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Zheng Sun

Publications and source records attributed to Zheng Sun.

At least 19 recordsLinked to original sources
arXiv2026

Limiter-based fully-discrete entropy stable explicit DG schemes for ideal MHD equations

We propose a class of high-order fully-discrete entropy stable (ES) explicit discontinuous Galerkin (DG) solvers for the compressible ideal magnetohydrodynamics (MHD) equations. Our main theoretical contribution is the introduction of a novel generalized-path-decomposition framework for MHD equations in Godunov's symmetric form. By innovatively interpreting the interior volume integral of the non-conservative source term as a path integral along a generalized path constructed by the solution polynomial, we establish the weak cell entropy inequality for the fully-discrete DG schemes. This overarching framework also accommodates other existing DG solvers based on the symmetric form. Combined with a carefully designed ES limiter, the proposed scheme satisfies the genuine fully-discrete cell entropy inequality. With this property, a Lax--Wendroff-type theorem can be obtained to show that the solution limit satisfies the entropy condition. Finally, the scheme is naturally compatible with the locally divergence-free space. Extensive numerical experiments demonstrate the scheme's low numerical dissipation and strong robustness.

math.NA↗
arXiv2026

Intense but Harmless: Exo-Space Weather Around an M Dwarf with a Single-Hemisphere Dynamo

M dwarfs are among the most promising host stars in the search for habitable exoplanets. However, their active atmospheres drive intense magnetic activity, including energetic flares and possibly coronal mass ejections (CMEs), which may pose serious threats to planetary habitability. In this study, we perform three-dimensional magnetohydrodynamic (MHD) simulations of CMEs on a fully convective M dwarf with a rotation period of 30 days, corresponding to the moderate-rotation regime. The magnetic topology driving our simulations is adopted from an exploratory global dynamo simulation of a fully convective low-mass star exhibiting a single-hemisphere magnetic configuration, which is not yet observationally confirmed. The large-scale magnetic field is mostly restricted to a single hemisphere and characterized by high-latitude polarity inversion lines (PILs), with the implication that most CMEs should originate from high latitudes. We find that these high-latitude CMEs propagate radially and away from the equatorial plane, producing only weak and spatially limited disturbances along the equatorial orbits of exoplanets. Moreover, low-latitude CMEs experience stronger drag within the dense and slow stellar wind near the equator, which significantly reduces both their propagation speeds and their overall impact on exoplanets. The resulting dynamic pressure enhancements on equatorial exoplanets caused by these CMEs are within two orders of magnitude above the quiescent conditions, much lower than those reported in previous M-dwarf CME simulations. These results indicate that, if such magnetic topologies indeed exist on M dwarfs, they may produce a relatively benign CME environment, which could be favorable for planetary habitability at face value.

astro-ph.SR↗
arXiv2026

On Energy Laws and Stability of First-Subdiagonal Pade Approximants for Linear Seminegative Problems

We derive an explicit discrete energy identity for rational time discretizations generated by the first-subdiagonal Pad\'e approximants of the exponential for solving linear seminegative problems. This work extends the diagonal Pad\'e energy laws in [Z. Sun, Y. Wei, and K. Wu, SIAM J. Numer. Anal., 60 (2022)] to the first-subdiagonal family. The main new ingredient is an explicit Cholesky-type factorization of the energy coefficient matrix associated with the semi-inner-product terms in the discrete energy identity. The construction and proof of this factorization are nontrivial, since the matrix entries are alternating sums of Pad\'e coefficients and the triangular factor has a parity-dependent factorial structure. We prove the factorization by reducing it to scalar rational identities and establishing them through finite product reductions and telescoping summations. Together with a \beta-coefficient cancellation, the factorization yields an exact discrete energy law that recovers the classical unconditional contractivity for linear seminegative problems. Numerical experiments adapted from the diagonal Pad\'e energy-law setting illustrate the predicted order and verify the discrete dissipation identity.

