arXiv subjects

Weihua Wang

Publications and source records attributed to Weihua Wang.

At least 19 recordsLinked to original sources

arXiv2026

The Roadmap of Inorganic Computational Materials Databases: Capabilities, Credibility, Coverage, and the Open Frontier

Computational materials databases have become central infrastructure for data-driven discovery of inorganic materials, yet their growth remains strikingly uneven across property families. This perspective synthesizes a systematic survey of mainstream density functional theory (DFT) software, the computational cost and credibility of nineteen material-property families, and the coverage of existing computational databases, into a coherent picture of where the field stands and where it should go. We show that the ecosystem of first-principles codes is methodologically mature: for nearly every property of technological interest, at least one production-grade code can compute it.The binding constraint is no longer methodological capability but the economics of trust - which properties can be computed cheaply enough, and accurately enough, to be harvested at database scale. Mapping database coverage onto a Gartner-style readiness cycle reveals a sharp divide: ground-state structure, energetics, elasticity, and topology have reached routine production, while nine property families - including NMR/EPR parameters, core-level spectra, electron-phonon properties, thermal conductivity, and quantum transport - remain without any systematic computational database. We argue that these blank zones define the scientific opportunity of the next decade, and we propose a three-horizon roadmap: consolidating coverage and interoperability in the near term, industrializing mid-cost properties through surrogate-accelerated workflows in the medium term, and conquering the high-cost frontier through machine-learned interatomic potentials, autonomous computing infrastructure, and community governance in the long term.

cond-mat.mtrl-sci↗

arXiv2026

Super4DR: 4D Radar-centric Self-supervised Odometry and Gaussian-based Map Optimization

Conventional odometry and mapping methods using visual or LiDAR data often struggle under poor illumination and adverse weather conditions. Although 4D radar is suited for such environments, its sparse and noisy point clouds hinder accurate odometry estimation, while the radar maps suffer from obscure and incomplete structures. Thus, we propose Super4DR, a 4D radar-centric framework for learning-based odometry estimation and gaussian-based map optimization. First, we design a cluster-aware odometry network that incorporates object-level cues from the clustered radar points for inter-frame matching, alongside a hierarchical self-supervision mechanism to overcome outliers through spatio-temporal consistency, knowledge transfer, and feature contrast. Second, we propose using 3D gaussians as an intermediate representation, coupled with a radar-specific growth strategy, selective separation, and multi-view regularization, to recover blurry map areas and those undetected based on image texture. Experiments show that Super4DR achieves a 67% performance gain over prior self-supervised methods, nearly matches supervised odometry, and narrows the map quality disparity with LiDAR while enabling multi-modal image rendering.

cs.RO↗

arXiv2026

Writing and erasing skyrmions by single ultrafast laser pulses in monolayer Janus 2D magnets

Skyrmions in 2D magnets are promising candidates for nonvolatile, low-power, and high-density spintronic memories. However, their experimental realization at the 2D limit remains challenging, owing to the difficulty in engineering the required chiral magnetic interactions. Here, we report the creation and direct imaging of Néel-type skyrmions in Janus 2D chromium chalcogenides using synchrotron X-ray photoemission electron microscopy, and scanning nitrogen-vacancy magnetometry, which exhibit field-free stability, nonvolatility, and size tunability. First-principles calculations and micromagnetic simulations reveal that Janus-surface-induced inversion-symmetry breaking enhances the Dzyaloshinskii-Moriya interaction, providing the microscopic mechanism for skyrmion stabilization and tunability. We further achieve reversible skyrmion writing and erasing using a single ultrafast laser pulse in a magnetic field as low as 300 Oe, demonstrating the excellent manipulability of this 2D magnetic system. These results establish Janus engineering as a route to creating and manipulating nonvolatile skyrmions in atomically thin magnets, with implications for skyrmion-based low-power spintronic devices.

cond-mat.mtrl-sci↗

arXiv2026

Central Equations and Band Structures of Linear Magnetohydrodynamic Waves in a Magneto-Lattice

We investigate the band structures and propagation properties of linear ideal magnetohydrodynamic (MHD) waves in a plasma with a spatially periodic background magnetic field (a magneto-lattice ). We develop a plane-wave expansion approach in two equivalent forms: one written using the usual linearized MHD perturbation variables and another written in terms of the fluid displacement. We validate both formulations with numerical tests, including an empty-lattice limit that recovers the uniform-plasma dispersion. The method enables efficient computation of dispersion relations and reveals intrinsic frequency band gaps and cutoff behavior caused by magnetic periodicity. We show that the band gap width increases with the amplitude of the periodic magnetic-field modulation (relative to the uniform background field), leading to suppression of selected wave modes. In addition, the magnetic periodicity splits the Alfvén continuum into multiple branches, a feature absent in uniform plasmas. These results provide a framework for tailoring MHD wave propagation in structured plasmas and may be useful for future studies of plasma metamaterials and topological plasma waves.

