arXiv subjects

Wei Hong

Publications and source records attributed to Wei Hong.

At least 37 records · Page 2Linked to original sources

arXiv2025

A Novel Multi-Reference-Point Modeling Framework for Monostatic Background Channel: Toward 3GPP ISAC Standardization

Integrated Sensing and Communication (ISAC) has been identified as a key 6G application by ITU and 3GPP. A realistic, standard-compatible channel model is essential for ISAC system design. To characterize the impact of Sensing Targets (STs), 3GPP defines ISAC channel as a combination of target and background channels, comprising multipath components related to STs and those originating solely from the environment, respectively. Although the background channel does not carry direct ST information, its accurate modeling is critical for evaluating sensing performance, especially in complex environments. Existing communication standards characterize propagation between separated transmitter (Tx) and receiver (Rx). However, modeling background channels in the ISAC monostatic mode, where the Tx and Rx are co-located, remains a pressing challenge. In this paper, we firstly conduct ISAC monostatic background channel measurements for an indoor scenario at 28 GHz. Realistic channel parameters are extracted, revealing pronounced single-hop propagation and discrete multipath distribution. Inspired by these properties, a novel stochastic model is proposed to characterizing the ISAC monostatic background channel as the superposition of sub-channels between the monostatic Tx&Rx and multiple communication Rx-like Reference Points (RPs). This model is compatible with standardizations, and a 3GPP-extended implementation framework is introduced. Finally, a genetic algorithm-based method is proposed to extract the optimal number and placement of multi-RPs. The optimization approach and modeling framework are validated by comparing measured and simulated channel parameters. Results demonstrate that the proposed model effectively captures monostatic background channel characteristics, addresses a critical gap in ISAC channel modeling, and supports 6G standardization.

eess.SP↗

arXiv2025

DATA: Domain-And-Time Alignment for High-Quality Feature Fusion in Collaborative Perception

Feature-level fusion shows promise in collaborative perception (CP) through balanced performance and communication bandwidth trade-off. However, its effectiveness critically relies on input feature quality. The acquisition of high-quality features faces domain gaps from hardware diversity and deployment conditions, alongside temporal misalignment from transmission delays. These challenges degrade feature quality with cumulative effects throughout the collaborative network. In this paper, we present the Domain-And-Time Alignment (DATA) network, designed to systematically align features while maximizing their semantic representations for fusion. Specifically, we propose a Consistency-preserving Domain Alignment Module (CDAM) that reduces domain gaps through proximal-region hierarchical downsampling and observability-constrained discriminator. We further propose a Progressive Temporal Alignment Module (PTAM) to handle transmission delays via multi-scale motion modeling and two-stage compensation. Building upon the aligned features, an Instance-focused Feature Aggregation Module (IFAM) is developed to enhance semantic representations. Extensive experiments demonstrate that DATA achieves state-of-the-art performance on three typical datasets, maintaining robustness with severe communication delays and pose errors. The code will be released at https://github.com/ChengchangTian/DATA.

cs.CV↗

arXiv2025

Theoretical Radio Signals from Radio-Band Gravitational Waves Converted from the Neutron Star Magnetic Field

Gravitational waves (GWs) can convert into electromagnetic waves in the presence of a magnetic field via the Gertsenshtein-Zeldovich (GZ) effect. The characteristics of the magnetic field substantially affect this conversion probability. This paper confirms that strong magnetic fields in neutron stars significantly enhance the conversion probability, facilitating detectable radio signatures of very high-frequency (VHF, $\left(10^6-10^{11}\mathrm{~Hz}\right)$) gravitational waves. We theoretically identify two distinct signatures using single-dish telescopes (FAST, TMRT, QTT, GBT) and interferometers (SKA1/2-MID): transient signals from burst-like gravitational wave sources and persistent signals from cosmological background gravitational wave sources. These signatures are mapped to graviton spectral lines derived from quantum field theory by incorporating spin-2 and mass constraints, resulting in smooth, featureless profiles that are critical for distinguishing gravitational wave signals from astrophysical foregrounds. FAST attains a characteristic strain bound of $h_c<10^{-23}$, approaching $10^{-24}$ in the frequency range of $1-3\mathrm{~GHz}$ with a 6-hour observation period. This performance exceeds the $5 σ$ detection thresholds for GWs originating from primordial black holes (PBHs) and nears the limits set by Big Bang nucleosynthesis. Additionally, projections for SKA2-MID indicate even greater sensitivity. Detecting such gravitational waves would improve our comprehension of cosmological models, refine the parameter spaces for primordial black holes, and function as a test for quantum field theory. This approach addresses significant deficiencies in VHF GW research, improving detection sensitivity and facilitating the advancement of next-generation radio telescopes such as FASTA and SKA, which feature larger fields of view and enhanced gain.

