arXiv subjects

Jincheng Wang

Publications and source records attributed to Jincheng Wang.

At least 19 recordsLinked to original sources

arXiv2026

Twinning of domains and spin anisotropy in K$_5$Fe$_4$Ag$_6$Te$_{10}$

The Fe-based superconductors are derived from metallic parent compounds with nematic and stripe magnetic orders, which lead to two types of magnetic domains. Recently it was found that K$_5$Fe$_4$Ag$_6$Te$_{10}$ (KFAT), an Fe-based semiconductor, exhibits similar nematic and stripe magnetic orders, and is thus an analogue to the Fe-based superconductors in the limit of localized electrons. In this work, the superstructure and magnetic domains of KFAT are elucidated by fully mapping the reciprocal space using time-of-flight single crystal neutron diffraction. In KFAT, Fe and Ag atoms order to form a $\sqrt{5}\times\sqrt{5}$ superstructure containing $2\times2$ Fe blocks, which leads to two superstructure domains with identical main Bragg peaks but distinct superstructure peaks. Below $T_{\rm N}\approx35$~K, magnetic and nematic orders break in-plane rotational symmetry of the tetragonal $\sqrt{5}\times\sqrt{5}$ superstructure, and further give rise to two magnetic domains. These four equally populated domains account for the complex scattering pattern observed in our time-of-flight elastic neutron scattering measurements. Using polarized neutron scattering, we demonstrate a prominent spin anisotropy with an easy-plane spanned by the $c$-axis and the intra-block antiferromagnetic Fe-Fe bond direction. Such an anisotropy at ${\bf q}\neq0$ persists well above $T_{\rm N}$, accounts for the in-plane ${\bf q}=0$ magnetic anisotropy observed in uniaxial-strained KFAT, and offers an indicator for discovering similar piezomagnetic effects in other materials.

cond-mat.str-el↗

arXiv2026

Reassessing Evidence for Dark-Sector Interactions with Dynamical Dark Energy and DESI DR2

Recent baryon acoustic oscillation measurements from DESI Data Release 2, when combined with CMB and supernova data, strengthen the motivation for exploring departures from $Λ$CDM in the late-time expansion history. Because an evolving dark-energy equation of state and an interaction within the dark sector can produce partially degenerate effects on the background expansion, their observational signatures should be assessed simultaneously. We first consider an interacting $w_0w_a$CDM model with $Q=βHρ_{\rm de}$, using Planck and ACT CMB data, DESI DR2, and DES-Dovekie supernovae. Allowing the dark-energy equation of state to evolve substantially weakens the preference for a nonzero coupling, while the preference for dynamical dark energy persists. The interaction provides essentially no additional improvement in the best fit, suggesting that part of the coupling preference found in more restricted interacting models may reflect a degeneracy with dark-energy dynamics. We then examine the same interaction for three one-parameter dynamical dark-energy trajectories: thawing, mirage, and generalized emergent dark energy (GEDE). The role of the interaction depends strongly on the assumed trajectory. The thawing and GEDE models favor sizable couplings of opposite signs, whereas the mirage trajectory already closely follows the dark-energy evolution preferred by the data and provides little support for an additional interaction. These models also predict markedly different signatures in structure growth, ranging from enhanced matter clustering in the interacting thawing model to strong suppression in interacting GEDE. These contrasting growth signatures, despite substantial degeneracies at the background level, highlight late-time large-scale-structure observations as a promising avenue for distinguishing dark-energy dynamics from dark-sector interactions.

