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Jia Zhang

Publications and source records attributed to Jia Zhang.

At least 19 recordsLinked to original sources
arXiv2026

Rapid Variability and Broadband Spectral Modeling in the Flaring Activity of BL Lacertae

We report a multi-wavelength study of two flaring episodes of the blazar BL Lacertae during MJD 60500-60800 (9 July 2024 - 5 May 2025). The source reached a daily-averaged $\gamma$-ray flux of $(1.03 \pm 0.05) \times 10^{-5} \, \mathrm{ph \, cm^{-2} \, s^{-1}}$ ($E > 100$ MeV) on MJD 60588 (5 October 2024). Using orbit-binned data from the Large Area Telescope (LAT) onboard the \textit{Fermi Gamma-ray Space Telescope}, we identify a minimum flux halving timescale of $\tau = 1.33 \pm 0.29$ hr. This constrains the upper limit on the $\gamma$-ray emitting region size to $R \le 2.0 \times 10^{15}$ cm, as well as its distance from the central supermassive black hole to $R_\mathrm{H} \le 5.9 \times 10^{16}$ cm, assuming a Doppler factor of $\delta = 14.8$ derived from the spectral energy distribution (SED) modeling. We find tentative evidence for sub-minute $\gamma$-ray variability with a minimum doubling time of $0.7 \pm 0.2$ min ($p$-value = 0.03). This may originate from an extremely compact region with a size of $R \le 1.8 \times 10^{13}$ cm, suggesting that the emission arises from magnetohydrodynamic substructures, such as plasmoids within a magnetic reconnection zone. Spectral analysis reveals a significant ``softer-when-brighter'' trend ($r = 0.96, p = 4.5 \times 10^{-4}$) during the minute-scale flare peaks, indicating a complex interplay between particle acceleration and radiative cooling. The SED is reproduced using a one-zone leptonic model, in which synchrotron self-Compton (SSC) and external Compton (EC) scattering effectively account for the high-energy emissions. The reduced magnetic field strengths and hard electron injection spectral indices observed during the flaring states suggest enhanced particle acceleration efficiency, possibly associated with relativistic magnetic reconnection.

astro-ph.HE↗
arXiv2026

UBio-MolFM: Enabling Biomolecular Dynamics at DFT Accuracy and $10^5$ Atoms with One Untuned Potential

Ion conduction, membrane permeation and metal recognition hinge on electronic structure, yet first-principles simulation reaches only hundreds of atoms. UBio-MolFM lifts that ceiling: a foundation model trained on 160 million quantum-chemical labels, its receptive field spanning non-covalent distances at near-linear cost. The barrier is cost, not principle. One untuned potential keeps force error near 20 meV/{\AA} past a thousand atoms, reproduces water's X-ray structure and ion hydration, and holds an RNA Mg$^{2+}$ site without ion-specific parameters. Cyclosporine A pays 3.5 kcal/mol in water for its permeable conformer, gated by one kinetically asymmetric hydrogen bond that a fixed-charge model flattens. In a 108,964-atom KcsA channel on one GPU, the relaxed four-ion column is anhydrous in all five replicas, in direct contact in four---the knock-on geometry ten fixed-charge simulations never form. It remains orders of magnitude costlier. Where electronic structure decides the answer, first-principles simulation is in reach.

physics.chem-ph↗
arXiv2026

Spin-group theory on Edelstein effect and spin-orbit torque in Collinear Ferromagnets

