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Researcher profile

Li Zhang

Li Zhang contributes to research discovery and scholarly infrastructure.

ResearcherAffiliation not importedOpen to collaborate
Artificial IntelligenceComputer Visionhep-exComputation and LanguageSoftware Engineeringcond-mat.mes-hallcond-mat.mtrl-sciCryptography and SecurityHardware Architecture

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Published work

26 published item(s)

preprint2026arXiv

An Enigmatic PeVatron in an Area around HII Region G35.6$-$0.5

Identifying Galactic PeVatrons (PeV particle accelerators) from the ultra-high-energy (UHE, >100 TeV) $γ$-ray sources plays a crucial role in revealing the origin of Galactic cosmic rays. The UHE source 1LHAASO J1857+0203u is suggested to be associated with HESS J1858+020, which may be attributed to the possible PeVatron candidate supernova remnant (SNR) G35.6$-$0.4 or HII region G35.6$-$0.5. We perform detailed analysis on the very-high-energy and UHE $γ$-ray emissions towards this region with data from the Large High Altitude Air Shower Observatory (LHAASO). 1LHAASO J1857+0203u is detected with a significance of 11.6$σ$ above 100 TeV, indicating the presence of a PeVatron. It has an extension of $\sim 0.18^\circ$ with a power-law (PL) spectral index of $\sim$2.5 in 1-25 TeV and a point-like emission with a PL spectral index of $\sim$3.2 above 25 TeV. Using the archival CO and HI data, we identify some molecular and atomic clouds that may be associated with the TeV $γ$-ray emissions. Our modelling indicates that the TeV $γ$-ray emissions are unlikely to arise from the clouds illuminated by the protons that escaped from SNR G35.6$-$0.4. In the scenario that HII region G35.6$-$0.5 could accelerate particles to the UHE band, the observed GeV-TeV $γ$-ray emission could be well explained by a hadronic model with a PL spectral index of $\sim$2.0 and cutoff energy of $\sim$450 TeV. However, an evolved pulsar wind nebula origin cannot be ruled out.

0 citations0 reviewsNo code linkedOpen access
preprint2026arXiv

An Ultrahigh-energy $γ$-ray Bubble Powered by a Super PeVatron

We report the detection of a $γ$-ray bubble spanning at least 100$\rm deg^2$ in ultra high energy (UHE) up to a few PeV in the direction of the star-forming region Cygnus X, implying the presence Super PeVatron(s) accelerating protons to at least 10 PeV. A log-parabola form with the photon index $Γ(E) = (2.71 \pm 0.02) + (0.11 \pm 0.02) \times \log_{10} (E/10 \ {\rm TeV})$ is found fitting the gamma-ray energy spectrum of the bubble well. UHE sources, `hot spots' correlated with very massive molecular clouds, and a quasi-spherical amorphous $γ$-ray emitter with a sharp central brightening are observed in the bubble. In the core of $\sim 0.5^{\circ}$, spatially associating with a region containing massive OB association (Cygnus OB2) and a microquasar (Cygnus X-3), as well as previously reported multi-TeV sources, an enhanced concentration of UHE $γ$-rays are observed with 2 photons at energies above 1 PeV. The general feature of the bubble, the morphology and the energy spectrum, are reasonably reproduced by the assumption of a particle accelerator in the core, continuously injecting protons into the ambient medium.

0 citations0 reviewsNo code linkedOpen access
preprint2026arXiv

CodeMEM: AST-Guided Adaptive Memory for Repository-Level Iterative Code Generation

Large language models (LLMs) substantially enhance developer productivity in repository-level code generation through interactive collaboration. However, as interactions progress, repository context must be continuously preserved and updated to integrate newly validated information. Meanwhile, the expanding session history increases cognitive burden, often leading to forgetting and the reintroduction of previously resolved errors. Existing memory management approaches show promise but remain limited by natural language-centric representations. To overcome these limitations, we propose CodeMEM, an AST-guided dynamic memory management system tailored for repository-level iterative code generation. Specifically, CodeMEM introduces the Code Context Memory component that dynamically maintains and updates repository context through AST-guided LLM operations, along with the Code Session Memory that constructs a code-centric representation of interaction history and explicitly detects and mitigates forgetting through AST-based analysis. Experimental results on the instruction-following benchmark CodeIF-Bench and the code generation benchmark CoderEval demonstrate that CodeMEM achieves state-of-the-art performance, improving instruction following by 12.2% for the current turn and 11.5% for the session level, and reducing interaction rounds by 2-3, while maintaining competitive inference latency and token efficiency.

