this reprogramming arises from strain-induced mixing of the NV center's excited states and dramatic alteration of intersystem crossing, which we quantify through a combination of opto-magnetic spectroscopy and a theoretical model that disentangles symmetry-preserving and symmetry-breaking strain contributions. Furthermore, the polarization reversal is spatially mapped with a transition region below 120 nm, illustrating sub-diffraction-limit control. Our work establishes strain engineering as a powerful tool for tailoring quantum emitter properties, opening avenues for programmable quantum light sources, high-density spin-based memory, and hybrid quantum photonic devices.

quant-ph↗

arXiv2025

3D Gaussian Radiation Field Modeling for Integrated RIS-FAS Systems: Analysis and Optimization

The integration of reconfigurable intelligent surfaces (RIS) and fluid antenna systems (FAS) has attracted considerable attention due to its tremendous potential in enhancing wireless communication performance. However, under fast-fading channel conditions, rapidly and effectively performing joint optimization of the antenna positions in an FAS system and the RIS phase configuration remains a critical challenge. Traditional optimization methods typically rely on complex iterative computations, thus making it challenging to obtain optimal solutions in real time within dynamic channel environments. To address this issue, this paper introduces a field information-driven optimization method based on three-dimensional Gaussian radiation-field modeling for real-time optimization of integrated FAS-RIS systems. In the proposed approach, obstacles are treated as virtual transmitters and, by separately learning the amplitude and phase variations, the model can quickly generate high-precision channel information based on the transmitter's position. This design eliminates the need for extensive pilot overhead and cumbersome computations. On this framework, an alternating optimization scheme is presented to jointly optimize the FAS position and the RIS phase configuration. Simulation results demonstrate that the proposed method significantly outperforms existing approaches in terms of spectrum prediction accuracy, convergence speed, and minimum achievable rate, validating its effectiveness and practicality in fast-fading scenarios.

cs.NI↗

arXiv2025

Knowledge-Guided Multi-Agent Framework for Application-Level Software Code Generation

Automated code generation driven by Large Lan- guage Models (LLMs) has enhanced development efficiency, yet generating complex application-level software code remains challenging. Multi-agent frameworks show potential, but existing methods perform inadequately in large-scale application-level software code generation, failing to ensure reasonable orga- nizational structures of project code and making it difficult to maintain the code generation process. To address this, this paper envisions a Knowledge-Guided Application-Level Code Generation framework named KGACG, which aims to trans- form software requirements specification and architectural design document into executable code through a collaborative closed- loop of the Code Organization & Planning Agent (COPA), Coding Agent (CA), and Testing Agent (TA), combined with a feedback mechanism. We demonstrate the collaborative process of the agents in KGACG in a Java Tank Battle game case study while facing challenges. KGACG is dedicated to advancing the automation of application-level software development.

cs.SE↗

arXiv2025

Joint Optimization of Cooperation Efficiency and Communication Covertness for Target Detection with AUVs

This paper investigates underwater cooperative target detection using autonomous underwater vehicles (AUVs), with a focus on the critical trade-off between cooperation efficiency and communication covertness. To tackle this challenge, we first formulate a joint trajectory and power control optimization problem, and then present an innovative hierarchical action management framework to solve it. According to the hierarchical formulation, at the macro level, the master AUV models the agent selection process as a Markov decision process and deploys the proximal policy optimization algorithm for strategic task allocation. At the micro level, each selected agent's decentralized decision-making is modeled as a partially observable Markov decision process, and a multi-agent proximal policy optimization algorithm is used to dynamically adjust its trajectory and transmission power based on its local observations. Under the centralized training and decentralized execution paradigm, our target detection framework enables adaptive covert cooperation while satisfying both energy and mobility constraints. By comprehensively modeling the considered system, the involved signals and tasks, as well as energy consumption, theoretical insights and practical solutions for the efficient and secure operation of multiple AUVs are provided, offering significant implications for the execution of underwater covert communication tasks.

cs.LG↗

arXiv2025

Sympathetic Eruption of Two Filaments and Associated Solar Coronal Jet

Combining the high-quality observations from the {\it Solar Dynamics Observatory} (SDO), the Global Oscillation Network Group (GONG), and the Chinese H$α$ Solar Explorer (CHASE), we report a solar coronal jet triggered by the sympathetic eruption of two filaments on 2024 January 11. Initially, the western segment of an active region filament erupted. The erupting plasma propagated eastward, approximately along the filament's axis. This eruption perturbed the magnetic field of a second filament situated near its eastern footpoint, the second filament then erupted sympathetically about one hour later. The eruption of the second filament is a failed one, with the majority of the filament material falling back after the initial lifting. Although no GOES flare accompanied these filament eruptions, distinct brightenings were observed following each eruption. The second eruption produced a large coronal jet, which propagated along a bent trajectory with an apparent deflection angle of approximately 90 degrees. No clear evidence of magnetic reconnection was detected at the deflection site, thus we suspect that the jet may have traveled along an S-shaped trans-equatorial loop and shown a curved trajectory. This event exhibits multiple phenomena: partial filament eruption, failed filament eruption, sympathetic filament eruption, jet initiation by filament eruption, and apparently deflected jet propagation. Collectively, these observations highlight the complexity and diversity of solar activity.