Current-induced spin-orbit torques (SOTs) are central to the electrical manipulation of magnetic order in spintronic devices. In transition-metal/collinear ferromagnet bilayers, field-like and damping-like torques have been described only phenomenologically via the spin or orbital Hall effect, lacking a rigorous symmetry-based foundation. The precise role of spin-orbit coupling (SOC) in both the Edelstein effect and SOTs has remained unresolved. Here we develop a spin-group symmetry theory for the Edelstein effect and SOTs in collinear ferromagnets, treating SOC as a symmetry-breaking perturbation. For 4mm (C4v) point group symmetry, we derive the full forms of field-like and damping-like torques, which arise predominantly from first- and second-order SOC. We further show that SOTs in both orbital-Hall-dominated Ti/Ni and spin-Hall-dominated Pt/CoFe bilayers originate at first-order SOC. Taking the 3m (C3v) torque as a paradigmatic example, we elucidate the role of second- and higher-order SOC torques in field-free switching of perpendicular magnetic anisotropy. Remarkably, in PtMnSb, we demonstrate that SOTs under certain point group symmetries deviate from the conventional form: zeroth- and first-order SOC contributions vanish identically, with the leading SOT emerging at second order. All symmetry-based predictions from spin-group theory are in excellent quantitative agreement with first-principles calculations. Our work establishes a unified symmetry framework for the microscopic understanding of the Edelstein effect and current-induced spin torques in ferromagnetic systems.

cond-mat.mtrl-sci↗
arXiv2026

Spin Hall Effect in Collinear Ferromagnets from Spin-Group Symmetry

Magnetic materials support both time-reversal-even (T-even) and time-reversal-odd (T-odd) spin Hall currents, yet their underlying microscopic origins remain elusive. Here, we elucidate the spin Hall effect (SHE) in collinear ferromagnets by treating spin-orbit coupling (SOC) as a perturbation that breaks spin-group symmetry, thereby revealing how magnetic order activates distinct spin Hall response. To first order in SOC, we identify two dominant T-even SHE mechanisms: a magnetization-independent conventional contribution and a magnetization-dependent channel associated with anomalous Hall charge transport. At the same order, the leading T-odd magnetic spin Hall effect (MSHE) originates from the exchange interaction between the conventional spin current and the local magnetization. At second order in SOC, we further uncover a distinct T-odd planar spin Hall mechanism. Our spin-symmetry analysis is corroborated by first-principles calculations, which reveal a pronounced anisotropic magnetic spin Hall effect whose magnitude can be comparable to the T-even spin Hall conductivity (SHC) when the magnetic moment is tilted away from the principal crystallographic axes. These findings clarify the microscopic origins of the SHC in collinear ferromagnets and pave the way for ferromagnet-based spin current sources with versatile properties in spintronic applications.

cond-mat.mes-hall↗
arXiv2026

GlaKG: A Biomarker-Centric Fundus Knowledge Graph for Explainable Glaucoma Diagnosis and Risk Assessment

Glaucoma is a leading cause of irreversible blindness worldwide, yet most automated diagnosis systems rely on opaque deep-learning models that offer little clinical interpretability. We present GlaKG, a biomarker-centric fundus knowledge graph that integrates structural biomarkers, clinically grounded rules, and image features to produce traceable reasoning for glaucoma diagnosis and risk stratification. GlaKG encodes six entity types (Fundus Image, Optic Disc, Neural Rim, Pathology, Diagnosis, Risk Level), eight relation types, and 11 clinically validated rules into a unified graph, so that every prediction is accompanied by an explicit reasoning chain linking biomarker evidence to activated clinical rules. To keep knowledge-based reasoning strictly separate from label information, we adopt a post-processing fusion framework that combines ResNet50 image embeddings with a normalized KG reasoning-chain score via a tunable weight alpha, with all fitting confined to the training split. On a publicly available, AI-annotated fundus dataset, GlaKG reaches F1 = 0.9953 for binary glaucoma classification and 0.930 accuracy with 0.922 weighted F1 for four-class risk stratification; we report openly that the dataset's biomarker annotations are highly label-correlated, and therefore frame these figures as an upper bound attainable with clean structured biomarkers rather than as leakage-free image-only performance. Feature-importance analysis shows KG-derived and biomarker features contributing near-equally (51.1% vs. 48.9%), and the reasoning chain flags borderline cases by exposing low chain scores rather than failing silently. GlaKG's central contribution is therefore a clinically auditable reasoning framework that complements raw predictive performance by explicitly exposing the biomarker evidence and rule activations behind each decision.