0 citations0 reviewsNo code linkedOpen access
preprint2026arXiv

Constraining the Cosmic-ray Energy Based on Observations of Nearby Galaxy Clusters by LHAASO

Galaxy clusters act as reservoirs of high-energy cosmic rays (CRs). As CRs propagate through the intracluster medium, they generate diffuse $γ$-rays detectable by arrays such as LHAASO. These $γ$-rays result from proton-proton ($pp$) collisions of very high-energy cosmic rays (VHECRs) or inverse Compton (IC) scattering of positron-electron pairs created by $pγ$ interactions of ultra-high-energy cosmic rays (UHECRs). We analyzed diffuse $γ$-ray emission from the Coma, Perseus, and Virgo clusters using LHAASO data. Diffuse emission was modeled as a disk of radius $R_{500}$ for each cluster while accounting for point sources. No significant diffuse emission was detected, yielding 95\% confidence level (C.L.) upper limits on the $γ$-ray flux: for WCDA (1-25~TeV) and KM2A ($>25$~TeV), less than $(49.4, 13.7, 54.0)$ and $(1.34, 1.14, 0.40) \times 10^{-14}$~ph~cm$^{-2}$~s$^{-1}$ for Coma, Perseus, and Virgo, respectively. The $γ$-ray upper limits can be used to derive model-independent constraints on the integral energy of CRp above 10~TeV (corresponding to the LHAASO observational range $>1$~TeV under the $pp$ scenario) to be less than $(1.96, 0.59, 0.08) \times 10^{61}$~erg. The absence of detectable annuli/ring-like structures, indicative of cluster accretion or merging shocks, imposes further constraints on models in which the UHECRs are accelerated in the merging shocks of galaxy clusters.

0 citations0 reviewsNo code linkedOpen access
preprint2026arXiv

Constraints on heavy decaying dark matter from 570 days of LHAASO observations

The Kilometer Square Array~(KM2A) of the Large High Altitude Air Shower Observatory (LHAASO) aims at surveying the northern gamma-ray sky at energies above 10 TeV with unprecedented sensitivity. Gamma-ray observations have long been one of the most powerful tools for dark matter searches, as e.g., high-energy gamma-rays could be produced by the decays of heavy dark matter particles. In this letter, we present the first dark matter analysis with LHAASO-KM2A, using the first 340~days of data from 1/2-KM2A and 230~days of data from 3/4-KM2A. Several regions of interest are used to search for a signal and account for the residual cosmic-ray background after gamma/hadron separation. We find no excess of dark matter signals, and thus place some of the strongest gamma-ray constraints on the lifetime of heavy dark matter particles with mass between 10^5 and 10^9~GeV. Our results with LHAASO are robust, and have important implications for dark matter interpretations of the diffuse astrophysical high-energy neutrino emission.

0 citations0 reviewsNo code linkedOpen access
preprint2026arXiv

ContraFix: Agentic Vulnerability Repair via Differential Runtime Evidence and Skill Reuse

Large language model (LLM) agents are increasingly used for automated vulnerability repair (AVR), where repository-level reasoning enables them to inspect context and produce source-code patches. However, recent empirical results show that these agents still struggle with real-world vulnerabilities. Their main failure mode is semantic misunderstanding: choosing a repair direction that does not match the root cause. We identify two reasons for this gap. Existing agents usually reason from the failing execution alone. A crash report can pinpoint where the program failed, but it does not reveal which variable or state transition, among many candidates near the fault site, separates the crashing behavior from safe execution. As a result, agents often produce symptom-oriented patches instead of causal fixes. Moreover, evidence collected for one vulnerability is rarely retained, so similar cases in later repositories must be diagnosed again from scratch. We present ContraFix, an agentic AVR framework that couples differential runtime evidence with reusable repair skills. Its Mutator constructs PoC variants that straddle the failure boundary; its Analyzer inserts state probes around the fault region and summarizes divergences between crashing and non-crashing executions into a repair specification; and its Patcher converts the specification into verified source patches. Each successful repair updates a two-track skill base containing repair specifications and mutation strategies, which are retrieved through a three-tier policy for future instances. On SEC-Bench (C/C++, 200 instances) and PatchEval (Go, Python, JavaScript, 225 instances), ContraFix with GPT-5-mini resolves 84.0% and 73.8% of the tasks, respectively, achieving state-of-the-art performance on both benchmarks while costing less than one-third of the strongest comparable baseline.

