arXiv subjects

Jiang Zhu

Publications and source records attributed to Jiang Zhu.

At least 19 recordsLinked to original sources

arXiv2026

An Enhanced MNOMP for Line Spectrum Estimation and Detection

Multisnapshot Newtonized orthogonal matching pursuit (MNOMP) incorporates Newton's method into OMP to avoid the off-grid issues, achieve high accuracy, high resolution and fast line spectrum estimation with multiple measurement vectors. It employs the generalized likelihood ratio test (GLRT) with a constant false alarm rate (CFAR) criterion to determine the number of sinusoids. In this paper, we develop an enhanced MNOMP (EMNOMP) by analyzing the statistical distribution of the exact GLRT statistic. In contrast to MNOMP, which approximates the GLRT by restricting the search to discrete Fourier transform (DFT) grid frequencies, EMNOMP instead solves the GLRT over the continuous frequency domain. The key technical novelty is the derivation of the false alarm probability for this continuous-domain GLRT using chi-squared random field theory and the resulting closed-form threshold via the Lambert W function. The signal-to-noise ratio (SNR) gain of EMNOMP relative to MNOMP is derived and analyzed in depth. Numerical simulations validate the theoretical analysis and the effectiveness of EMNOMP compared to MNOMP.

eess.SP↗

arXiv2026

A MeV-Scale Dark QCD Solution to the Axion Domain Wall Problem

PQ solution to the strong CP problem probably encounters the axion domain wall problem. In this article, we propose a simple and testable solution, assuming that the $U(1)_{\rm PQ}$ possesses mixed anomaly to a hidden $SU(N_c)$ color. Then, the axion field receives a new cosine potential from the hidden instantons, which breaks the $Z_{N_{\rm DW}}$ subgroup explicitly. The new potential lifts the vacua degeneracy, but also drives the effective $\theta$ angle away from the origin, re-incuring the strong CP problem. However, we find that the dark QCD scale within the 0.1 to 3 MeV window survives, maintaining a delicate balance. Two observational signatures are explored: gravitational waves from domain wall collapse, already probed by current PTAs, and di-photon signals from axion-dark-glueball mixing, which require next-generation MeV telescopes. The scenario favors a cold dark QCD sector consistent with dark glueball relic constraints.

hep-ph↗

arXiv2026

HierSVA: A Data Synthesis Pipeline, Dataset, and Benchmark for LLM-Driven Hierarchical Hardware Formal Verification

We present HierSVA, an integrated suite that combines a pipeline, dataset, and benchmark for LLM-driven hierarchical hardware formal verification. HierSVA-SP pairs an RTL preprocessing toolchain with an LLM-in-the-loop formal verification flow to produce reference SystemVerilog Assertions (SVA) on hierarchical RTL. Applying it to BaseJump STL yields HierSVA-DS, a dataset of 342 modules, with hierarchy metadata and depths 0--9, accompanied by a deep subset of 28 module-bug pairs with natural-language specifications and bug variants. HierSVA-B decomposes assertion quality into six metric axes: syntax correctness, assertion proof success rate, vacuity, specification faithfulness, mutation coverage, and formal core coverage. Applying HierSVA-B to twelve recent LLMs reveals three findings. First, the module-level compile rate is 67.1\%; among generated assertions in evaluable runs, 82.1\% prove non-vacuously, but the corresponding assertion sets detect only 70.2\% of eligible injected faults and cover 36.2\% of the formal core. Second, on 211 evaluable model--module entries in the deep subset, assertion sets flag buggy RTL with 0.87 recall, but 40\% of predicted-buggy outcomes are false positives on correct RTL, limiting precision to 0.60. Third, agentic mode improves S1-style provability and strength metrics, but gains plateau and oscillate. Codes and artifacts are available at \href{https://github.com/HierSVAAnon/HierSVACodeAndArtifacts}{https://github.com/HierSVAAnon/HierSVACodeAndArtifacts}. Dataset is available at \href{https://huggingface.co/datasets/AnonymousHierSVA/HierSVA}{https://huggingface.co/datasets/AnonymousHierSVA/HierSVA}.