astro-ph.CO↗

arXiv2026

Statistical Study of Solar Prominence Plumes Based on NVST H$α$ Observations

Plumes are one of the most representative dynamic features observed in prominences and play a key role in mass and magnetic transport within them. However, their physical nature and triggering processes remain actively debated. Based on limb H$α$ observations from the New Vacuum Solar Telescope (NVST) during 2013--2025, we statistically investigated 34 plumes with clear and complete evolutions by developing an automated image-processing pipeline. It is revealed that plume lifetimes mainly range from 300 s to 700 s, with vertical displacements between 3--7 Mm. The mean widths and velocities are concentrated in the range of 0.5--1.5 Mm and 10--20 km s$^{-1}$, respectively. Besides wide distribution ranges, plume parameters exhibit irregular evolution fluctuations, indicating that the formation and evolution of various plumes may exhibit different physical patterns. Correlation analysis among the parameters further reveals that: (1) Positive correlations were found among lifetime, vertical displacement, and mean width, indicating an intrinsic coupling between the temporal and spatial scales of plumes. (2) Trajectory curvature is negatively correlated with lifetime, vertical displacement, and velocity. Accelerating and width-contracting plumes typically have lower curvature, suggesting that curvature may reflect environmental influences and the stability of plumes. (3) Plumes with higher initial velocities were more likely to be accompanied by precursor brightening, suggesting that these plumes may be triggered by magnetic reconnection. Furthermore, we infer that some plumes in non-bubble regions may be inherently driven by mini-filament eruptions. These results establish a statistical framework for prominence plumes and reveal diversity in their dynamical evolution and triggering mechanisms.

astro-ph.SR↗

arXiv2026

SVRepair: Structured Visual Reasoning for Automated Program Repair

Large language models (LLMs) have recently been applied to Automated Program Repair (APR), yet most existing approaches remain unimodal and fail to use diagnostic signals contained in visual artifacts such as screenshots and control-flow graphs. In practice, many bug reports convey critical information visually (e.g., layout breakage or missing widgets), but directly using such dense visual inputs often causes context loss and noise, making it difficult for MLLMs to ground visual observations into precise fault localization and executable patches. To bridge this semantic gap, we propose \textbf{SVRepair}, a multimodal APR framework with Structured Visual Representation (SVR). SVRepair first fine-tunes a vision-language model, SVR, to uniformly transform heterogeneous visual artifacts into a \emph{semantic scene graph} that captures GUI elements and their structural relations (e.g., hierarchy), providing normalized, code-relevant context for downstream repair. Building on the graph, SVRepair drives a coding agent to localize faults and synthesize patches, and further introduces an iterative visual-artifact segmentation strategy that progressively narrows the input to bug-centered regions to suppress irrelevant context and reduce hallucinations. Across primary repository-level APR benchmarks, SVRepair resolves \textbf{186/517} SWE-Bench M instances (\textbf{35.98\%} over all instances; \textbf{36.47\%} over submitted runs) and \textbf{4/19} visual OmniGIRL instances (\textbf{21.05\%}). On supplementary structured multimodal code reasoning benchmarks, SVRepair reaches \textbf{38.02\%} on MMCode and \textbf{95.73\%} on CodeVision. Code is available at https://github.com/codefuse-ai/CodeFuse-SVR.

cs.SE↗

arXiv2026

Observations of a Solar Jet Triggered by Reconnection between Super-penumbral Fibrils and a Mini-filament

Coronal jets are highly dynamic phenomena in the solar atmosphere, yet their driving mechanisms remain an active topic of investigation. In this paper, we report a coronal jet triggered by the interaction between super-penumbral fibrils and a mini-filament, based on coordinated observations from the New Vacuum Solar Telescope (NVST), the Chinese H$α$ Solar Explorer (CHASE), and the Solar Dynamics Observatory (SDO). The fibrils were anchored between the negative-polarity region of a sunspot and an emerging positive-polarity region associated with a moving magnetic feature (MMF). As the positive polarity migrated outward, the fibrils elongated and interacted with the mini-filament, one of whose footpoints was rooted in pre-existing negative-polarity fields. Intense brightenings at the interaction site, together with changes in the connectivity of the mini-filament footpoint from the pre-existing negative polarity to the sunspot, indicate the occurrence of magnetic reconnection. The event produced a narrow hot jet accompanied by a broader cool component. The cool plasma exhibited a clockwise rotation, providing evidence for the transfer of magnetic twist during reconnection. Persistent magnetic flux cancellation was observed before and during the jet eruption. These observations demonstrate that small-scale magnetic structures, such as MMFs, can significantly influence mini-filament eruptions and highlight the important role of flux cancellation in triggering coronal jet activity.