astro-ph.HE↗

arXiv2025

Mean Field Stochastic Partial Differential Equations with Nonlinear Kernels

This work focuses on the mean field stochastic partial differential equations with nonlinear kernels. We first prove the existence and uniqueness of strong and weak solutions for mean field stochastic partial differential equations in the variational framework, then establish the convergence (in certain Wasserstein metric) of the empirical laws of interacting systems to the law of solutions of mean field equations, as the number of particles tends to infinity. The main challenge lies in addressing the inherent interplay between the high nonlinearity of operators and the non-local effect of coefficients that depend on the measure. In particular, we do not need to assume any exponential moment control condition of solutions, which extends the range of the applicability of our results. As applications, we first study a class of finite-dimensional interacting particle systems with polynomial kernels, which are commonly encountered in fields such as the data science and the machine learning. Subsequently, we present several illustrative examples of infinite-dimensional interacting systems with nonlinear kernels, such as the stochastic climate models, the stochastic Allen-Cahn equations, and the stochastic Burgers type equations.

math.PR↗

arXiv2025

Interleaved Transceiver Design for a Continuous- Transmission MIMO-OFDM ISAC System

This paper proposes an interleaved transceiver design method for a multiple-input multiple-output (MIMO) integrated sensing and communication (ISAC) system utilizing orthogonal frequency division multiplexing (OFDM) waveforms. We consider a continuous transmission system and focus on the design of the transmission signal and a receiving filter in the time domain for an interleaved transmission architecture. For communication performance, constructive interference (CI) is integrated into the optimization problem. For radar sensing performance, the integrated mainlobe-to-sidelobe ratio (IMSR) of the beampattern is considered to ensure desirable directivity. Additionally, we tackle the challenges of inter-block interference and eliminate the spurious peaks, which are crucial for accurate target detection. Regarding the hardware implementation aspect, the power of each time sample is constrained to manage the peak-to-average power ratio (PAPR). The design problem is addressed using an alternating optimization (AO) framework, with the subproblem for transmitted waveform design being solved via the successive convex approximation (SCA) method. To further enhance computational efficiency, the alternate direction penalty method (ADPM) is employed to solve the subproblems within the SCA iterations. The convergence of ADPM is established, with convergence of the case of more than two auxiliary variables being established for the first time. Numerical simulations validate the effectiveness of our transceiver design in achieving desirable performance in both radar sensing and communication, with the fast algorithm achieving comparable performance with greater computational efficiency.

eess.SP↗

arXiv2025

McKean-Vlasov Stochastic Partial Differential Equations: Existence, Uniqueness and Propagation of Chaos

In this paper, we provide a general framework for investigating McKean-Vlasov stochastic partial differential equations. We first show the existence of weak solutions by combining the localizing approximation, Faedo-Galerkin technique, compactness method and the Jakubowski version of the Skorokhod representation theorem. Then under certain locally monotone condition we further investigate the existence and uniqueness of (probabilistically) strong solutions. The applications of the main results include a large class of McKean-Vlasov stochastic partial differential equations such as stochastic 2D/3D Navier-Stokes equations, stochastic Cahn-Hilliard equations and stochastic Kuramoto-Sivashinsky equations. Finally, we show a propagation of chaos result in Wasserstein distance for weakly interacting stochastic 2D Navier-Stokes systems.

math.PR↗

arXiv2025

Generalized Yosida Approximation and Multi-Valued Stochastic Evolution Inclusions

In this paper, we generalize the classical Yosida approximation by utilizing a nonstandard duality mapping to establish the existence and uniqueness of both (probabilistically) weak and strong solutions and demonstrate the continuous dependence on initial values for a class of multi-valued stochastic evolution inclusions within the variational framework. Furthermore, leveraging this generalized Yosida approximation, we derive the finite-time extinction of solutions with probability one and also provide an explicit upper bound of the moment of extinction time for multi-valued stochastic evolution inclusions perturbed by linear multiplicative noise. The main results are applicable to various examples, including multi-valued stochastic porous media equations, stochastic $Φ$-Laplace equations and stochastic evolution inclusions involving subdifferentials.

math.PR↗

arXiv2025

Probing Millikelvin Temperature Sensitivity in Chiral Nanoparticles via Optical Forces