cs.AR↗

arXiv2026

A novel energy-conservation Crank-Nicolson finite element method for generalized Klein-Gordon-Zakharov equations

This article focuses on an energy-conservation Galerkin finite element method (FEM) for the generalized Klein-Gordon-Zakharov (KGZ) equations. This method combines the bilinear finite element method for spatial discretization with the Crank-Nicolson (CN) scheme for temporal discretization, thereby guaranteeing exact conservation of the discrete energy functional. A rigorous theoretical analysis is devoted to deriving error bounds for the fast-time-scale electronic field $u$ and the ion density deviation $\varphi$. By systematically integrating interpolation estimates, Ritz projection, and a postprocessing technique, the superclose error estimates and global superconvergence are established for $u$ in the $H^1$-norm, even under weakened regularity assumptions on the exact solution. Concurrently, we prove $H^1$-norm superconvergence for the auxiliary variable $\phi$ ($-\Delta\phi = \varphi_t$) and optimal-order $L^2$-norm error estimates for the auxiliary variable $p$ ($p=u_t$) and $\varphi$. Numerical examples are provided to confirm theoretical results.

math.NA↗

arXiv2026

Confinement and Chiral Phase Transitions: The Role of Polyakov Loop Kinetics Terms

We studied a crucial but often oversimplified ingredient in predicting gravitational-wave signals from QCD-type phase transitions: the kinetic term of the Polyakov loop. For the first time, we derive this term from first principles in finite-temperature pure SU(3) Yang-Mills theory, incorporating a field-dependent renormalization factor--a calculation we also extend to theories with more colors. Employing this derived kinetic term alongside three commonly-used effective potentials (the Haar-measure, polynomial, and quasi-particle models), we demonstrate that it substantially modifies the predicted GW energy spectrum from confinement transitions by 1-2 orders of magnitude. Based on this, we provide the first complete analysis of the chiral transition within the Polyakov-Nambu-Jona-Lasinio (PNJL) framework, described by the quark condensate. Our results reveal a clear dichotomy: while the Polyakov-loop kinetic term critically shapes GWs from confinement transitions, it has a negligible impact on the dynamics of the chiral transition, which is dominated by fermion condensation effects.

hep-ph↗

arXiv2025

A Model and Data Dual-driven Approach for Multitargets Detection under Mainlobe Jamming

In modern radar systems, target detection and parameter estimation face significant challenges when confronted with mainlobe jamming. This paper presents a Diffusion-based Model and Data Dual-driven (DMDD) approach to estimate and detect multitargets and suppress structured jamming. In DMDD, the jamming prior is modeled through a score-based diffusion process with its score learned from the pure jamming data, enabling posterior sampling without requiring detailed knowledge of jamming. Meanwhile, the target signal is usually sparse in the range space, which can be modeled via a sparse Bayesian learning (SBL) framework, and hyperparameter is updated through the expectation-maximization (EM) algorithm. A single diffusion process is constructed for the jamming, while the state of targets are estimated through direct posterior inference, enhancing computational efficiency. The noise variance is also estimated through EM algorithm. Numerical experiments demonstrate the effectiveness of the proposed method in structured jamming scenarios. The proposed DMDD algorithm achieves superior target detection performance, compared with existing methods.