cs.CV↗
arXiv2026

Electric-Field Switchable Magnetic Spin Hall Effect

It is established that the polarity of a time-reversal-odd ($\mathcal{T}$-odd) physical quantity can be reversed under the $\mathcal{T}$ operation. Here, we use the spin-group analysis to directly demonstrate that the $\mathcal{T}$-odd magnetic spin Hall effect in ferroelectric altermagnets can be switchable by electric fields beyond the $\mathcal{T}$ operation. This arises from the ferroelectric switching of the nonrelativistic spin splitting, which swaps the roles of spin up and down channels in the reciprocal space. As a result, the $\mathcal{T}$-odd spin conductivity that are proportional to the spin-polarized conductivity difference reverses its polarity upon polarization switching. We identify spin-group operations to switch both the polarization and the magnetic spin Hall effect simultaneously for non-centrosymmetric spin point groups. Then, we exemplify those phenomena in the ferroelectric altermagnet VOI$_2$ monolayer based on density functional theory calculations and an effective Hamiltonian analysis. Our findings not only provide novel strategies to switch the magnetic spin Hall effect using the dissipation-free electric field but also open a promising avenue for electrically programmable spintronic devices.

cond-mat.other↗
arXiv2026

Backdoor Attacks on Speech Emotion Recognition via TTS-Generated Poisoning

Speech Emotion Recognition (SER) systems increasingly leverage self-supervised acoustic representations, yet their vulnerability to training-time attacks remains largely underexplored. This paper presents the first systematic study of poisoning-based backdoor attacks on SER, with a focus on threats enabled by text-to-speech (TTS) generated audio. We introduce a stealthy, low-energy acoustic trigger that can be embedded imperceptibly into both natural and synthetic speech, enabling scalable and consistent poisoning. Our experiments demonstrate that SER models can be reliably compromised with high attack success rates under low poisoning ratios, while maintaining near-clean performance on benign inputs. We further show that backdoor patterns exhibit strong cross-model transferability and that self-supervised representations are particularly susceptible to learning these triggers. These findings reveal that TTS technology dramatically lowers the barrier to effective backdoor attacks, exposing critical vulnerabilities in modern SER pipelines and motivating the urgent need for dedicated defenses.

cs.SD↗
arXiv2026

Diversity in Evolutionary Status and Magnetic Activity among Solar-Type Twin Detached Eclipsing Binaries

We present a combined photometric and spectroscopic analysis of four detached eclipsing binaries (KIC 8957954, KIC 10593759, KIC 8302455, and TIC 207398432), all of which exhibit composite G-type spectra and nearly equal mass ratios. Based on survey data and our own observations, we measured radial velocities with the broadening function method, applied the fd3 program for spectral disentangling, and modeled the light curves with the Wilson-Devinney code to determine accurate absolute parameters. The results reveal significant differences in evolutionary stages and magnetic activity despite their nearly equal masses. Both components of KIC 8957954 and KIC 8302455 are on the main sequence; KIC 10593759 has evolved to the subgiant stage; and in TIC 207398432, the secondary has entered the red giant phase. Stronger magnetic activity is observed in KIC 10593759 and TIC 207398432, characterized by rapid O'Connell Effect Ratio variations, with the latter also exhibiting multiple superflare events. In addition, the spectral characteristics of TIC 207398432 suggest that it may be part of a hierarchical triple system. This study provides precise absolute parameters for twin binaries and offers important observational evidence for understanding their evolutionary diversity, magnetic activity, and the possible presence of tertiary companions.

astro-ph.SR↗
arXiv2026

Accelerating Locality-Driven Integration in Quantum Chemistry with Block-Structured Matrix Multiplication