0 citations0 reviewsNo code linkedOpen access
preprint2026arXiv

Deep view of Composite SNR CTA1 with LHAASO in $γ$-rays up to 300 TeV

The ultra-high-energy (UHE) gamma-ray source 1LHAASO J0007+7303u is positionally associated with the composite SNR CTA1 that is located at high Galactic Latitude $b\approx 10.5^\circ$. This provides a rare opportunity to spatially resolve the component of the pulsar wind nebula (PWN) and supernova remnant (SNR) at UHE. This paper conducted a dedicated data analysis of 1LHAASO J0007+7303u using the data collected from December 2019 to July 2023. This source is well detected with significances of 21$σ$ and 17$σ$ at 8$-$100 TeV and $>$100 TeV, respectively. The corresponding extensions are determined to be 0.23$^{\circ}\pm$0.03$^{\circ}$ and 0.17$^{\circ}\pm$0.03$^{\circ}$. The emission is proposed to originate from the relativistic electrons and positrons accelerated within the PWN of PSR J0007+7303. The energy spectrum is well described by a power-law with an exponential cutoff function $dN/dE = (42.4\pm4.1)(\frac{E}{20\rm\ TeV})^{-2.31\pm0.11}\exp(-\frac{E}{110\pm25\rm\ TeV})$ $\rm\ TeV^{-1}\ cm^{-2}\ s^{-1}$in the energy range from 8 TeV to 300 TeV, implying a steady-state parent electron spectrum $dN_e/dE_e\propto (\frac{E_e}{100\rm\ TeV})^{-3.13\pm0.16}\exp[(\frac{-E_e}{373\pm70\rm\ TeV})^2]$ at energies above $\approx 50 \rm\ TeV$. The cutoff energy of the electron spectrum is roughly equal to the expected current maximum energy of particles accelerated at the PWN terminal shock. Combining the X-ray and gamma-ray emission, the current space-averaged magnetic field can be limited to $\approx 4.5\rm\ μG$. To satisfy the multi-wavelength spectrum and the $γ$-ray extensions, the transport of relativistic particles within the PWN is likely dominated by the advection process under the free-expansion phase assumption.

0 citations0 reviewsNo code linkedOpen access
preprint2026arXiv

Discovery of a new $γ$-ray source LHAASO J0341+5258 with emission up to 200TeV

We report the discovery of a new unidentified extended $γ$-ray source in the Galactic plane named LHAASO J0341+5258 with a pre-trial significance of 8.2 standard deviations above 25 TeV. The best fit position is R.A.$=55.34^{\circ}\pm0.11^{\circ}$ and Dec$=52.97^{\circ}\pm0.07^{\circ}$. The angular size of LHAASO J0341+5258 is $0.29^\circ \pm 0.06^\circ_{stat} \pm0.02^\circ_{sys}$. The flux above 25 TeV is about $20\%$ of the flux of Crab Nebula. Although a power-law fit of the spectrum from 10 TeV to 200 TeV with the photon index $α=2.98 \pm 0.19_{stat} \pm 0.02_{sys}$ is not excluded, the LHAASO data together with the flux upper limit at 10 GeV set by the Fermi LAT observation, indicate a noticeable steepening of an initially hard power-law spectrum %($α\leq 1.75$) spectrum with a cutoff at $\approx 50$ TeV. We briefly discuss the origin of UHE gamma-rays. The lack of an energetic pulsar and a young SNR inside or in the vicinity of LHAASO J0341+5258 challenge, but do not exclude both the leptonic and hadronic scenarios of gamma-ray production.

0 citations0 reviewsNo code linkedOpen access
preprint2026arXiv

Discovery of the Ultra-high energy gamma-ray source LHAASO J2108+5157

We report the discovery of a UHE gamma-ray source, LHAASO J2108+5157, by analyzing the LHAASO-KM2A data of 308.33 live days. Significant excess of gamma-ray induced showers is observed in both energy bands of 25-100 TeV and $\gt$100 TeV with 9.5 sigma and 8.5 sigma, respectively. This source is not significantly favored as an extensive source with the angular extension smaller than the point-spread function of KM2A. The measured energy spectrum from 20 to 200 TeV can be approximately described by a power-law function with an index of -2.83$\pm$ 0.18stat. A harder spectrum is demanded at lower energies considering the flux upper limit set by Fermi-LAT observations. The position of the gamma-ray emission is correlated with a giant molecular cloud, which favors a hadronic origin. No obvious counterparts have been found, deeper multiwavelength observations will help to shed new light on this intriguing UHE source.