eess.SP↗

arXiv2025

BodyWave: Egocentric Body Tracking using mmWave Radars on an MR Headset

Egocentric body tracking, also known as inside-out body tracking (IOBT), is an essential technology for applications like gesture control and codec avatar in mixed reality (MR), including augmented reality (AR) and virtual reality (VR). However, it is more challenging than exocentric body tracking due to the limited view angles of camera-based solutions, which provide only sparse and self-occluded input from head-mounted cameras, especially for lower-body parts. To address these challenges, we propose, BodyWave, an IOBT system based on millimeter-wave (mmWave) radar, which can detect non-line-of-sight. It offers low SWAP+C (size, weight, and power consumption), robustness to environmental and user factors, and enhanced privacy over camera-based solutions. Our prototype, modeled after the Meta Quest 3 form factor, places radars just 4cm away from the face, which significantly advances the practicality of radar-based IOBT. We tackle the sparsity issue of mmWave radar by processing the raw signal into high-resolution range profiles to predict fine-grained 3D coordinates of body keypoints. In a user study with 14 participants and around 500,000 frames of collected data, we achieved a mean per-joint position error (MPJPE) of 9.85 cm on unseen users, 4.94 cm with a few minutes of user calibration, and 3.86 cm in a fully-adapted user-dependent setting. This is comparable to state-of-the-art camera-based IOBT systems, introducing a robust and privacy-preserving alternative for MR applications.

eess.IV↗

arXiv2025

Fast and Efficient Implementation of the Maximum Likelihood Estimation for the Linear Regression with Gaussian Model Uncertainty

The linear regression model with a random variable (RV) measurement matrix, where the mean of the random measurement matrix has full column rank, has been extensively studied. In particular, the quasiconvexity of the maximum likelihood estimation (MLE) problem was established, and the corresponding Cramer-Rao bound (CRB) was derived, leading to the development of an efficient bisection-based algorithm known as RV-ML. In contrast, this work extends the analysis to both overdetermined and underdetermined cases, allowing the mean of the random measurement matrix to be rank-deficient. A remarkable contribution is the proof that the equivalent MLE problem is convex and satisfies strong duality, strengthening previous quasiconvexity results. Moreover, it is shown that in underdetermined scenarios, the randomness in the measurement matrix can be beneficial for estimation under certain conditions. In addition, a fast and unified implementation of the MLE solution, referred to as generalized RV-ML (GRV-ML), is proposed, which handles a more general case including both underdetermined and overdetermined systems. Extensive numerical simulations are provided to validate the theoretical findings.

eess.SP↗

arXiv2025

Unbiased Evaluation of Large Language Models from a Causal Perspective

Benchmark contamination has become a significant concern in the LLM evaluation community. Previous Agents-as-an-Evaluator address this issue by involving agents in the generation of questions. Despite their success, the biases in Agents-as-an-Evaluator methods remain largely unexplored. In this paper, we present a theoretical formulation of evaluation bias, providing valuable insights into designing unbiased evaluation protocols. Furthermore, we identify two type of bias in Agents-as-an-Evaluator through carefully designed probing tasks on a minimal Agents-as-an-Evaluator setup. To address these issues, we propose the Unbiased Evaluator, an evaluation protocol that delivers a more comprehensive, unbiased, and interpretable assessment of LLMs.Extensive experiments reveal significant room for improvement in current LLMs. Additionally, we demonstrate that the Unbiased Evaluator not only offers strong evidence of benchmark contamination but also provides interpretable evaluation results.

cs.AI↗

arXiv2025

The Fourth Monocular Depth Estimation Challenge

This paper presents the results of the fourth edition of the Monocular Depth Estimation Challenge (MDEC), which focuses on zero-shot generalization to the SYNS-Patches benchmark, a dataset featuring challenging environments in both natural and indoor settings. In this edition, we revised the evaluation protocol to use least-squares alignment with two degrees of freedom to support disparity and affine-invariant predictions. We also revised the baselines and included popular off-the-shelf methods: Depth Anything v2 and Marigold. The challenge received a total of 24 submissions that outperformed the baselines on the test set; 10 of these included a report describing their approach, with most leading methods relying on affine-invariant predictions. The challenge winners improved the 3D F-Score over the previous edition's best result, raising it from 22.58% to 23.05%.

cs.CV↗

arXiv2025

Bubble wall velocity from Kadanoff-Baym equations: fluid dynamics and microscopic interactions

