arXiv subjects

Rui Zhang

Publications and source records attributed to Rui Zhang.

At least 109 records · Page 6Linked to original sources

arXiv2026

Bending Beam for THz Wireless Networks: Fundamental, Design Issue, and Prototype

Bending beams, characterized by their non diffracting and self-healing properties in the near field, offer a new approach to bypass blockage in terahertz (THz) wireless communication and sensing. However, the investigations of bend ing beams in the context of wireless communications still remain at an early stage. This article provides a state-of-the-art review of the fundamentals and key application scenarios of bending beams in THz wireless communications and sensing. We first present and compare the existing beamforming design and practical hardware implementation methods for bending beams. Next, we discuss potential applications of bending beams in wireless communica tions and sensing and identify their associated challenges, such as blocked channel modeling, bending beam training, codebook design, etc. Finally, a hardware demonstration of bending beam over THz frequency bands is presented, validating the advantages of bending beam over conventional beamfocusing.

eess.SP↗

arXiv2026

GDBR: Label Recovery Attack Against Partial Gradient Encryption in Federated Learning

The increasing demand for data privacy, alongside the benefits of aggregating data from networked devices, has catalyzed the emergence of federated learning (FL). In FL, clients jointly train a global model by sharing gradients computed over private data. While this paradigm eliminates the need to exchange raw data, inference attacks can still be launched to extract sensitive information from gradients. To this end, partial gradient encryption has emerged as a promising design for balancing privacy and efficiency in practical FL systems, as encrypting only the classification-head gradients is believed to prevent known inference attacks while avoiding the high computational cost of encrypting the entire model. However, this design provides a false sense of privacy. By proposing GDBR, we show that sharing even a single unencrypted layer of gradients can lead to serious privacy leakage. GDBR is the first attack capable of high-fidelity label recovery with partial access to the gradients. It exploits a vulnerability in a commonly used neural building block, constructs a gradient bridge from the unencrypted layer to the final output layer, and approximates the logits information for accurate inference of private labels. These inferred labels not only reveal sensitive information about a client's private dataset but also serve as a prerequisite for many downstream attacks, such as data reconstruction and membership inference. GDBR brings these threats squarely into scope for FL systems employing partial encryption. In addition to theoretical analysis, extensive experiments demonstrate the severity of the problem across a wide variety of datasets and model architectures, including convolutional and transformer-based networks. Overall, our findings challenge the widespread assumption that encrypting only the output layer suffices for privacy protection.

cs.LG↗

arXiv2026

Elastic Modulus in One-Dimensional Quantum Droplets

Quantum droplets (QDs) are self-bound states of ultradilute quantum fluids stabilized by the interplay between the Lee Huang-Yang (LHY) quantum-fluctuation correction and the mean-field interaction, providing a useful platform for exploring macroscopic quantum phenomena. Recent studies on three-dimensional QDs have introduced the concept of bulk modulus and revealed its connection with the breathing-mode frequency, thereby linking the elastic response of QDs to their collective dynamics. Motivated by this progress, we investigate the elastic modulus of one-dimensional QDs. Based on a super Gaussian variational ansatz, we systematically derive the elastic modulus B and analyze its dependence on the interaction strength and particle number. The analytical predictions are further validated by numerical simulations based on imaginary time evolution and the spatial scaling method. We also establish a quantitative relation between the elastic modulus and the eigenfrequency of the breathing mode. In addition, by incorporating corrections to the droplet width beyond the Thomas Fermi approximation, we obtain the dependence of the ratio η = B/2 on the control parameters g and N. Unlike the three-dimensional case, where the corresponding ratio follows a simple power-law scaling, the one-dimensional system is affected by the soliton-to-droplet crossover, leading to a more intricate dependence of η on g and N. Our results show that, in the high-particle-number regime, the elastic modulus asymptotically approaches a limiting value determined mainly by the interaction strength, whereas in the low-particle-number regime it depends on both the particle number and the interaction strength.