astro-ph.SR↗

arXiv2026

COVENANT: Natural-Language Workflow Compilation for Aligned Agent Execution

Large language model (LLM) agents are increasingly entrusted with natural-language workflow instructions (e.g., retail-payment policies) that specify not only what outcome to achieve, but also which steps, branches, and tool interactions are permitted. When these instructions are supplied as prompt context, however, the model retains control over both procedure selection and step execution. As interactions accumulate, an agent can skip required steps, take unsupported branches, or execute a valid step with unsupported arguments or effects--a failure mode we call workflow misalignment. In this work, we propose COVENANT, a compiler-and-interpreter architecture for workflow-aligned agent execution. Our key insight is to treat workflow instructions as source programs rather than prompts. COVENANT converts the instructions into a workflow abstract syntax tree (WAST) and lowers it to a workflow control-flow graph (WCFG). At runtime, a controller interprets the WCFG one node at a time, checks each proposal against requirements extracted from the instructions before committing controller state or advancing the graph, and returns diagnostic feedback for repair. To evaluate COVENANT, we use 120 cases from three existing benchmarks, spanning seven workflow scenarios. Compared with state-of-the-art LLM agents, COVENANT improves benchmark success from 50.00% to 83.33% and reduces the workflow-misalignment failure rate from 42.50% to 15.83% (62.75% relative). These results show that COVENANT substantially mitigates workflow misalignment, moving LLM-agent alignment beyond isolated prompt following toward reliable execution of complex and multi-step workflows.

cs.AI↗

arXiv2026

Phantom-Divide Crossing in Exponentially Coupled Quintessence and the Role of Neutrino-Mass Freedom

We investigate a quintessence dark-energy model with an exponential potential and an exponential coupling to cold dark matter (CDM), hereafter referred to as the CQ-EXP model, using Planck CMB, DESI BAO, and DES-Dovekie supernova observations. We also examine how variations in the neutrino mass sector affect the constraints. When the neutrino mass sum is fixed at $\sum m_ν=0.06$ eV, the data favor a coupling between quintessence and CDM, with the coupling parameter $β$ deviating from zero at more than $3σ$. In particular, the observations favor the $β<0$ branch, where the energy transfer between the two dark sectors changes sign and the effective equation of state (EoS) of dark energy crosses the phantom divide, $w=-1$. When the effective neutrino mass parameter $\sum m_{ν,\mathrm{eff}}$ is treated as a free parameter, the data show a preference for negative values of $\sum m_{ν,\mathrm{eff}}$. This additional freedom weakens the preference for the coupling between quintessence and CDM and leads to nearly identical values of $χ^2_{\rm min}$ for the CQ-EXP models with $β>0$ and $β<0$, corresponding respectively to models without and with phantom-divide crossing in the effective EoS. Both values are slightly larger than that obtained in the $w_0w_a$CDM model, indicating that the CQ-EXP model cannot be statistically distinguished from the $w_0w_a$CDM model with the data considered here. Therefore, when $\sum m_ν$ is fixed, current observations favor the CQ-EXP model with phantom-divide crossing. In contrast, when negative values of $\sum m_{ν,\mathrm{eff}}$ are allowed, a CQ-EXP dark energy without crossing $w=-1$ can also provide an effective explanation of the latest observations.

astro-ph.CO↗

arXiv2026

Observational Evidence of Solar Spicules Associated with Microfilament Eruptions Using DKIST

The formation mechanism of spicules is fundamentally important for understanding mass and energy transport from the chromosphere into the corona. Recent studies suggested that spicules may be powered by microfilament eruptions. However, direct observational evidence remains limited due to insufficient spatial resolution. Using high-resolution H$α$ broadband observations from the Visible Broadband Imager (VBI) onboard the Daniel K. Inouye Solar Telescope (DKIST), we identify 30 spicule events triggered by microfilament eruptions in a quiet Sun region near the solar disk center on 2023 August 29. The detected microfilaments have an average length of $0.93\pm0.46$ Mm and a minimum length of 0.17 Mm, substantially smaller than previously reported minifilaments. We identify two distinct morphological classes of ejecta: individual spicules associated with smaller microfilaments, and enhanced spicular activities associated with larger microfilaments. Moreover, some events exhibit apparent twisting motions. All these high-resolution observations provide compelling evidence that spicules can be triggered by microfilament eruptions.