physics.plasm-ph↗

arXiv2026

Liouville Type Theorem for the Steady Fractional Compressible MHD Equations in $\mathbb{R}^{3}$

This paper is concerned with the Liouville-type problem for the stationary fractional compressible magnetohydrodynamics (MHD) equations. The main difficulty comes from the nonlocal fractional Laplace operator $(-Δ)^s$. To overcome it, we combine the Caffarelli-Silvestre extension technique with truncation arguments. Under suitable regularity and decay conditions, we prove that the only solution is trivial, establishing a Liouville-type theorem.

math.AP↗

arXiv2026

Wisteria: A Unified Multi-Scale Feature Learning Framework for DNA Language Model

DNA language model aims to decipher the regulatory grammar and semantic of genomes by capturing long range dependencies in DNA sequences. Existing methods emphasize long range token interactions but often ignore the interplay between local motifs and global dependencies. In this paper, we propose Wisteria, a genomic language model that integrates multi scale feature learning within a unified framework for DNA sequence. Specifically, Wisteria augments the Mamba based architecture with gated dilated convolutions to capture local motifs and regulatory patterns, while gated multilayer perceptrons refine global dependencies. We further introduce a Fourier based attention mechanism to support frequency domain modeling, periodic extension and length generalization. Across four experimental settings with both short and long range dependencies, Wisteria demonstrates strong performance on downstream benchmarks against competitive DNA language model baselines. These results indicate that Wisteria effectively unifies local and global dependency modeling for multi scale genomic sequence analysis.

cs.AI↗

arXiv2026

Energy equality of the weak solutions to non-Newtonian fluids equations

In this paper, we study the problem of energy equality for weak solutions of the 3D incompressible non-Newtonian fluid equations with initial value conditions. We derive new sufficient conditions via Sobolev multiplier spaces that guarantee the validity of the energy equality. Moreover, the aforementioned equations are often associated with the uniqueness problem of weak solutions for non-Newtonian fluids, which, in a certain sense, constitutes the positive counterpart of Onsager's conclusion for non-Newtonian fluids.

math.AP↗

arXiv2026

Debate to Align: Reliable Entity Alignment through Two-Stage Multi-Agent Debate

Entity alignment (EA) aims to identify entities referring to the same real-world object across different knowledge graphs (KGs). Recent approaches based on large language models (LLMs) typically obtain entity embeddings through knowledge representation learning and use embedding similarity to identify an alignment-uncertain entity set. For each uncertain entity, a candidate entity set (CES) is then retrieved based on embedding similarity to support subsequent alignment reasoning and decision making. However, the reliability of the CES and the reasoning capability of LLMs critically affect the effectiveness of subsequent alignment decisions. To address this issue, we propose AgentEA, a reliable EA framework based on multi-agent debate. AgentEA first improves embedding quality through entity representation preference optimization, and then introduces a two-stage multi-role debate mechanism consisting of lightweight debate verification and deep debate alignment to progressively enhance the reliability of alignment decisions while enabling more efficient debate-based reasoning. Extensive experiments on public benchmarks under cross-lingual, sparse, large-scale, and heterogeneous settings demonstrate the effectiveness of AgentEA.

cs.CL↗

arXiv2026

Liouville Type Theorem for the Fractional MHD and Hall-MHD equations in $\mathbb{R}^{3}

In this paper, we are mainly concerned with the Liouville type problem for the stationary fractional magnetohydrodynamics(MHD) and stationary fractional Hall-MHD equations. In addition, we present the results of the Navier-Stokes equation as a byproduct. The key point is to use the Caffarelli-Sivestre extension to overcome the difficulty caused by the non-local operator $(-\triangle)^{s}$ and combined with Yuan and Xiao's method (J. Math. Anal. Appl. 491 (2020) 124343).