We establish a first principles, systematic framework for determining the bubble wall velocity during a first order cosmological phase transition. This framework, based on non-local Kadanoff-Baym equations, incorporates both macroscopic fluid dynamics and microscopic interactions between the bubble wall and particles in the plasma. Previous studies have generally focused on one of these two sources of friction pressure that govern the wall velocity. As a precursor, we utilize background field quantum field theory to obtain the relevant local Boltzmann equations, from which we derive the forces associated with variation of particle masses across the bubble wall and the microscopic wall-particle interactions. We subsequently show how these equations emerge from the Kadanoff-Baym framework under various approximations. We apply this framework in the ballistic regime to compute the new friction force arising from the $2\rightarrow 2$ scattering processes in scalar field theory. We obtain a linear relationship between this force and the Lorentz factor $\gamma_w$ that would preclude runaway bubbles with such effects.

hep-ph↗

arXiv2025

Numerical simulation of wormhole propagation with the mixed hybridized discontinuous Galerkin finite element method

The acid treatment of carbonate reservoirs is a widely employed technique for enhancing the productivity of oil and gas reservoirs. In this paper, we present a novel combined hybridized mixed discontinuous Galerkin (HMDG) finite element method to simulate the dissolution process near the wellbore, commonly referred to as the wormhole phenomenon. The primary contribution of this work lies in the application of hybridization techniques to both the pressure and concentration equations. Additionally, an upwind scheme is utilized to address convection-dominant scenarios, and a ``cut-off" operator is introduced to maintain the boundedness of porosity. Compared to traditional discontinuous Galerkin methods, the proposed approach results in a global system with fewer unknowns and sparser stencils, thereby significantly reducing computational costs. We analyze the existence and uniqueness of the new combined method and derive optimal error estimates using the developed technique. Numerical examples are provided to validate the theoretical analysis.

math.NA↗

arXiv2025

Expectation Propagation based Line Spectral Estimation

The fundamental problem of line spectral estimation (LSE) using the expectation propagation (EP) method is studied. Previous approaches estimate the model order sequentially, limiting their practical utility in scenarios with large dimensions of measurements and signals. To overcome this limitation, a bilinear generalized LSE (BiG-LSE) method that concurrently estimates the model order is developed. The key concept involves iteratively approximating the original nonlinear model as a bilinear model through Taylor series expansion, with EP employed for inference. To mitigate computational complexity, the posterior log-pdfs are approximated to reduce the number of messages. BiG-LSE automatically determines the model order, noise variance, provides uncertainty levels for the estimates, and adeptly handles nonlinear measurements. Based on the BiG-LSE, a variant employing the von Mises distribution for the frequency is developed, which is suitable for sequential estimation. Numerical experiments and real data are used to demonstrate that BiG-LSE achieves estimation accuracy comparable to current methods.

cs.IT↗

arXiv2025

VacuumTunneling: A package to solve bounce equation with renormalization factor

The Vacuum tunneling rate $Γ$ from the effective action is a key to studying the cosmological first-order phase transition(FOPT). One solid way to compute the $Γ$ is to start with the derivative expansion of the effective action and solve the bounce equation numerically. In this process, the renormalization factor $Z$ of the tunneling field may play a center rule, which is not considered in existing packages. Therefore, we present a \texttt{Mathematica} package \vt to compute the bounce action with or without the renormalization factor. Applying the \vt package, we find that the presence of $Z$ has a significant impact on the action, as well on the tunneling path. We provide some concrete examples to demonstrate the difference between the solution with and without the renormalization factor, both in the action and tunneling path. This package is based on the modified shooting and path deformation method. We also made some optimizations for the super-cooling phase transition(thick wall scenario), in which other numerical package works poorly. This package works as long as the expressions can give values of the potential and the renormalization at a certain field point. This means the input potential and the renormalization can be merely numerical quantities without analytical expressions. The computation time can be as short as 1 second in single-field tunneling and several seconds in multi-field cases.

hep-ph↗

arXiv2025

Dark Chiral Phase Transition Driven by Chemical Potential and its Gravitational Wave Test