astro-ph.SR↗

arXiv2026

Intertwining Properties for Bimodule Quantum Markov Semigroups

In this paper, we study the Bakry-Émery estimates for GNS- and KMS-symmetric semigroups in terms of the Fourier multiplier of the gradient form and the iterated gradient form in the framework of quantum Fourier analysis. We also systematically investigate the intertwining properties for bimodule GNS- and KMS-symmetric quantum Markov semigroups and compare with the Bakry-Émery estimates. A number of examples of GNS- and KMS-symmetric semigroups satisfying these intertwining properties are presented.

math.OA↗

arXiv2026

FluxNet: Learning Capacity-Constrained Local Transport Operators for Conservative and Bounded PDE Surrogates

Autoregressive learning of time-stepping operators provides an effective approach to data-driven partial differential equation (PDE) simulation, yet for conservation laws, they face a fundamental challenge: learned updates may violate global conservation over long rollouts. For the important subclass of mass-conservation-type equations, the problem is compounded by inherent physical bounds (e.g., nonnegativity or concentrations in [0,1]) whose violation further destabilizes predictions. We introduce FluxNet, which learns cumulative transport amounts representing the total conserved quantity redistributed between each cell and a configurable neighborhood over the full surrogate interval. A conservative update guarantees exact discrete conservation by construction; modular capacity-constrained transport heads (L, U, and D) enforce lower bounds, upper bounds, or near-zero dual-bound violations through architectural design. Unlike flux-rate surrogates that require temporal integration and thus inherit CFL constraints, FluxNet involves no such integration; configurable transport neighborhoods enable large-timestep prediction at full spatial resolution. Ghost cells extend the framework to non-periodic boundaries. Experiments on four benchmarks (1D convection--diffusion, 2D shallow water, 1D traffic flow, 2D Cahn--Hilliard) demonstrate exact conservation, structural bound preservation, architecture modularity, and superior stability over flux-rate surrogates at large temporal strides. The code is publicly available at: https://github.com/Lan-zs/FluxNet.

cond-mat.mtrl-sci↗

arXiv2026

Coupled quintessence with a potential from supergravity exhibits sign-changing interaction

Quintessence with a potential motivated by supergravity (SUGRA) exhibits several intriguing features. Depending on its initial conditions, it can behave either as dynamical dark energy or effectively as a cosmological constant. Moreover, when quintessence is coupled to dark matter, the effective dark-energy equation of state can cross the phantom divide. In this paper, we test both coupled and uncoupled SUGRA quintessence models using DESI BAO, DES-Dovekie SNIa, and Planck CMB data. We find that current observations strongly favor a coupling between dark energy and dark matter, with the coupling parameter deviating from zero at more than $4σ$. The data also favor the branch of coupled SUGRA quintessence in which the energy transfer between the two dark sectors changes sign, leading to a crossing of the phantom divide by the effective dark-energy equation of state. Interestingly, this coupled SUGRA branch is statistically indistinguishable from dark energy described by the CPL parametrization, with only a very small difference in $χ^2_\mathrm{min}$. Our results suggest that coupled quintessence with a SUGRA potential provides a field-theoretic realization of the evolving dark energy behavior favored by the latest observations.

astro-ph.CO↗

arXiv2026

QHyer: Q-conditioned Hybrid Attention-mamba Transformer for Offline Goal-conditioned RL

Offline goal-conditioned RL (GCRL) learns goal-reaching policies from static datasets, but real-world datasets are often partially observable and history-dependent, exhibiting a mix of Markovian and non-Markovian that violate standard RL assumptions. History-aware sequence models such as Decision Transformer (DT) are a natural fit for long-term dependency modeling, yet pure attention is inefficient and brittle when handling local Markovian structure and long-range context simultaneously. Although recent hybrid architectures (e.g., LSDT) introduce local extractors to improve local dependencies modeling, the fixed-window extraction cannot adapt its effective memory to varying dependency lengths in temporally heterogeneous settings, often truncating long-range context rather than compressing its content adaptively. Moreover, sequential offline GCRL faces a key bottleneck: under sparse rewards, return-to-go (RTG) becomes non-discriminative across sub-trajectories, providing little guidance signal for stitching goal-reaching behaviors from diverse demonstrations. To address these, we propose \textbf{QHyer}, which replaces RTG with a flow-parameterized, state-conditioned goal-reaching Q-estimator to support stitching across demonstrations, and introduces a gated Hybrid Attention-Mamba backbone that performs content-adaptive history compression while preserving local dynamics. Extensive experiments demonstrate that \textbf{QHyer} achieves state-of-the-art performance on both non-Markovian and Markovian datasets, validating its effectiveness for diverse scenarios.