With increasing interest in utilizing nanostructures as nanoscale heat sources, the ability to precisely measure photothermal effects at the nanoscale has become increasingly significant. Techniques based on fluorescence or Raman signals often suffer from challenges in accurate calibration, far-field imaging methods are limited by diffraction-limited spatial resolution, and electron microscopy requires vacuum conditions, restricting in situ applicability. In contrast, tip-based measurement techniques offer sub-diffraction spatial resolution under ambient conditions, making them well-suited for nanoscale photothermal mapping. In this study, we employ tip-based optical force nanoscopy combined with phase-informed decomposition to investigate the origin of the photothermal force, enable nanoscale mapping, and evaluate temperature sensitivity. Our system achieves a temperature sensitivity of approximately 0.1 K without necessitating an additional temperature-sensitive layer. We anticipate that our approach has the potential to serve as a versatile platform for investigating localized thermal effects in fields such as semiconductors, nanophotonics, and photocatalysis.

physics.optics↗

arXiv2025

Polarization Properties of the Electromagnetic Response to High-frequency Gravitational Wave

Electromagnetic waves (EMWs) can be generated by gravitational waves (GWs) within a magnetic field via the Gertsenshtein effect. The conversion probability between GWs and EMWs can be enhanced by inhomogeneities in the electron density and magnetic field within the magnetized plasma of both the Milky Way (MW) and the intergalactic medium in the expanding Universe. Polarized GWs can induce polarized EMWs, and the polarization properties of these EMWs can be altered by Faraday rotation as they propagate through magnetized plasma. Additionally, the polarization intensity of the EMWs may be weakened due to depolarization effects. In this study, we calculate the enhanced GW-EMW conversion in inhomogeneous magnetized plasma during the propagation of GWs through the Universe and our galaxy. We analyze the polarization states of the EMWs generated by polarized GWs and discuss the depolarization effects induced by the medium's irregularities, as well as the differential Faraday rotation occurring in multilayer polarized radiation. Our work provides alternative methods for detecting GWs and exploring their polarization states, and potentially constraining the parameters of the possible GW sources, especially the primordial black hole, contributing to the advancement of very-high-frequency GW detection and research.

astro-ph.CO↗

arXiv2025

Twist-2 distribution amplitudes of $a_{0}(980)$ and $a_{0}(1450)$

We investigate the twist-2 distribution amplitudes of the scalar mesons $a_{0}(980)$ and $a_{0}(1450)$ in the two-quark picture. The moments of these scalar mesons are obtained up to the third order with QCD sum rules method. With these moments, the first two Gegenbauer coefficients are determined and utilized to analyze the twist-2 distribution amplitudes. Our numerical results indicate that the meson $a_{0}(980)$ favors a conventional two-quark ground state. The paper concludes with an examination of the form factors for the transitions $B/D\rightarrow a_{0}$.

hep-ph↗

arXiv2025

Progress of the TianQin project

TianQin is a future space-based gravitational wave observatory targeting the frequency window of $10^{-4}$ Hz $\sim 1$ Hz. A large variety of gravitational wave sources are expected in this frequency band, including the merger of massive black hole binaries, the inspiral of extreme/intermediate mass ratio systems, stellar-mass black hole binaries, Galactic compact binaries, and so on. TianQin will consist of three Earth orbiting satellites on nearly identical orbits with orbital radii of about $10^5$ km. The satellites will form a normal triangle constellation whose plane is nearly perpendicular to the ecliptic plane. The TianQin project has been progressing smoothly following the ``0123" technology roadmap. In step ``0", the TianQin laser ranging station has been constructed and it has successfully ranged to all the five retro-reflectors on the Moon. In step ``1", the drag-free control technology has been tested and demonstrated using the TianQin-1 satellite. In step ``2", the inter-satellite laser interferometry technology will be tested using the pair of TianQin-2 satellites. The TianQin-2 mission has been officially approved and the satellites will be launched around 2026. In step ``3", i.e., the TianQin-3 mission, three identical satellites will be launched around 2035 to form the space-based gravitational wave detector, TianQin, and to start gravitational wave detection in space.

gr-qc↗

arXiv2024

HGSFusion: Radar-Camera Fusion with Hybrid Generation and Synchronization for 3D Object Detection