cond-mat.quant-gas↗

arXiv2026

Correct Asymptotic Wavefunctions for Calculating Photoelectron Angular Distributions of O2- and NO-

The ab initio calculation of photoelectron angular distributions (PADs) for negative ions remains a significant theoretical challenge. In this work, we report a joint experimental and theoretical investigation of PADs for a series of molecular anions with varying polarities, including the nonpolar O2-, the weakly polar NO-, and the strongly polar AsO- and SbO-. To accurately describe the long-range electronic wavefunctions -- where photodetachment contributes most strongly -- we modified the standard Gaussian-type orbitals (GTOs) by augmenting them with a correct exponential Slater-tail basis set (~e^(-ξr)). This simple yet effective approach significantly improves the agreement between the experimental and theoretical PADs for O2- and NO-. However, notable discrepancies persist for NO- for transitions to the v = 0 and v = 1 vibrational levels of neutral NO even after this correction. Given that our methodology successfully reproduced PADs for strongly polar anions (e.g., AsO- and SbO-), these residual discrepancies are unlikely to stem from "exit-channel scattering" induced by long-range dipole fields. Instead, we tentatively attribute the failure for NO- to the breakdown of the Born-Oppenheimer approximation or the frozen orbital approximation, arising from the extremely weak binding of the excess electron.

physics.atom-ph↗

arXiv2026

Toward Efficient Sensing in Multi-Device ISCC by Removing Frequency Domain Redundancy

Integrated sensing, communication, and computation (ISCC) is envisioned as a key enabler for intelligent services in future wireless networks. However, in multi-device ISCC systems, directly offloading full orthogonal frequency division multiplexing (OFDM) sensing data to the edge may incur excessive overhead, thereby limiting sensing performance under practical resource constraints. In this paper, we propose a subcarrier selection-based sensing framework for multi-device ISCC systems, where frequency-domain redundancy in OFDM sensing data is removed during local preprocessing to reduce sensing data transmission and processing overhead. Based on the proposed framework, we establish analytical models for sensing accuracy, delay, and energy consumption, and formulate a sensing accuracy maximization problem under practical resource constraints. To solve this problem, we develop an alternating direction method of multipliers (ADMM)-based algorithm. Experiments on commodity wireless devices validate the effectiveness of the proposed framework and show that it consistently outperforms three baseline schemes under various resource constraints.

eess.SP↗

arXiv2026

A second-order unified gas-kinetic wave-particle method with enhanced mesh independence for hypersonic flows

Benefiting from the direct modeling of physical laws in a discretized space and the automatic decomposition of the gas distribution function into hydrodynamic waves and particles, the UGKWP method offers significant advantages for multiscale flows such as hypersonic flows, plasma transport, and radiation transport. In this study, the particle sampling accuracy in the UGKWP method is improved from first order to second order, so that the second-order spatial and temporal accuracy is preserved across the full scheme. Specifically, the modifications include second-order particle sampling based on local macroscopic gradients, a weighted least-squares gradient reconstruction that incorporates wall values, a revised Venkatakrishnan limiter for highly stretched cells, and conservation corrections after particle sampling. Moreover, the first-order Chapman--Enskog term is considered in the free-transport part of the hydrodynamic wave flux, enabling better recovery of the GKS in the near-continuum regime. Based on these improvements, the mesh-independence behavior of the UGKWP method is notably enhanced, which is more consistent with the performance of the UGKS, validated by a detailed hypersonic cylinder flow test case. Furthermore, systematic comparisons with the single-scale DSMC method are performed for two-dimensional hypersonic flow over a cylinder and three-dimensional flow over a blunt cone. Wall pressure, shear stress, and heat flux coefficients (CP, CF, and CQ) are examined in the cylinder case, while the overall aerodynamic coefficients (CL, CD, and L/D) are assessed in the cone case. The multiscale UGKWP method exhibits significantly better mesh-independence performance than DSMC for mesh-sensitive quantities such as CF, CQ, CD, and L/D, which are critical for aerodynamic and thermal protection design of near-space hypersonic vehicles.