math.NA↗
arXiv2026

Counterdirectional Exciton and Trion Motion in Applied Electric Field

Charged excitonic complexes are central to the optoelectronic and many-body properties of semiconductors, yet their real-space transport dynamics remain largely unexplored. Here, we report the direct optical observation of trion motion under an applied electric field. The trions exhibit electrically driven drift with velocities approaching {$10^5~\mathrm{m/s}$}. Unexpectedly, the trion flow induces a pronounced back-action on coexisting neutral excitons, driving them in the opposite direction and giving rise to counterpropagating exciton-trion transport. Our results reveal an interaction-driven nonequilibrium transport regime of mixed excitonic fluids and establish a direct route for imaging the dynamics of more complex charged quasiparticles, including doubly charged excitons.

physics.optics↗
arXiv2026

How Magnetic Field Strength Affects Stellar Coronal Mass Ejection Dynamics

Observations show that stellar coronal mass ejection (CME) candidates display relatively lower kinetic energies compared to expectations from solar flare-CME relations extrapolated to the stellar regime. This behaviour was predicted by studies of magnetic confinement of CMEs by strong large-scale stellar magnetic fields. However, the possible promoting role of stronger small-scale magnetic fields has not yet been properly explored in previous studies. In this work, we present the first parametric study that simultaneously incorporates both the promoting and confining effects of magnetic field strength on CME dynamics. We perform CME simulations with scaled solar magnetograms spanning = 1, 5, 10, 50, 100 B_sun and inserting flux ropes whose magnetic energy is set to scale as E_FR \propt ^2. Our results show that CME speed and mass increase with magnetic field strength in this restrictive scenario, approximately following v_CME \propt and M_CME \propt ^1.5. These trends indicate that, within this idealized solar-scaled framework, increasing the magnetic field strength enhances the net promoting forces relative to the confining forces and drives faster, more massive CMEs. We further identify the upward Lorentz force as the dominant contributor to the acceleration and the mass enhancement. We also conducted additional cases with different flux rope energies that do not follow the above scaling assumption, and found that stronger flux ropes produce faster and more massive CMEs for each given stellar model. The adopted scaling assumptions are intended as a controlled parametric experiment rather than a realistic model of young solar-type stars, and future work using more realistic stellar magnetic maps will be required to determine which regions of the parameter space explored here are most relevant to active stars.

astro-ph.SR↗
arXiv2026

Beyond Point-Attached Semantics: Object-Centric Semantic Fields for Generalizable Manipulation

Generalizable robot manipulation requires stable 3D understanding of functional object parts, such as handles, tool heads, openings, and graspable regions. Raw point clouds provide geometry but lack explicit part semantics, and their sampled points vary with viewpoint, sensor configuration, and object instance. Existing 2D feature lifting and discrete 3D point-wise features enrich point clouds with semantics, but the resulting features remain attached to observation-dependent samples. We propose an object-centric continuous semantic field that conditions on an object point cloud and reads part-aware semantic embeddings at explicit 3D query locations. The field is trained from part-annotated object models and then frozen to generate semantic point clouds as object-level conditioning for manipulation policies. Experiments on RoboTwin simulation tasks and real-world bimanual object manipulation show that our representation provides more stable functional-part cues and improves policy performance over raw point-cloud, 2D feature lifting, and 3D point-wise feature baselines. Project Page: \href{https://zainzh.github.io/beyond-point-attached-semantics}{https://zainzh.github.io/beyond-point-attached-semantics}.

cs.RO↗
arXiv2026

TVD and TVB preservation without TVD time discretization for discontinuous Galerkin methods