Locality-driven integration is a pervasive computational pattern in quantum chemistry, arising whenever spatially localized basis functions interact through numerical quadrature or integral screening. The dominant matrix multiplications in these tasks exhibit dynamic, structured sparsity driven by spatial locality, posing significant challenges for both dense batched kernels and generic sparse formats on GPUs. We present KerneLDI, a GPU-oriented framework that addresses this regime by co-designing data layout, screening logic, and matrix-computation operators to realize block-structured matrix multiplication for locality-driven integration. KerneLDI reorganizes operand matrices into a unified block-filtered representation that retains only spatially relevant blocks, and executes the resulting contractions with customized dense block multipliers that adapt proven dense-matmul optimizations to retained block pairs. We develop and evaluate KerneLDI on exchange--correlation (EXC) integration in Kohn--Sham density functional theory, a representative and computationally critical instance of this pattern. Across diverse molecular systems, KerneLDI preserves numerical accuracy while delivering up to 10$\times$ speedup for EXC evaluation over a dense GPU baseline, scales favorably with increasing system size and multi-GPU parallelism, accelerates end-to-end self-consistent field calculations, and yields nearly 6$\times$ throughput improvement for ab initio molecular dynamics.

physics.comp-ph↗
arXiv2026

Giant orbital-magnon conversion driven perpendicular magnetization switching

The pursuit of beyond-Moore information technologies has stimulated the exploration of novel information carriers, such as electron spin, orbital, and magnon, beyond electron charge. Efficient interconversion among these degrees of freedom and precise control over the information states are crucial for advancing nanoelectronic devices. However, a direct coupling between orbital angular momentum (L) and magnons (M) has remained elusive, and magnetization switching through orbital-to-magnon (L-M) conversion has not yet been achieved. Here, we report the experimental demonstration of L-M conversion in an orbital metal/antiferromagnetic insulator bilayer at room temperature, with an efficiency over an order of magnitude higher than that in traditional orbital systems lacking the L-M process. Consequently, we achieved efficient room-temperature perpendicular magnetization switching in a CoFeB ferromagnetic layer mediated by this new mechanism. Our findings establish a direct link between orbitronics and magnonics, providing a new platform for the development of advanced nano-devices based on orbital-driven magnonic phenomena.

cond-mat.mes-hall↗
arXiv2026

Agents on a Tree: Pathwise Coordination for Multi-Objective Molecular Optimization

Multi-objective molecular optimization requires searching vast chemical spaces under conflicting objectives, where early design decisions strongly constrain downstream outcomes. Existing methods typically rely on a single policy or fixed scalarization, which limits their ability to represent diverse trade-offs and to explore multiple promising design trajectories. We propose ATOM, a multi-agent framework that formulates molecular optimization as a tree-structured search. Each node corresponds to an atomic operation and hosts an agent specialized for a particular objective or decision context. Agents coordinate along different paths of the tree rather than enforcing a global consensus, enabling the method to maintain and compare alternative molecular evolution trajectories. A global memory of past optimization behaviors further supports balanced exploration and exploitation across objectives. This tree-structured interaction enables reasoning over long-horizon dependencies inherent in molecular design. Experiments on challenging multi-objective benchmarks involving activity, synthesizability, and ADMET-related properties show that ATOM consistently achieves improved Pareto coverage and hypervolume over strong baselines. These results demonstrate the effectiveness of pathwise multi-agent coordination for molecular optimization. Code is available at https://anonymous.4open.science/r/ATOM-41CE.

cs.AI↗
arXiv2026

CausalVAD: De-confounding End-to-End Autonomous Driving via Causal Intervention

Planning-oriented end-to-end driving models show great promise, yet they fundamentally learn statistical correlations instead of true causal relationships. This vulnerability leads to causal confusion, where models exploit dataset biases as shortcuts, critically harming their reliability and safety in complex scenarios. To address this, we introduce CausalVAD, a de-confounding training framework that leverages causal intervention. At its core, we design the sparse causal intervention scheme (SCIS), a lightweight, plug-and-play module to instantiate the backdoor adjustment theory in neural networks. SCIS constructs a dictionary of prototypes representing latent driving contexts. It then uses this dictionary to intervene on the model's sparse vectorized queries. This step actively eliminates spurious associations induced by confounders, thereby eliminating spurious factors from the representations for downstream tasks. Extensive experiments on benchmarks like nuScenes show CausalVAD achieves state-of-the-art planning accuracy and safety. Furthermore, our method demonstrates superior robustness against both data bias and noisy scenarios configured to induce causal confusion.