physics.flu-dyn↗

arXiv2026

Beyond Uniform Experts: Cost-Aware Expert Execution for Efficient Multi-Device MoE Inference

Mixture-of-Experts (MoE) architectures enable language models to achieve unprecedented scale via sparse activation. However, their inference performance is often limited by data movement bottlenecks. Two coupled challenges exacerbate this limtation: (1) Importance-Agnostic Cost: Low-contribution experts incur nearly uniform memory and transfer costs, resulting in a low cost-to-benefit ratio and wasting critical bandwidth; (2) System-Level Imbalance: Multi-device deployments are universally bottlenecked by the slowest device, meaning that local reductions on one device may yield no improvement in end-to-end latency. We propose Cost-Aware Expert Execution (CAEE), a hardware-guided runtime framework that jointly optimizes for token-level expert importance and system-level execution cost. CAEE uses lightweight, calibrated cost models to estimate hardware overhead, selectively prunes low-importance, high-cost experts, and redistributes their contributions via a low-overhead compensation mechanism, avoiding extra data movement. Evaluations on the 671B DeepSeek-R1 model show that CAEE can reduce end-to-end inference latency by 8\%-18\% across diverse deployment settings, including expert offloading and on-device execution on multi-device systems, while maintaining a model accuracy drop of less than 1\%.

cs.DC↗

arXiv2026

Spin-orbit coupling induced geometric squeezing in rotating Bose-Einstein condensates

Squeezed states play a key role in diverse frontiers of quantum physics. Geometrically squeezed states, a squeezed state in the orbital phase space of rotating Bose-Einstein condensates (BEC), have been conventionally generated by anisotropic trapping potentials. In this work, we propose a different route to generate geometric squeezing via spin-orbit coupling (SOC) in a pseudospin-1/2 BEC. We show that the SOC enables effective two-phonon transitions within the lowest Landau level via virtual spin-flip processes, leading to exponential squeezing dynamics in both spin components. Furthermore, by applying a $π/2$ spin rotation, the two spin channels can be coherently coupled to produce two-mode geometric squeezing. We also investigate the influence of interatomic interactions on squeezing performance and identify parameters where robust squeezing can be achieved. Our work provides a viable pathway to realize and manipulate geometric squeezing in spinor quantum gases.

cond-mat.quant-gas↗

arXiv2026

Silicon-compatible ideal antiferroelectricity with large digital electromechanical responses enabled by thermal-strain domain engineering

Antiferroelectrics exhibit reversible antipolar-polar transformations, offering a compelling platform for multiple functionalities in modern nanoelectronics, yet deterministic control of antiferroelectric domains and switching pathways remain elusive. Moreover, their integration with ubiquitous silicon-based electronic devices has been limited by the structural and chemical incompatibilities of conventional oxide platforms. Here, we convert the conventional drawback of thermal mismatch into a functional advantage and realize ideal antiferroelectricity in epitaxial PbZrO3 thin films on silicon through thermal tensile-strain engineering, a strain regime unattainable on conventional perovskite substrates. Combined theoretical and experimental studies show that tensile strain stabilizes the (004)o domain, enabling a direct one-step switching, whereas compressive-strain-stabilized (240)o domains switch through intermediate ferrielectric states. The resulting films exhibit near-zero remanent polarization, square double hysteresis, nanosecond switching (~75ns), large reversible electrostrain (~0.6%) and robust operation windows. These findings provide key insights into domain-engineered ideal antiferroelectricity on silicon, opening a viable route toward high-performance antiferroelectric nano-electronic devices.