math.AP↗

arXiv2025

Towards 3D Object-Centric Feature Learning for Semantic Scene Completion

Vision-based 3D Semantic Scene Completion (SSC) has received growing attention due to its potential in autonomous driving. While most existing approaches follow an ego-centric paradigm by aggregating and diffusing features over the entire scene, they often overlook fine-grained object-level details, leading to semantic and geometric ambiguities, especially in complex environments. To address this limitation, we propose Ocean, an object-centric prediction framework that decomposes the scene into individual object instances to enable more accurate semantic occupancy prediction. Specifically, we first employ a lightweight segmentation model, MobileSAM, to extract instance masks from the input image. Then, we introduce a 3D Semantic Group Attention module that leverages linear attention to aggregate object-centric features in 3D space. To handle segmentation errors and missing instances, we further design a Global Similarity-Guided Attention module that leverages segmentation features for global interaction. Finally, we propose an Instance-aware Local Diffusion module that improves instance features through a generative process and subsequently refines the scene representation in the BEV space. Extensive experiments on the SemanticKITTI and SSCBench-KITTI360 benchmarks demonstrate that Ocean achieves state-of-the-art performance, with mIoU scores of 17.40 and 20.28, respectively.

cs.CV↗

arXiv2025

Energy equality of the weak solutions to the fractional Navier-Stokes / MHD equations

In this paper, we study the problem of energy equality for weak solutions of the 3D incompressible fractional Navier-Stokes / MHD equations. With the help of the technique of symmetrization and interpolation method, we obtain some new sufficient conditions including the Sobolev multiplier spaces, which insures the validity of the energy equality of the weak solution to fractional MHD equations. Correspondingly, the results of fractional Navier-Stokes equations are obtained. And these energy equations are usually related to the uniqueness of solutions to the corresponding fractional Navier-Stokes / MHD equations.

math.AP↗

arXiv2025

Mechanical Amorphization of Glass-Forming Systems Induced by Oscillatory Deformation: The Energy Absorption and Efficiency Control

The kinetic process of mechanical amorphization plays a central role in tailoring material properties. Therefore, a quantitative understanding of how this process depends on loading parameters is critical for optimizing mechanical amorphization and tuning material performance. In this study, we employ molecular dynamics simulations to investigate oscillatory deformation-induced amorphization in three glass-forming intermetallic systems, addressing two unresolved challenges: (1) the relationship between amorphization efficiency and mechanical loading, and (2) energy absorption dynamics during crystal-to-amorphous (CTA) transitions. Our results demonstrate a decoupling between amorphization efficiency--governed by work rate and described by an effective temperature model--and energy absorption, which adheres to the Herschel-Bulkley constitutive relation. Crucially, the melting enthalpy emerges as a key determinant of the energy barrier, establishing a thermodynamic analogy between mechanical amorphization and thermally induced melting. This relationship provides a universally applicable metric to quantify amorphization kinetics. By unifying material properties and loading conditions, this work establishes a predictive framework for controlling amorphization processes. These findings advance the fundamental understanding of deformation-driven phase transitions and offer practical guidelines for designing materials with tailored properties for ultrafast fabrication, ball milling, and advanced mechanical processing techniques.

cond-mat.mtrl-sci↗

arXiv2025

Physics of Strong Magnetism with eXTP

In this paper we present the science potential of the enhanced X-ray Timing and Polarimetry (eXTP) mission, in its new configuration, for studies of strongly magnetized compact objects. We discuss the scientific potential of eXTP for quantum electrodynamic (QED) studies, especially leveraging on the recent observations made with the NASA IXPE mission. Given eXTP's unique combination of timing, spectroscopy, and polarimetry, we focus on the perspectives for physics and astrophysics studies of strongly magnetized compact objects, such as magnetars and accreting X-ray pulsars. Developed by an international Consortium led by the Institute of High Energy Physics of the Chinese Academy of Sciences, the eXTP mission is expected to launch in early 2030.

astro-ph.HE↗

arXiv2025

Dense Matter in Neutron Stars with eXTP

In this White Paper, we present the potential of the enhanced X-ray Timing and Polarimetry (eXTP) mission to constrain the equation of state of dense matter in neutron stars, exploring regimes not directly accessible to terrestrial experiments. By observing a diverse population of neutron stars - including isolated objects, X-ray bursters, and accreting systems - eXTP's unique combination of timing, spectroscopy, and polarimetry enables high-precision measurements of compactness, spin, surface temperature, polarimetric signals, and timing irregularity. These multifaceted observations, combined with advances in theoretical modeling, pave the way toward a comprehensive description of the properties and phases of dense matter from the crust to the core of neutron stars. Under development by an international Consortium led by the Institute of High Energy Physics of the Chinese Academy of Sciences, the eXTP mission is planned to be launched in early 2030.