cs.CV↗
arXiv2026

UBio-MolFM: A Universal Molecular Foundation Model for Bio-Systems

All-atom molecular simulation serves as a quintessential ``computational microscope'' for understanding the machinery of life, yet it remains fundamentally limited by the trade-off between quantum-mechanical (QM) accuracy and biological scale. We present UBio-MolFM, a universal foundation model framework specifically engineered to bridge this gap. UBio-MolFM introduces three synergistic innovations: (1) UBio-Mol26, a large bio-specific dataset constructed via a multi-fidelity ``Two-Pronged Strategy'' that combines systematic bottom-up enumeration with top-down sampling of native protein environments (up to 1,200 atoms); (2) E2Former-V2, a linear-scaling equivariant transformer that integrates Equivariant Axis-Aligned Sparsification (EAAS) and Long-Short Range (LSR) modeling to capture non-local physics with up to ~4x higher inference throughput in our large-system benchmarks; and (3) a Three-Stage Curriculum Learning protocol that transitions from energy initialization to energy-force consistency, with force-focused supervision to mitigate energy offsets. Rigorous benchmarking across microscopic forces and macroscopic observables -- including liquid water structure, ionic solvation, and peptide folding -- demonstrates that UBio-MolFM achieves ab initio-level fidelity on large, out-of-distribution biomolecular systems (up to ~1,500 atoms) and realistic MD observables. By reconciling scalability with quantum precision, UBio-MolFM provides a robust, ready-to-use tool for the next generation of computational biology.

physics.chem-ph↗
arXiv2026

LatentChem: From Textual CoT to Latent Thinking in Chemical Reasoning

Current chemical large language models (LLMs) predominantly rely on explicit Chain-of-Thought (CoT) to solve complex reasoning problems. However, forcing nonverbal tacit chemical logic into discrete natural language imposes a fundamental ``modality mismatch,'' creating an artificial bottleneck for reasoning. We introduce LatentChem, a reasoning interface that decouples chemical logic from linguistic generation, enabling the model to process information via continuous thought vectors and dynamic perception. Our investigation reveals a pivotal emergent behavior: spontaneous internalization, defined here as self-selected under outcome-only optimization. When optimized for task success, the model abandons verbose textual derivations in favor of implicit latent computation, suggesting that it identifies the continuous manifold as a more native substrate for chemical logic. This paradigm shift also proves to be a superior computational strategy: LatentChem achieves a 59.88\% non-tie win rate against the strong CoT baseline on the rigorous ChemCoTBench, while delivering a broad 10.84$\times$ average reduction in reasoning step overhead (5.96$\times$ wall-clock speedup) across all evaluated benchmarks. Our results provide empirical evidence that chemical reasoning is more naturally and effectively realized as continuous latent dynamics rather than discretized linguistic trajectories.