cond-mat.mtrl-sci↗

arXiv2026

Diffusion asymmetry of repulsive skyrmions in structured environment

The diffusion of matter in structured environments can give rise to emergent phenomena that do not occur in unstructured environments. Here, we report the asymmetric diffusion of magnetic skyrmions in structured chambers, where repulsive skyrmion-skyrmion and skyrmion-environment interactions play vital roles in their diffusive behavior. By fabricating an off-center asymmetric gate separating two chambers, skyrmions could demonstrate asymmetric diffusion through the gate, which depends on the gate symmetry, the gate opening width, and the skyrmion density. Although the diffusion is affected by the skyrmion density, the simulation outcomes are generally in line with rate equation solutions assuming time-independent diffusion rates. Diffusive skyrmions within the chamber can transiently form bonds through repulsive skyrmion-skyrmion interactions, leading to emergent rotational dynamics that is unique to interacting skyrmion systems. Our results uncover asymmetric diffusive behavior of skyrmions, offering insights that will appeal to the wide audience interested in magnetism, active matter, and statistical physics.

cond-mat.mes-hall↗

arXiv2026

ISAC for Sea-Air Networks: Predictive Beam Tracking under Sea Induced Disturbances

In sea-air communication networks composed of an uncrewed aerial vehicle (UAV) and an uncrewed surface vehicle (USV), the extended target characteristics and three degree of freedom motion of the USV under sea induced disturbances cause beam misalignment in the UAV's tracking of the USV. To address these issues, this paper proposes a predictive beam tracking scheme based on integrated sensing and communication (ISAC) for sea-air networks. We develop a wide and narrow beam switching scheme based on sub-array selection, where a time allocation factor is optimized to balance robust state sensing in the wide beam mode and high-rate communication in the narrow beam mode. Specifically, a wide beam mode provides full USV coverage and state sensing, while a narrow beam mode exploits the estimated state for high-gain communication with the communication receiver (CR) mounted on the USV. To characterize the CR motion, a sea-air state evolution model is derived by jointly considering the surge, sway, yaw, and sea induced disturbances of the USV. For the extended target USV, the measurement equation is constructed from multiple scatterer observations, with the measurement noise caused by sea clutter modeled, and an extended Kalman filter (EKF) based CR state prediction and estimation method is developed. In addition, the effect of sea clutter on sensing accuracy is incorporated into the time allocation optimization problem to adjust the time of the wide beam mode. Simulation results demonstrate that the proposed scheme achieves higher tracking accuracy than the state-of-the-art benchmark schemes.

eess.SY↗

arXiv2026

Performance Analysis for Heterogeneous Air-Ground ISAC in Coordinated Multipoint Networks

The emergence of the \textit{low-altitude economy} (LAE) calls for highly integrated and reliable wireless systems that can simultaneously support \textit{communication and sensing} (C\&S) functions. Although \textit{integrated sensing and communication} (ISAC) has been widely studied, most existing works focused on link-level or single-cell architectures in terrestrial environments, leaving the potential of network-level cooperative air-ground ISAC largely unexplored. To bridge this gap, a heterogeneous air-ground ISAC network architecture based on \textit{coordinated multipoint} (CoMP) is proposed, which incorporates a cooperative hybrid mono/bi-static sensing scheme to enhance spatial diversity and sensing capability. In the proposed architecture, a two-tier \textit{base station} (BS) deployment is adopted: master BSs are arranged in a hexagonal lattice, while slave BSs follow a Poisson point process distribution. This structure concurrently supports communication for terrestrial users and sensing for aerial targets. A holistic performance analysis framework for both C\&S is further developed, accounting for key channel and network parameters. Simulation results reveal inherent trade-offs between C\&S performance, especially under multi-BS cooperation and varying network density. These findings provide practical guidance for the deployment of scalable and efficient ISAC networks in LAE scenarios.

cs.IT↗

arXiv2026

CrypFormBench: Benchmarking Formal Analysis Capability of Large Language Models for Cryptographic Schemes