Total variation diminishing (TVD) and total variation bounded (TVB) properties are crucial for controlling spurious oscillations in numerical solutions of conservation laws. In the classical Runge--Kutta (RK) discontinuous Galerkin (DG) framework, enforcing these properties is intrinsically tied to TVD time integrators, more commonly known today as strong-stability-preserving (SSP) methods. This reliance imposes severe structural restrictions, including order barriers and incompatibility with various fully discrete DG formulations, ranging from the recent RKDG method with compact stencils (cRKDG) to the widely established Arbitrary DERivative (ADER) DG method. To bypass these constraints, we propose a novel trace-limited corrector framework that preserves the TVD/TVB-in-the-means properties using generic, non-SSP time stepping. Based on Harten's lemma, our key insight is that total variation stability is dictated solely by the cell-average update in the final corrector stage. Consequently, we modify the traces in the numerical fluxes exclusively in the final stage, leaving the intermediate predictor stages unconstrained. This strategy decouples oscillation control from the SSP restriction, accommodates standard RKDG, cRKDG, and ADER-DG predictors, and retains the compactness of the cRKDG framework. We also prove that the limiter does not activate in smooth regions, thereby preserving the underlying accuracy. Finally, numerical experiments are presented to demonstrate the capabilities and robustness of the method.

math.NA↗
arXiv2026

Fine-scale downflows above flare ribbons captured by Solar Orbiter/EUI

In solar flares, flare ribbons map chromospheric footpoints where flare energy deposition occurs. These locations are associated with field aligned energy transport from the corona that results from energy liberated during magnetic reconnection. Recent chromospheric observations in the H$\alpha$ and H$\beta$ bands have revealed fine-scale downflow structures above flare ribbons, referred to as riblets. In this study, we identify similar downflow structures in the extreme-ultraviolet (EUV) wavelength using high-resolution observations from Solar Orbiter/EUI. These fine-scale downflows appear as downward-propagating, bright, and thread-like structures. They exhibit typical velocities of $\sim100~\mathrm{km\ s^{-1}}$, lifetimes of $\sim15$~s, and lengths of $\sim1.6$~Mm. Based on their morphological and dynamical properties, we interpret these observed downflows as the EUV counterparts of the riblets that have previously been reported from chromospheric observations. This study presents EUV imaging of $\sim 10^6$~K downflows above flare ribbons. We interpret these downflows as a result of (1) the energisation and subsequent compression of pre-existing chromospheric fibrils due to particle beams or (2) adiabatic or shock-driven compression induced by the downward-propagating plasma from the corona. These fine-scale EUV riblets provide a new diagnostic tool for probing the dynamics of magnetic reconnection as well as energy transport and deposition during solar flares.

astro-ph.SR↗
arXiv2026

PaperFlow: Profiling, Recommending, and Adapting Across Daily Paper Streams

Scientific paper recommendation is typically evaluated as static ranking over a fixed candidate set, yet real scientific reading unfolds as a daily, longitudinal process in which interests shift and feedback accumulates. We introduce PaperFlow, a framework that organizes it into three coupled stages: Profiling, which constructs and maintains a structured, inspectable scholarly profile from heterogeneous cold-start evidence; Recommending, which ranks each date-specific paper stream through multi-signal aggregation under a fixed display budget; and Adapting, which updates user state from semantically distinct feedback signals and models interest drift across days. We further define a longitudinal user-day benchmark that fixes users, dates, candidate pools, visible inputs, and hidden simulated relevance labels under a shared temporal information boundary. The benchmark contains 24 simulated research users, 50 daily paper streams, 1,200 user-day episodes, 20,727 unique papers, and 497,448 episode-paper records. We additionally specify a blind human-evaluation protocol to validate alignment between automatic metrics and expert judgments. Experiments against five scientific recommendation baselines show that PaperFlow achieves the strongest oracle-based ranking, the highest behavioral alignment with simulated reading selections, and the best blind human-evaluation score.

cs.IR↗
arXiv2026

PAGER: Bridging the Semantic-Execution Gap in Point-Precise Geometric GUI Control