Millimeter-wave radar plays a vital role in 3D object detection for autonomous driving due to its all-weather and all-lighting-condition capabilities for perception. However, radar point clouds suffer from pronounced sparsity and unavoidable angle estimation errors. To address these limitations, incorporating a camera may partially help mitigate the shortcomings. Nevertheless, the direct fusion of radar and camera data can lead to negative or even opposite effects due to the lack of depth information in images and low-quality image features under adverse lighting conditions. Hence, in this paper, we present the radar-camera fusion network with Hybrid Generation and Synchronization (HGSFusion), designed to better fuse radar potentials and image features for 3D object detection. Specifically, we propose the Radar Hybrid Generation Module (RHGM), which fully considers the Direction-Of-Arrival (DOA) estimation errors in radar signal processing. This module generates denser radar points through different Probability Density Functions (PDFs) with the assistance of semantic information. Meanwhile, we introduce the Dual Sync Module (DSM), comprising spatial sync and modality sync, to enhance image features with radar positional information and facilitate the fusion of distinct characteristics in different modalities. Extensive experiments demonstrate the effectiveness of our approach, outperforming the state-of-the-art methods in the VoD and TJ4DRadSet datasets by $6.53\%$ and $2.03\%$ in RoI AP and BEV AP, respectively. The code is available at https://github.com/garfield-cpp/HGSFusion.

cs.CV↗

arXiv2024

Charge management system based on disturbance observer sliding mode control for space inertial sensors

Precision space inertial sensors are imperative for Earth geodesy missions, gravitational wave observations, and fundamental physics experiments in space. In these missions, free-falling test masses(TMs) are susceptible to parasitic electrostatic forces and torques, with significant contributions from the interaction between stray electric fields and TM charge. These effects can make up a sizable fraction of the noise budget. Thus, a charge management system(CMS) is essential in high-precise space-based missions. However, the operating environment for space charge control is full of uncertainties and disturbances. TM charge tracking precision is negatively affected by many physical parameters such as external charging rate, quantum yield, UV light power, etc. Those parameters are rarely measured and supposed to vary because of changes in solar activity, temperature, aging of electronic components and so on. The unpredictability and variability of these parameters affects the CMS performance in long-term space missions and must be evaluated or eliminated. This paper presents a simple physics-based model of the discharging process with high charging/discharging rate based on the geometry of inertial sensors. After that, a disturbance observer sliding mode control (DOSMC) is proposed for the CMS with parametric uncertainties and unknown disturbance to maintain the TM charge below a certain level and improve its robustness. The simulation results show that the DOSMC is able to force the system trajectory coincides with the sliding line, which depends neither on the parameters or disturbances. In this way, the DOSMC can effectively ignore the parameter perturbation and external disturbances. The control precision can reach 0.1 mV, which is superior to that of a classic proportional-integral-derivative controller and conventional sliding mode control.

physics.ins-det↗

arXiv2024

Multi-Scale McKean-Vlasov SDEs: Moderate Deviation Principle in Different Regimes

The main aim of this paper is to study the moderate deviation principle for McKean-Vlasov stochastic differential equations with multiple scales. Specifically, we are interested in the asymptotic estimates of the deviation processes $\frac{X^δ-\bar{X}}{λ(δ)}$ as $δ\to 0$ in different regimes (i.e. $\varepsilon=o(δ)$ and $\varepsilon=O(δ)$), where $δ$ stands for the intensity of the noise and $\varepsilon:=\varepsilon(δ)$ stands for the time scale separation. The rate functions in two regimes are different, in particular, we show that it is strongly affected by the noise of the fast component in latter regime, which is essentially different from the former one and the case of large deviations (cf. \cite{HLLS}). As a by-product, the explicit representation formulas of the rate functions in all of regimes are also given. The main techniques are based on the weak convergence approach and the functional occupation measure approach.