astro-ph.SR↗

arXiv2025

Non-universal Thermal Hall Responses in Fractional Quantum Hall Droplets

We analytically compute the thermal Hall conductance (THC) of fractional quantum Hall droplets under realistic conditions that go beyond the idealized linear edge theory with conformal symmetry. Specifically, we consider finite-size effects at low temperature, nonzero self-energies of quasiholes, and general edge dispersions. We derive measurable corrections in THC that are consistent with the experimental observables. Although the quantized THC is commonly regarded as a topological invariant that is independent of edge confinement, our results show that this quantization remains robust only for arbitrary edge dispersion in the thermodynamic limit. Furthermore, the THC contributed by Abelian modes can become extremely sensitive to finite-size effects and irregular confining potentials in any realistic experimental system. In contrast, non-Abelian modes show robust THC signatures under perturbations, indicating an intrinsic stability of non-Abelian anyons.

cond-mat.mes-hall↗

arXiv2025

TimeEmb: A Lightweight Static-Dynamic Disentanglement Framework for Time Series Forecasting

Temporal non-stationarity, the phenomenon that time series distributions change over time, poses fundamental challenges to reliable time series forecasting. Intuitively, the complex time series can be decomposed into two factors, \ie time-invariant and time-varying components, which indicate static and dynamic patterns, respectively. Nonetheless, existing methods often conflate the time-varying and time-invariant components, and jointly learn the combined long-term patterns and short-term fluctuations, leading to suboptimal performance facing distribution shifts. To address this issue, we initiatively propose a lightweight static-dynamic decomposition framework, TimeEmb, for time series forecasting. TimeEmb innovatively separates time series into two complementary components: (1) time-invariant component, captured by a novel global embedding module that learns persistent representations across time series, and (2) time-varying component, processed by an efficient frequency-domain filtering mechanism inspired by full-spectrum analysis in signal processing. Experiments on real-world datasets demonstrate that TimeEmb outperforms state-of-the-art baselines and requires fewer computational resources. We conduct comprehensive quantitative and qualitative analyses to verify the efficacy of static-dynamic disentanglement. This lightweight framework can also improve existing time-series forecasting methods with simple integration. To ease reproducibility, the code is available at https://github.com/showmeon/TimeEmb.

cs.LG↗

arXiv2025

On the Robustness Evaluation of 3D Obstacle Detection Against Specifications in Autonomous Driving

Autonomous driving systems (ADSs) rely on real-time sensor data, such as cameras and LiDARs, for time-critical decisions using deep neural networks. The accuracy of these decisions is crucial for the widespread adoption of ADSs, as errors can have serious consequences. 3D obstacle detection, in particular, is sensitive to point cloud data (PCD) noise from various sources. However, the robustness of current 3D obstacle detection models against specification-based perturbations remains unevaluated. These perturbations are derived from the specification of LiDAR sensors and previous research on LiDAR's ability to capture objects of different colors and materials. They can manifest as very subtle sensor-based noises or obstacle-specific perturbations. Hence, we propose SORBET, a framework that tests the robustness of 3D obstacle detection models in ADS against such perturbations to the PCD to evaluate their robustness. We applied SORBET to evaluate the robustness of five classic 3D obstacle detection models, including one from an industry-grade Level 4 ADS (Baidu's Apollo). Furthermore, we studied how the deviated obstacle detection results would propagate and negatively impact trajectory prediction. Our evaluation emphasizes the importance of testing 3D obstacle detection against specification-based perturbations. We find that even very subtle changes in the PCD (i.e., removing two points) may introduce a non-trivial decrease in the detection performance. Furthermore, such a negative impact will further propagate to other modules and endanger the safety of the ADS.

cs.SE↗

arXiv2025

A Predictive and Sampled-Data Barrier Method for Safe and Efficient Quadrotor Control

This paper proposes a cascaded control framework for quadrotor trajectory tracking with formal safety guarantees. First, we design a controller consisting of an outer-loop position model predictive control (MPC) and an inner-loop nonlinear attitude control, enabling decoupling of position safety and yaw orientation. Second, since quadrotor safety constraints often involve high relative degree, we adopt high order control barrier functions (HOCBFs) to guarantee safety. To employ HOCBFs in the MPC formulation that has formal guarantees, we extend HOCBFs to sampled-data HOCBF (SdHOCBFs) by introducing compensation terms, ensuring safety over the entire sampling interval. We show that embedding SdHOCBFs as control-affine constraints into the MPC formulation guarantees both safety and optimality while preserving convexity for real-time implementations. Finally, comprehensive simulations are conducted to demonstrate the safety guarantee and high efficiency of the proposed method compared to existing methods.

eess.SY↗

arXiv2025

PolyLink: A Blockchain Based Decentralized Edge AI Platform for LLM Inference

The rapid advancement of large language models (LLMs) in recent years has revolutionized the AI landscape. However, the deployment model and usage of LLM services remain highly centralized, creating significant trust issues and costs for end users and developers. To address these issues, we propose PolyLink, a blockchain-based decentralized AI platform that decentralizes LLM development and inference. Specifically, PolyLink introduces a decentralized crowdsourcing architecture that supports single-device and cross-device model deployment and inference across heterogeneous devices at the edge. Moreover, to ensure the inference integrity, we design the TIQE protocol, which combines a lightweight cross-encoder model and an LLM-as-a-Judge for a high-accuracy inference evaluation. Lastly, we integrate a comprehensive token-based incentive model with dynamic pricing and reward mechanisms for all participants. We have deployed PolyLink and conducted an extensive real-world evaluation through geo-distributed deployment across heterogeneous devices. Results indicate that the inference and verification latency is practical. Our security analysis demonstrates that the system is resistant to model degradation attacks and validator corruptions. PolyLink is now available at https://github.com/IMCL-PolyLink/PolyLink.

cs.CR↗