Large vision-language models have significantly advanced GUI agents, enabling executable interaction across web, mobile, and desktop interfaces. Yet these gains largely rely on a forgiving region-tolerant paradigm, where many nearby pixels inside the same component remain valid. Precise geometric construction breaks this assumption: actions must land on points in continuous canvas space rather than tolerant regions. Because geometric primitives carry ontological dependencies, a local coordinate error can induce cascading topological failures that distort downstream objects and invalidate the final construction. We identify this regime as precision-sensitive GUI tasks, requiring point-level accuracy, geometry-aware verification, and robustness to dependency-driven error propagation. To benchmark it, we introduce PAGE Bench, with 4,906 problems and over 224K process-supervised, pixel-level GUI actions. We further propose PAGER, a topology-aware agent that decomposes construction into dependency-structured planning and pixel-level execution. Pixel-grounded supervised tuning establishes executable action grammar, while precision-aligned reinforcement learning mitigates rollout-induced exposure bias through state-conditioned geometric feedback. Experiments reveal a pronounced Semantic-Execution Gap: general multimodal models can exceed 88% action type accuracy yet remain below 6% task success. PAGER closes this gap, delivering 4.1x higher task success than the strongest evaluated general baseline and raising step success rate from below 9% for GUI-specialized agents to over 62%, establishing a new state of the art for point-precise GUI control.

cs.AI↗
arXiv2026

Solar Energetic Particle Events and Associated Type II Radio Bursts from Different Source Regions

Large solar energetic particle (SEP) events are thought to originate from the shocks driven by fast coronal mass ejections (CMEs) and thus generally accompanied by type II radio bursts. However, a significant proportion of type II radio bursts is not accompanied by SEP events. To study the relationship between SEPs and type II radio bursts and the associated physical mechanisms, we statistically analyze 43 SEP halo-CMEs and 131 non-SEP halo-CMEs observed from 2010 to 2024, and check the related properties of type II radio bursts and solar source region. We find nearly all SEP events and approximately two-thirds of non-SEP events are accompanied by type II radio bursts. Type II radio bursts associated with SEP events usually have longer duration and lower ending frequencies. The starting frequency exhibits a clear source region dependence, being highest for ''single active region (AR)'', intermediate for ''multiple ARs'', and lowest for ''outside of ARs''. Furthermore, the spectra of both protons and electrons exhibit a similar softening trend in the three types of source regions. Joint analysis of spectra and type II radio bursts reveals that the proton spectra index has a good anti-correlation with the starting frequency of the type II radio bursts. Our statistical results have important implications for the mechanisms behind SEP acceleration

astro-ph.SR↗
arXiv2026

Imaging magnetically driven astrospheres: a forward modelling approach

An astrosphere is a vast, tailed bubble-like volume around a star, formed through the interaction between the stellar magnetic field, the stellar wind, and the interstellar medium (ISM). Detecting and characterizing astrospheres are essential for constraining stellar wind properties, understanding stellar evolution, and assessing the habitability of surrounding exoplanetary systems. Charge exchanges between ionized stellar wind particles and cold ISM hydrogen atoms populate the astrosphere with neutral hydrogen, which can leave observable signatures in the Lyman-$\alpha$ (Ly$\alpha$) line absorption profile. Previous studies have inferred stellar mass-loss rates by measuring Ly$\alpha$ absorption in stellar spectra caused by astrospheric neutral hydrogen. However, our knowledge of the global morphology of astrospheres remains limited and largely dependent on sometimes contradictory simulations. Here we investigate the feasibility of detecting Ly$\alpha$ emission generated by resonant scattering from \NH{} surrounding the star, enabling the construction of a two-dimensional map of the astrosphere. With a three-dimensional magnetohydrodynamic astrosphere model, we perform forward modelling of the Ly$\alpha$ emission and assess the observation feasibility according to the observational limits of the {\it Hubble Space Telescope} (HST). We further discuss the influence of varied line-of-sight orientations and averaged ISM velocity along the line-of-sight. The spatially resolved circumstellar Ly$\alpha$ emission could provide important constraints on the astrospheric configuration and stellar wind properties, such as the bow shock standing distance, the stellar wind symmetry, and the shape of the astro-tail. Our results highlight Ly$\alpha$ astrosphere detections as a promising science case for {\it HST} and future missions such as the \textit{Habitable Worlds Observatory}.}