Manual formal analysis of cryptographic schemes is labor-intensive and requires substantial expertise. While model-checking tools (e.g., Scyther and Tamarin) and computational-security tools (e.g., CryptoVerif and EasyCrypt) improve the automation of security proofs, they still rely on experts to abstract schemes and write tool-specific formal descriptions. Large language models (LLMs) are a promising alternative, but their effectiveness in this domain remains unexplored due to the absence of standardized evaluation methodologies. To fill this gap, we introduce CrypFormBench (C.F.B for short), a comprehensive benchmark jointly covering symbolic and computational security to evaluate five core LLM capabilities: interpretation, generation, completion, transformation, and correction. It comprises 700 instances spanning 677 schemes, 7 mainstream formal verifier languages, and 160 security properties. The evaluation of 9 state-of-the-art LLMs reveals that most of them perform well on interpretation and completion, given their code-awareness advantages, but struggle with generation, transformation, and correction. Overall, their performance remains limited, with Claude-3.5 achieving the highest score at 48.7 out of 100. We further provide practical guidance, e.g., few-shot prompting, Pass@K sampling, and lightweight fine-tuning, to mitigate the executability bottleneck and improve tool-usable outputs. Taken together, our benchmark and analyses offer a grounded view of current progress and concrete directions toward reliable LLM-assisted formal cryptographic analysis.

cs.CR↗

arXiv2026

Capture Timing-Attention of Events in Clinical Time Series

The contemporary paradigm of trajectory learning operates fundamentally at the level of group dynamics, systematically reducing individual-level complexity to fit group-level models, thus rendering effective patient subtyping difficult and individual-level modeling largely out of reach. We propose a data-driven paradigm that introduces a dedicated individual-level temporal variable to capture \emph{Timing Attention} (i.e., the degree of concentration of an event's timing distribution across the patient cohort), thereby rendering timing a \emph{computable dimension} that enables individualized temporal features in trajectory learning. Instantiated as the Level-of-Individual Time Transformation (LITT) and applied to longitudinal EHR data from 3,276 breast cancer patients, the proposed paradigm demonstrates, for the first time to our knowledge: (1) automatic discovery of clinically significant patient trajectories, and (2) counterfactual timing deduction, that is, a \emph{What-If Machine}. Both results are purely data-driven, requiring no prior domain knowledge. LITT further achieves strong performance on timing prediction and survival analysis tasks.

cs.LG↗

arXiv2026

Kinematic enhancement for nucleon interpolators

The reliable treatment of highly boosted hadrons is crucial for many lattice QCD applications. For all these cases the kinematically enhanced interpolators promise very significant improvements and are, therefore, ever more often used in recent calculations, especially for highly boosted mesons like the pion. Motivated by, e.g., the physics program of the future Electron-Ion Collider (EIC) in the US and Electron-Ion collider in China (EIcC), we systematically benchmark our code for the unpolarized isovector nucleon quark matrix elements extracted at large source-sink separations, where excited state artifacts are significantly suppressed. We find that the precision of the renormalized nucleon matrix elements is typically improved by an order of magnitude at momentum $P_z\sim2.5$ GeV. By comparing the results from three CLS ensembles with different lattice spacings $a$ but the same pion mass, we observe no statistically significant dependence on $a$ in the renormalized matrix elements at nearly identical values of $P_z$. These encouraging results suggest that the use of kinematically improved operators is highly advantageous for parton physics calculations and can be extended to a broader class of baryon observables, making them a promising candidate for a standard component of modern lattice QCD.

hep-lat↗

arXiv2026

Movable Antennas for Robust Wireless Sensing via Joint Cramér-Rao Bound and Sidelobe Minimization