In this article, for the first time, we explore the scenario that the dark-QCD sector has a large chemical potential $μ$ (on the order of magnitude of temperature) of dark quarks. It leads to a complex-valued Polyakov loop and tilts the partial confinement effect, driving the dark-QCD phase transition to a first-order one in the early universe. We present a toy model via the Affleck-Dine mechanism that could generate degenerate dark quarks. Our study, in the framework of PNJL, focuses on the dynamical impacts of a large chemical potential on the chiral phase transition without turning on the KMT instanton term. We plot the phase diagram of the dark-QCD in the chiral limit. The resulting first-order phase transition actually refers to a chiral phase transition, with the transition to the confinement vacuum being a cross-over. Following the phase diagram, we find that increasing $μ$ can considerably prolong the duration of the phase transition and also the release of latent heat, which together make the cosmic dark-QCD phase transition at the critical temperature above 1 GeV and below 100 GeV produce gravitational wave signal in the intermediate frequency band, which is well probable in space detectors such as BBO

hep-ph↗

arXiv2025

Confinement Bubble Wall Velocity via Quasiparticle Determination

Lattice simulations reveal that the deconfinement-confinement (D-C) phase transition (PT) of the hot pure $SU(N>2)$ Yang-Mills system is first order. This system can be described by a pool of quasigluons moving in the Polyakov loop background, and in this picture, we establish an effective distribution function for quasigluons, which encodes interactions among quasigluons and in particular the confinement effect. With it, we made the first attempt to calculate the confinement bubble wall velocity $v_w$ at the microscopical level, and we obtained a small velocity $v_w\sim 0.04$ using two different approaches, which is qualitatively consistent with others results like holography.

hep-ph↗

arXiv2024

Joint Multitarget Detection and Tracking with mmWave Radar

Accurate targets detection and tracking with mmWave radar is a key sensing capability that will enable more intelligent systems, create smart, efficient, automated system. This paper proposes an end-to-end detection-estimation-track framework named MNOMP-SPA-KF consisting of the target detection and estimation module, the data association (DA) module and the target tracking module. In the target estimation and detection module, a low complexity, super-resolution and constant false alarm rate (CFAR) based two dimensional multisnapshot Newtonalized orthogonal matching pursuit (2D-MNOMP) is designed to extract the multitarget's radial distances and velocities, followed by the conventional (Bartlett) beamformer to extract the multitarget's azimuths. In the DA module, a sum product algorithm (SPA) is adopted to obtain the association probabilities of the existed targets and measurements by incorporating the radial velocity information. The Kalman filter (KF) is implemented to perform target tracking in the target tracking module by exploiting the asymptotic distribution of the estimators. To improve the detection probability of the weak targets, extrapolation is also coupled into the MNOMP-SPA-KF. Numerical and real data experiments demonstrate the effectiveness of the MNOMP-SPA-KF algorithm, compared to other benchmark algorithms.

eess.SP↗

arXiv2024

Gaze Label Alignment: Alleviating Domain Shift for Gaze Estimation

Gaze estimation methods encounter significant performance deterioration when being evaluated across different domains, because of the domain gap between the testing and training data. Existing methods try to solve this issue by reducing the deviation of data distribution, however, they ignore the existence of label deviation in the data due to the acquisition mechanism of the gaze label and the individual physiological differences. In this paper, we first point out that the influence brought by the label deviation cannot be ignored, and propose a gaze label alignment algorithm (GLA) to eliminate the label distribution deviation. Specifically, we first train the feature extractor on all domains to get domain invariant features, and then select an anchor domain to train the gaze regressor. We predict the gaze label on remaining domains and use a mapping function to align the labels. Finally, these aligned labels can be used to train gaze estimation models. Therefore, our method can be combined with any existing method. Experimental results show that our GLA method can effectively alleviate the label distribution shift, and SOTA gaze estimation methods can be further improved obviously.

cs.CV↗