astro-ph.SR↗
arXiv2026

GEditBench v2: A Human-Aligned Benchmark for General Image Editing

Recent advances in image editing have enabled models to handle complex instructions with impressive realism. However, existing evaluation frameworks lag behind: current benchmarks suffer from narrow task coverage, while standard metrics fail to adequately capture visual consistency, i.e., the preservation of identity, structure and semantic coherence between edited and original images. To address these limitations, we introduce GEditBench v2, a comprehensive benchmark with 1,200 real-world user queries spanning 23 tasks, including a dedicated open-set category for unconstrained, out-of-distribution editing instructions beyond predefined tasks. Furthermore, we propose PVC-Judge, an open-source pairwise assessment model for visual consistency, trained via two novel region-decoupled preference data synthesis pipelines. Besides, we construct VCReward-Bench using expert-annotated preference pairs to assess the alignment of PVC-Judge with human judgments on visual consistency evaluation. Experiments show that our PVC-Judge achieves state-of-the-art evaluation performance among open-source models and even surpasses GPT-5.1 on average. Finally, by benchmarking 16 frontier editing models, we show that GEditBench v2 enables more human-aligned evaluation, revealing critical limitations of current models, and providing a reliable foundation for advancing precise image editing.

cs.CV↗
arXiv2026

A limiter-based approach to construct high-order fully-discrete entropy stable explicit DG schemes for hyperbolic conservation laws

This paper presents a class of novel high-order fully-discrete entropy stable (ES) discontinuous Galerkin (DG) schemes with explicit time discretization. The proposed methodology exploits a critical observation from [4] that the cell averages of classical DG solutions with forward Euler time stepping satisfy an ``entropy-stable-like'' property. Building on this result, fully-discrete entropy stability is rigorously enforced through a simple Zhang--Shu-type scaling limiter [45] applied as a post-processing step, without modifying the underlying spatial discretization. Furthermore, the proposed methodology can simultaneously enforce multiple cell entropy inequalities, a capability unavailable in existing ES DG schemes. High-order accuracy in time is achieved by using strong-stability-preserving (SSP) multistep methods. Theoretically, we prove that the proposed scheme indeed maintains high-order accuracy and establish a Lax--Wendroff-type theorem guaranteeing that the limit of the numerical solutions, if it exists, satisfies the desired entropy inequality. Extensive numerical tests for scalar equations and systems, including the nonconvex Buckley--Leverett problem and extreme examples of Euler equations, demonstrate optimal accuracy, enforcement of multiple entropy conditions, and strong robustness.

math.NA↗
arXiv2026

Twist-angle evolution from valley-polarized fractional topological phases to valley-degenerate superconductivity in twisted bilayer MoTe2

Moir\'e superlattices formed by semiconducting transition metal dichalcogenides (TMDs) provide a highly tunable platform for investigating strongly correlated and topological quantum phases. As a prototypical example, twisted bilayer MoTe2 (tMoTe2) has been shown to host fractional topological phases, such as zero-field fractional Chern insulators (FCIs) exhibiting fractional quantum anomalous Hall (FQAH) effects. However, how these correlated topological phases evolve with twist angle and compete with other quantum phases in tMoTe2 remains largely unexplored. Here we report a systematic transport study of twist-angle-dependent phase diagrams in tMoTe2 across a range of 3.8{\deg}-5.78{\deg}, revealing an evolution from fractionalized states of matter with spontaneous valley polarization to valley-degenerate superconductivity. At relatively small twist angles, partially-filled Chern bands of tMoTe2 host FQAH states following the Jain sequence, together with signatures of an anomalous composite Fermi liquid at moir\'e hole filling factor {\nu}h = 1/2. Increasing twist angle progressively suppresses fractional topological phases and reconstructs the half-filled Chern band into symmetry-breaking integer Chern insulating states. At {\nu}h = 1, we observe a transition from robust integer quantum anomalous Hall (IQAH) insulators at small angles to displacement-field-tuned, topologically trivial correlated insulators at larger angles. Remarkably, at a twist angle of 5.78{\deg}, superconductivity emerges adjacent to the correlated insulating phase, with a phase diagram closely resembling that recently reported in twisted bilayer WSe2 (tWSe2). Our results uncover a unified twist-angle-driven phase evolution linking fractional topology, symmetry breaking, magnetic order, and superconductivity, providing new insight into the emergent quantum phenomena in moir\'e systems.