This paper presents a novel design approach for movable antenna (MA)-enabled wireless sensing systems by jointly minimizing the Cramér-Rao bound (CRB) and the maximum sidelobe level (MSL) of the ambiguity function via antenna position optimization. In particular, the mean squared error (MSE) of angle-of-arrival (AoA) estimation is decomposed into a local estimation error within the mainlobe of the ambiguity function (i.e., CRB) and an additional ambiguity error caused by its sidelobes. Since the MSE is dominated by the CRB in the high-signal-to-noise ratio (SNR) regime but by the sidelobes of the ambiguity function in the low-SNR regime, our analysis reveals a fundamental trade-off between CRB minimization and MSL minimization in the moderate-SNR regime. Specifically, minimizing the CRB prefers a narrower mainlobe, where antennas are concentrated near the two edges of the one-dimensional (1-D) movement region; whereas minimizing the MSL favors a wider mainlobe, where antennas are distributed more densely near the center of the movement region. Inspired by this and to ensure robust sensing performance across different SNR regimes, we formulate an optimization problem to minimize the CRB subject to a prescribed MSL constraint via antenna position optimization. An efficient successive convex approximation (SCA) algorithm is developed to optimize the antenna position vector (APV), and a 1-D linear search method is proposed to determine the optimal MSL threshold that minimizes the actual MSE for any given SNR. Numerical results demonstrate that the proposed scheme effectively balances the trade-off between MSL and CRB minimization, thus achieving a significantly lower AoA estimation MSE across the entire SNR range compared to conventional uniform and non-uniform fixed-position antenna (FPA) arrays.

cs.IT↗

arXiv2026

CallBench: A Benchmark for Dual-Goal Coordination in Phone Call Assistants

Target-oriented dialogue systems have demonstrated strong capabilities in completing user goals through interactive conversations. However, existing studies are primarily designed for single, explicit goal completion, while phone call assistants face a proxy setting that requires coordinating the device owner's explicit preset goal with the caller's implicit and dynamic goal. We introduce \textsc{CallBench}, a Chinese benchmark for evaluating dual-goal coordination in phone call assistants. \textsc{CallBench} contains 50,000 complete multi-turn phone call dialogues across six scenarios: takeout, delivery, taxi, work, life, and harassment. It covers regular presets, emergent presets, and no-preset cases, and includes diverse relations between owner-side and caller-side goals, such as alignment, complementarity, irrelevance, and conflict. We further design a preset-aware turn-level evaluation protocol covering semantic understanding, context use, active guidance, response quality, preset compliance, dialogue rhythm, and safety. Experiments on representative dialogue methods show that existing approaches still struggle with this task, highlighting the need for phone call assistants that can make reliable turn-level decisions between two independent goals under proxy constraints.

cs.AI↗

arXiv2026

Galactic Diffuse Gamma-Ray and Neutrino Emission from Cosmic-Ray Interactions in Stellar Atmospheres

The Galactic diffuse gamma-ray emission is conventionally modeled as the product of cosmic-ray interactions with the interstellar medium. However, the cumulative contribution of stellar atmospheres acting as hadronic interaction targets remains an unexplored multi-messenger background. In this work, we present the first systematic evaluation of this stellar diffuse emission by coupling MESA stellar evolution profiles and magnetic-field-modulated cosmic-ray transport with a 3D Galactic population synthesis framework. We find that the cumulative stellar contribution to the Galactic diffuse gamma-ray flux is negligible at 1 TeV, and the associated diffuse neutrino flux ($\sim 10^{-16}\;\mathrm{TeV\;cm^{-2}\;s^{-1}\;sr^{-1}}$) remains orders of magnitude below current IceCube limits. Nevertheless, at ultra-high energies ($>10\;\mathrm{TeV}$), this emission establishes an irreducible local background that overtakes the strongly attenuated extragalactic isotropic gamma-ray background. Our results demonstrate that the Galactic stellar ensemble is a strictly sub-dominant background, indicating that stellar subtraction templates are not required for identifying Galactic PeVatrons or constraining dark matter annihilation.

astro-ph.HE↗