cs.LG↗

arXiv2026

Repeated Sunspot Light Bridge Jets Associated with Slipping Base Brightenings

Light bridge (LB) jets offer a unique window into small-scale eruptive phenomena within sunspots, the Sun's strongest magnetic environments; however, their generation mechanism remains a subject of debate. Using high-resolution observations from the New Vacuum Solar Telescope (NVST), we investigated six recurrent light bridge jets and the slipping motions of their jet base points (JBPs). Analogous to coronal jets, our observations show that these LB jets are characterized by a preceding JBP followed by a collimated jet spire. The JBP of each repeated jet along the LB displays apparent slipping motion at velocities of 0.6-1.5 km/s, which is temporally correlated with quasi-periodic enhanced photospheric horizontal motion of 1.3-6.5 km/s. Following the slipping JBPs, the resulting jet spires' fronts display similar slipping behaviors within the upper solar atmosphere. The Chinese Ha Solar Explorer (CHASE) reveals Ellerman-bomb-like spectral signatures at the JBPs, confirming that magnetic reconnection is operating at the jet base. Based on these results, we propose that repeated 3D reconnection occurring between the horizontal LB field and the ambient vertical umbral field may drive these LB jets. This process appears to be driven and/or modulated by quasi-periodic horizontal motion fueled by convective upflows and the transport of magnetic flux along the light bridge. This work suggests that some LB jets share a common reconnection-driven mechanism with coronal jets and provides direct evidence of slipping reconnection occurring along the sunspot light bridge.

astro-ph.SR↗

arXiv2026

Rapid LoRA Aggregation for Wireless Channel Adaptation in Open-Set Radio Frequency Fingerprinting

Radio frequency fingerprints (RFFs) enable secure wireless authentication but struggle in open-set scenarios with unknown devices and varying channels. Existing methods face challenges in generalization and incur high computational costs. We propose a lightweight, self-adaptive RFF extraction framework using Low-Rank Adaptation (LoRA). By pretraining LoRA modules per environment, our method enables fast adaptation to unseen channel conditions without full retraining. During inference, a weighted combination of LoRAs dynamically enhances feature extraction. Experimental results demonstrate a 15% reduction in equal error rate (EER) compared to non-finetuned baselines and an 83% decrease in training time relative to full fine-tuning, using the same training dataset. This approach provides a scalable and efficient solution for open-set RFF authentication in dynamic wireless vehicular networks.

eess.SP↗

arXiv2026

Spectroscopic Case Studies of Four Long-duration Transition-region Explosive Events

This work presents a detailed spectroscopic case study of four long-duration transition-region (TR) explosive events (EEs) observed in NOAA Active Region 13213 on 2023 February 10 using the Interface Region Imaging Spectrograph. The dynamic spectral evolution of each event is tracked through multicomponent Gaussian fitting of the Si IV 1403 Å line profiles. Three recurrent spectral morphologies are identified and characterized: bilateral wing enhancement, exclusive red-wing enhancement, and exclusive blue-wing enhancement, among which bilateral enhancement is the most common in the studied cases. Throughout their lifetimes of 20-25 minutes, these events display sustained and evolving bidirectional flows, with high-velocity components ($|v|$ > 100 km $s^{-1}$) emerging in late phases. These spectral signatures are interpreted as evidence of ongoing or recurrent magnetic reconnection, where bilateral profiles correspond to bidirectional outflows, and exclusive wing enhancements represent geometric or evolutionary phases of the same process. In contrast, cotemporal flare ribbons and loop structures exhibit pronounced, unidirectional redshifts. This study underscores that significant non-Gaussian wing enhancement, rather than exclusively high speed, constitutes a defining spectroscopic signature of EEs, and provides detailed kinematic constraints on the dynamics of such TR EEs.

astro-ph.SR↗

arXiv2026

Quasiperiodic Slipping Motion of Flare Ribbon Fine Structures Anchored in a Sunspot Light Bridge