cond-mat.mes-hall↗
arXiv2026

PersonaTrace: Synthesizing Realistic Digital Footprints with LLM Agents

Digital footprints (records of individuals' interactions with digital systems) are essential for studying behavior, developing personalized applications, and training machine learning models. However, research in this area is often hindered by the scarcity of diverse and accessible data. To address this limitation, we propose a novel method for synthesizing realistic digital footprints using large language model (LLM) agents. Starting from a structured user profile, our approach generates diverse and plausible sequences of user events, ultimately producing corresponding digital artifacts such as emails, messages, calendar entries, reminders, etc. Intrinsic evaluation results demonstrate that the generated dataset is more diverse and realistic than existing baselines. Moreover, models fine-tuned on our synthetic data outperform those trained on other synthetic datasets when evaluated on real-world out-of-distribution tasks.

cs.CL↗
arXiv2026

Fine Structure and Formation Mechanism of a Sunspot Bipolar Light Bridge in NOAA AR 13663

Bipolar Light Bridges (BLBs) are bright regions located between sunspot umbrae of opposite magnetic polarity. They are typically characterized by strong magnetic fields and intense flows, which are believed to be closely associated with major solar flares. Despite their importance, their fine structure, formation and evolution remain poorly understood. In this work, we analyze the observations of a well-defined BLB obtained by the Goode Solar Telescope at the Big Bear Solar Observatory and the Helioseismic and Magnetic Imager onboard the Solar Dynamics Observatory. The high-resolution GST observations reveal that the BLB is composed of fine, penumbral filament-like structures with widths of approximately 100-150 km. The corresponding Doppler velocity maps present a stable pattern of spatially adjacent red- and blueshifted patches within the BLB throughout the 5.5-hour GST observation. HMI observations show that the BLB arises from the converging and shearing motions of sunspots with opposite polarities. Penumbral regions originating from different polarities gradually evolve and interact, eventually forming the BLB. The observed Doppler velocity pattern, characterized by red- and blueshifted patches, can be interpreted as a projection effect of the Evershed flow within the penumbrae. Therefore, we argue that the BLB is formed through the compression and stretching of penumbral structures from oppositely polarized sunspots.

astro-ph.SR↗
arXiv2026

How RL Unlocks the Aha Moment in Geometric Interleaved Reasoning

Solving complex geometric problems inherently requires interleaved reasoning: a tight alternation between constructing diagrams and performing logical deductions. Although recent Multimodal Large Language Models (MLLMs) have demonstrated strong capabilities in visual generation and plotting, we identify a counter-intuitive and underexplored phenomenon. Naively applying Supervised Fine-Tuning (SFT) on interleaved plot-solution data leads to a substantial degradation in reasoning performance compared to text-only baselines. We argue that this failure stems from a fundamental limitation of SFT, which primarily induces distributional alignment: the model learns to reproduce the surface format of interleaved plotting but fails to internalize the causal dependency between the generated plot and reasoning steps. To overcome this limitation, we propose Faire (Functional alignment for interleaved reasoning), a reinforcement learning framework that enforces three casual constraints to move beyond superficial imitation toward functional alignment. Extensive experiments show that Faire induces a qualitative shift in model behavior in which the plotting is effectively internalized, yielding competitive performance on challenging geometric reasoning benchmarks.

cs.CL↗