physics.chem-ph↗
arXiv2026

E2Former-V2: On-the-Fly Equivariant Attention with Linear Activation Memory

Equivariant Graph Neural Networks (EGNNs) have become a widely used approach for modeling 3D atomistic systems. However, mainstream architectures face critical scalability bottlenecks due to the explicit construction of geometric features or dense tensor products on \textit{every} edge. To overcome this, we introduce \textbf{E2Former-V2}, a scalable architecture that integrates algebraic sparsity with hardware-aware execution. We first propose \textbf{E}quivariant \textbf{A}xis-\textbf{A}ligned \textbf{S}parsification (EAAS). EAAS builds on Wigner-$6j$ convolution by exploiting an $\mathrm{SO}(3) \rightarrow \mathrm{SO}(2)$ change of basis to transform computationally expensive dense tensor contractions into efficient, sparse parity re-indexing operations. Building on this representation, we introduce \textbf{On-the-Fly Equivariant Attention}, a fully node-centric mechanism implemented via a custom fused Triton kernel. By eliminating materialized edge tensors and maximizing SRAM utilization, our kernel achieves a \textbf{20$\times$ improvement in TFLOPS} compared to standard implementations. Extensive experiments on the SPICE and OMol25 datasets demonstrate that E2Former-V2 maintains comparable predictive performance while notably accelerating inference. This work demonstrates that large equivariant transformers can be trained efficiently using widely accessible GPU platforms. The code is avalible at https://github.com/IQuestLab/UBio-MolFM/tree/e2formerv2.

cs.LG↗
arXiv2026

The reason for the occurrence of W-type contact binaries

For more than half a century, the puzzling W-type phenomenon in contact binaries has challenged astrophysicists. In these systems, the less massive component exhibits a higher surface temperature than its more massive companion, which is a reversal of the typical A-type configuration, where the more massive star is hotter. This counterintuitive temperature inversion defies the basic stellar physics and still lacks a widely accepted explanation. In this study, we assembled a sample of over 3,000 extensively observed contact binaries and derived their complete set of physical parameters. Our statistical analysis revealed a strong positive correlation between the occurrence of W-type contact binaries and the intensity and frequency of magnetic activities. This result strongly supports the hypothesis that magnetic activities are the primary driver of the W-type phenomenon and offers a compelling explanation for the observed transitions between the W-type and A-type.

astro-ph.SR↗
arXiv2026

HD 26172: an active solar-type subgiant in a close binary system

We present the first comprehensive photometric and spectroscopic analysis of the RS CVn system HD 26172, robustly determining the previously debated evolutionary state of its primary star. Since this system is a single-lined spectroscopic binary with spot-induced light curve modulations, we derived its physical parameters by combining the TESS light curves, the radial velocity curve from our observations, and the primary-star mass estimates based on three complementary methods.Our results reveal that HD 26172 is a detached binary system composed of a $1.25 \pm 0.32 M_{\odot}$ subgiant and a $0.63 \pm 0.11 M_{\odot}$ main-sequence star. The conclusion of subgiant primary is also supported by the absence of lithium absorption and no observed infrared excess. Using long-term photometry from the KWS survey, we detected a tentative stellar activity cycle of 5635 days with an amplitude of 0.04 mag in HD 26172. Additionally, we identified ten optical flare events exhibiting temporally clustered outburst behavior. The presence of a long-term activity cycle, pronounced starspot activity, and frequent optical flares makes HD 26172 a valuable laboratory for studying magnetic activity in subgiants within close binary systems.

astro-ph.SR↗
arXiv2026

Electric field switching of altermagnetic spin-splitting in multiferroic skyrmions

Magnetic skyrmions are localized magnetic structures that retain their shape and stability over time, thanks to their topological nature. Recent theoretical and experimental progress has laid the groundwork for understanding magnetic skyrmions characterized by negligible net magnetization and ultrafast dynamics. Notably, skyrmions emerging in materials with altermagnetism, a novel magnetic phase featuring lifted Kramers degeneracy-have remained unreported until now. In this study, we demonstrate that BiFeO3, a multiferroic renowned for its strong coupling between ferroelectricity and magnetism, can transit from a spin cycloid to a Neel-type skyrmion under antidamping spin-orbit torque at room temperature. Strikingly, the altermagnetic spin splitting within BiFeO3 skyrmion can be reversed through the application of an electric field, revealed via the Circular photogalvanic effect. This quasiparticle, which possesses a neutral topological charge, holds substantial promise for diverse applications-most notably, enabling the development of unconventional computing systems with low power consumption and magnetoelectric controllability.

cond-mat.mtrl-sci↗