astro-ph.HE↗

arXiv2025

Discovery of the anti-glitch in PSR J1835$-$1106

We report the detection of an anti-glitch with a fractional frequency change of $Δν/ν=-3.46(6)\times10^{-9}$ in the rotation-powered pulsar PSR J1835$-$1106 at MJD 55813, based on timing observations collected with the Nanshan 26-m and Parkes 64-m radio telescopes from January 2000 to July 2022. A comparison of the average pulse profiles within $\pm300$ d of the event reveals no significant morphological changes. We also estimate the angular velocity lag between the normal and superfluid components at the time of the glitch, showing that one of the superfluid glitch models is incompatible with PSR J1835$-$1106 due to its insufficient spin-down rate and angular velocity lag. The wind braking scenario offers a viable alternative, consistent with the observed spin-down behavior, glitch amplitude, and post-glitch recovery. High-cadence, high-sensitivity monitoring of similar events is essential to distinguish between internal (superfluid) and external (wind-related) glitch mechanisms.

astro-ph.HE↗

arXiv2025

Combinatorial Development of Amorphous/nanocrystalline Biphase Soft Magnetic Alloys with Silicon-steel like Saturated Magnetic Induction

Maximization saturation magnetic induction (Bs) of soft magnetic alloys is essential for the high power-density electromagnetic devices. However, identifying the alloy compositions with high Bs often replies on the lab-intensive melt casting method and a high-throughput characterization on magnetic properties remains challenging. Here, we develop a new combinatorial method for fast screening alloys with optimal soft magnetic properties based on the high-throughput MOKE screening method. Based on the combinatorial method, we found that the alloys with a combination of high Bs and low coercivity (Hc) tend to have a feature of amorphous-nanocrystalline biphase microstructure. We also identified an amorphous/nanocrystalline alloy film with the composition the Fe68.09Co17.02B10.9Si4, exhibiting an ultra-high Bs up to 2.02 T that surpasses all amorphous/nanocrystalline alloys reported so far and is comparable to that of silicon steels, together with a high resistivity of 882 μΩ {\dot} cm, about 17 times of silicon steels. Our high-throughput magnetic screening method provides a paradigm for understanding the relationship between microstructure and magnetic properties and the development of the next-generation soft magnetic materials.

cond-mat.mtrl-sci↗

arXiv2025

An Ejection Event Captured by VLBI During the Outburst of Swift J1727.8$-$1613

We observed a newly-discovered Galactic black hole X-ray binary Swift J1727.8$-$1613 with the European Very Long Baseline Interferometry Network (EVN) at 5 GHz. The observation was conducted immediately following a radio quenching event detected by the Karl G. Jansky Very Large Array (VLA). The visibility amplitude evolution over time reveals a large-amplitude radio flare and is consistent with an ejection event. The data can be interpreted either as a stationary component (i.e., the radio core) and a moving blob, or as two blobs moving away from the core symmetrically in opposite directions. The initial angular separation speed of the two components was estimated to 30 mas d^{-1}. We respectively fitted a single circular Gaussian model component to each of 14 sliced visibility datasets. For the case of including only European baselines, during the final hour of the EVN observation, the fitted sizes exhibited linear expansion, indicating that the measured sizes were dominated by the angular separation of the two components. The 6-h EVN observation took place in a rising phase of an even larger 4-day-long radio flare, implying that the ejection events were quite frequent and therefore continuous radio monitoring is necessary to correctly estimate the power of the transient jet. Combined with X-ray monitoring data, the radio quenching and subsequent flares/ejections were likely driven by instabilities in the inner hot accretion disk.

astro-ph.HE↗

arXiv2024

Distance-Adaptive Quaternion Knowledge Graph Embedding with Bidirectional Rotation

Quaternion contains one real part and three imaginary parts, which provided a more expressive hypercomplex space for learning knowledge graph. Existing quaternion embedding models measure the plausibility of a triplet either through semantic matching or geometric distance scoring functions. However, it appears that semantic matching diminishes the separability of entities, while the distance scoring function weakens the semantics of entities. To address this issue, we propose a novel quaternion knowledge graph embedding model. Our model combines semantic matching with entity's geometric distance to better measure the plausibility of triplets. Specifically, in the quaternion space, we perform a right rotation on head entity and a reverse rotation on tail entity to learn rich semantic features. Then, we utilize distance adaptive translations to learn geometric distance between entities. Furthermore, we provide mathematical proofs to demonstrate our model can handle complex logical relationships. Extensive experimental results and analyses show our model significantly outperforms previous models on well-known knowledge graph completion benchmark datasets. Our code is available at https://github.com/llqy123/DaBR.

cs.LG↗