We used high-resolution observations from the New Vacuum Solar Telescope and the Solar Dynamics Observatory to carry out a detailed multiwavelength analysis of the fine structures in the flare ribbon of a C3.9-class flare on 22 April 2021. A segment of the flare ribbon was rooted in a sunspot light bridge and exhibited discrete substructures, which we term "burrs", with equivalent diameters of 233-895 km and inter-core separations of 1129-1739 km. These structures are characterized by discrete redshifted cores accompanied by "tails" with lengths of 700-1370 km and widths of 310-600 km that show faint blueshifts. The burrs display systematic slipping motions along the ribbon, with apparent velocities decreasing from about 40 to 21 km/s, and show a distinct quasi-periodicity of about 6 minutes in H-alpha and EUV passbands. Differential emission measure analysis indicates that the emitting plasma is multi-thermal and dominated by temperatures of 1-2 MK. The observed morphology and kinematics are consistent with impulsive energy deposition by precipitating plasmoids, or oblique flux ropes, produced by tearing-mode fragmentation in the coronal current sheet. The close spatiotemporal association between the tails and blueshifts supports the interpretation that these features are related to untwisting magnetic flux ropes. The approximately 6-minute periodicity further suggests that the reconnection process may be modulated by photospheric p-mode oscillations coupled with tearing-mode instability. These results provide observational evidence that light-bridge-anchored fine structures can act as elementary units of flare energy release.

astro-ph.SR↗

arXiv2026

SanD-Planner: Sample-Efficient Diffusion Planner in B-Spline Space for Robust Local Navigation

The challenge of generating reliable local plans has long hindered practical applications in highly cluttered and dynamic environments. Key fundamental bottlenecks include acquiring large-scale expert demonstrations across diverse scenes and improving learning efficiency with limited data. This paper proposes SanD-Planner, a sample-efficient diffusion-based local planner that conducts depth image-based imitation learning within the clamped B-spline space. By operating within this compact space, the proposed algorithm inherently yields smooth outputs with bounded prediction errors over local supports, naturally aligning with receding-horizon execution. Integration of an ESDF-based safety checker with explicit clearance and time-to-completion metrics further reduces the training burden associated with value-function learning for feasibility assessment. Experiments show that training with $500$ episodes (merely $0.25\%$ of the demonstration scale used by the baseline), SanD-Planner achieves state-of-the-art performance on the evaluated open benchmark, attaining success rates of $90.1\%$ in simulated cluttered environments and $72.0\%$ in indoor simulations. The performance is further proven by demonstrating zero-shot transferability to realistic experimentation in both 2D and 3D scenes. The dataset and pre-trained models will also be open-sourced.

cs.RO↗

arXiv2026

Deliberative Reasoning Network: An Uncertainty-Driven Paradigm for Belief-Tracked Inference with Pretrained Language Models

Large language models often fail at logical reasoning when semantic heuristics conflict with decisive evidence - a phenomenon we term cognitive traps. To address this fundamental limitation, we introduce the Deliberative Reasoning Network (DRN), a novel paradigm that reframes logical reasoning from probability maximization to uncertainty minimization. Instead of asking "Which answer is most likely?", DRN asks "Which hypothesis has the most internally consistent evidence?". DRN achieves intrinsic interpretability by explicitly tracking belief states and quantifying epistemic uncertainty for competing hypotheses through an iterative evidence synthesis process. We validate our approach through two complementary architectures - a bespoke discriminative model that embodies the core uncertainty minimization principle, and a lightweight verification module that enhances existing generative LLMs. Evaluated on LCR-1000, our new adversarial reasoning benchmark designed to expose cognitive traps, the bespoke DRN achieves up to 15.2% improvement over standard baselines. When integrated as a parameter-efficient verifier with Mistral-7B, our hybrid system boosts accuracy from 20% to 80% on the most challenging problems. Critically, DRN demonstrates strong zero-shot generalization, improving TruthfulQA performance by 23.6% without additional training, indicating that uncertainty-driven deliberation learns transferable reasoning principles. We position DRN as a foundational, verifiable System 2 reasoning component for building more trustworthy AI systems.

cs.AI↗