math.PR↗

arXiv2024

A Stochastic Approach to Reconstructing the Speed of Light in Cosmology

The Varying Speed of Light (VSL) model describes how the speed of light in a vacuum changes with cosmological redshift. Despite numerous models, there is little observational evidence for this variation. While the speed of light can be accurately measured by physical means, cosmological methods are rarely used. Previous studies quantified the speed of light at specific redshifts using Gaussian processes and reconstructed the redshift-dependent function $c(z)$. It is crucial to quantify the speed of light across varying redshifts. We use the latest data on angular diameter distances $D_A(z)$ and Hubble parameters $H(z)$ from baryon acoustic oscillation (BAO) and cosmic chronometer measurements in the redshift interval $z\in[0.07,1.965]$. The speed of light $c(z)$ is determined using Gaussian and deep Gaussian processes to reconstruct $H(z)$, $D_A(z)$, and $D^{\prime}_A(z)$. Furthermore, we conduct comparisons across three distinct models, encompassing two renowned VSL models. We get the result of the parameters constraints in the models (1) for the ``$c$-c" model, $c_0=29492.6 \pm^{6.2}_{5.3} \mathrm{~km} \mathrm{~s}^{-1}$. (2) For the ``$c$-cl" model, $c_0=29665.5 \pm^{11.2}_{11.4}\mathrm{~km} \mathrm{~s}^{-1}$ and $n=0.05535 \pm^{0.00008}_{0.00007}$. (3) For the ``$c$-CPL" model, $c_0=29555.7 \pm^{13.3}_{13.2} \mathrm{~km} \mathrm{~s}^{-1}$ and $n=-0.0607 \pm 0.0001$. Based on our findings, it may be inferred that Barrow's classical VSL model is not a suitable fit for our data. In contrast, the widely recognized Chevallier-Polarski-Linder (CPL) VSL model, under some circumstances, as well as the universal ``c is constant" model, demonstrate a satisfactory ability to account for our findings.

astro-ph.CO↗

arXiv2024

Identifying Black Holes Through Space Telescopes and Deep Learning

The EHT has captured a series of images of black holes. These images could provide valuable information about the gravitational environment near the event horizon. However, accurate detection and parameter estimation for candidate black holes are necessary. This paper explores the potential for identifying black holes in the ultraviolet band using space telescopes. We establish a data pipeline for generating simulated observations and present an ensemble neural network model for black hole detection and parameter estimation. The model achieves mean average precision [0.5] values of 0.9176 even when reaching the imaging FWHM ($θ_c$) and maintains the detection ability until $0.54θ_c$. The parameter estimation is also accurate. These results indicate that our methodology enables super-resolution recognition. Moreover, the model successfully detects the shadow of M87* from background noise and other celestial bodies and estimates its inclination and positional angle. Our work demonstrates the feasibility of detecting black holes in the ultraviolet band and provides a new method for black hole detection and further parameter estimation.

astro-ph.IM↗

arXiv2024

Proprioceptive Learning with Soft Polyhedral Networks

Proprioception is the "sixth sense" that detects limb postures with motor neurons. It requires a natural integration between the musculoskeletal systems and sensory receptors, which is challenging among modern robots that aim for lightweight, adaptive, and sensitive designs at a low cost. Here, we present the Soft Polyhedral Network with an embedded vision for physical interactions, capable of adaptive kinesthesia and viscoelastic proprioception by learning kinetic features. This design enables passive adaptations to omni-directional interactions, visually captured by a miniature high-speed motion tracking system embedded inside for proprioceptive learning. The results show that the soft network can infer real-time 6D forces and torques with accuracies of 0.25/0.24/0.35 N and 0.025/0.034/0.006 Nm in dynamic interactions. We also incorporate viscoelasticity in proprioception during static adaptation by adding a creep and relaxation modifier to refine the predicted results. The proposed soft network combines simplicity in design, omni-adaptation, and proprioceptive sensing with high accuracy, making it a versatile solution for robotics at a low cost with more than 1 million use cycles for tasks such as sensitive and competitive grasping, and touch-based geometry reconstruction. This study offers new insights into vision-based proprioception for soft robots in adaptive grasping, soft manipulation, and human-robot interaction.

cs.RO↗

arXiv2024

Actuation system of the inertial sensor for high-precision space missions using torsion pendulum

Precision space inertial sensors are imperative to Earth geodesy missions, gravitational wave observations and several fundamental physics experiments in space. In these missions, the residual acceleration noise of the test mass(TM) caused by the forces from inertial sensor components and environment is supposed to be kept below a certain level. As a number of forces contributing to residual acceleration are related to actuation system, developing a precise actuation system to exclude any erroneous force and obtain an ultra sensitive value for TM acceleration noise is necessary and essential. However, it is difficult to test the actuation system on ground. In this paper, a torsion pendulum is established to test the influence of actuation system on TM torque noise and a closed-loop control system combined torsion pendulum and parts of actuation modules is designed to assess the performance of actuation control algorithm. The experimental results show that the parameters in an actuation system will introduce additional torque noise and the maximum noise can reach as much as 10^{-13}Nm /Hz^{1/2} at 1 mHz. The stable tracking error for the closed-loop system is about 10^{-7}, indicating that the combination system achieves good tracking performance and robustness for TM rotation control in different conditions of inertial sensors.

physics.space-ph↗