0 citations0 reviewsNo code linkedOpen access
preprint2026arXiv

Empowering Small Language Models with Factual Hallucination-Aware Reasoning for Financial Classification

Small language models (SLMs) are increasingly used for financial classification due to their fast inference and local deployability. However, compared with large language models, SLMs are more prone to factual hallucinations in reasoning and exhibit weaker classification performance. This raises a natural question: Can mitigating factual hallucinations improve SLMs' financial classification? To address this, we propose a three-step pipeline named AAAI (Association Identification, Automated Detection, and Adaptive Inference). Experiments on three representative SLMs reveal that: (1) factual hallucinations are positively correlated with misclassifications; (2) encoder-based verifiers effectively detect factual hallucinations; and (3) incorporating feedback on factual errors enables SLMs' adaptive inference that enhances classification performance. We hope this pipeline contributes to trustworthy and effective applications of SLMs in finance.

0 citations0 reviewsNo code linkedOpen access
preprint2026arXiv

Energy calibration of LHAASO-KM2A using the cosmic ray Moon shadow

We present a precise measurement of the westward, rigidity-dependent shift of the Moon's shadow using three and a half years of cosmic-ray data collected by the Kilometer Square Array (KM2A) of the Large High Altitude Air Shower Observatory (LHAASO). These measurements enable us to calibrate the detector energy response in the range 20-260 TeV, with results showing excellent agreement with the response derived from Monte Carlo (MC) simulations of the KM2A detector. We also measure a best-fit parameter $ε= 0.015 \pm 0.08$, corresponding to a 95% confidence interval of [-14%, +17%] for the energy-scale estimation. This result establishes the exceptional accuracy of the KM2A-MC in simulating the detector's response within this energy range.

0 citations0 reviewsNo code linkedOpen access
preprint2026arXiv

Energy-Dependent Shifts of Medium-Scale Anisotropies in Very-High-Energy Cosmic Rays Observed by LHAASO-KM2A

Small deviations from isotropy in the arrival directions of Galactic cosmic rays serve as a unique probe of the local magnetic environment. In this Letter, we report observations of medium-scale anisotropies (MSA) at energies above 10 TeV using the LHAASO-KM2A array. Our analysis identifies four regions of excess and four regions of deficit, each spanning angular scales of approximately ten degrees. Crucially, we detect significant energy-dependent shifts in the centroids of two excess regions: Region B and the newly identified Region $\mathrm{\widetilde{D}}$. We also characterize the energy evolution of the fractional relative intensity across both excess and deficit regions. These findings imply that the observed anisotropies are shaped by the specific realization of the local turbulent magnetic field within the cosmic ray scattering length. Such energy-dependent behaviors impose strict constraints on local turbulence models and cosmic ray propagation theories.

0 citations0 reviewsNo code linkedOpen access
preprint2026arXiv

Evidence for particle acceleration approaching PeV energies in the W51 complex

The $γ$-ray emission from the W51 complex is widely acknowledged to be attributed to the interaction between the cosmic rays (CRs) accelerated by the shock of supernova remnant (SNR) W51C and the dense molecular clouds in the adjacent star-forming region, W51B. However, the maximum acceleration capability of W51C for CRs remains elusive. Based on observations conducted with the Large High Altitude Air Shower Observatory (LHAASO), we report a significant detection of $γ$ rays emanating from the W51 complex, with energies from 2 TeV to 200 TeV. The LHAASO measurements, for the first time, extend the $γ$-ray emission from the W51 complex beyond 100 TeV and reveal a significant spectrum bending at tens of TeV. By combining the ``$π^0$-decay bump" featured data from Fermi-LAT, the broadband $γ$-ray spectrum of the W51 region can be well-characterized by a simple pp-collision model. The observed spectral bending feature suggests an exponential cutoff at $\sim400$~TeV or a power-law break at $\sim200$~TeV in the CR proton spectrum, most likely providing the first evidence of SNRs serving as CR accelerators approaching the PeV regime. Additionally, two young star clusters within W51B could also be theoretically viable to produce the most energetic $γ$ rays observed by LHAASO. Our findings strongly support the presence of extreme CR accelerators within the W51 complex and provide new insights into the origin of Galactic CRs.

0 citations0 reviewsNo code linkedOpen access
preprint2026arXiv

Exploring Lorentz Invariance Violation from Ultra-high-energy Gamma Rays Observed by LHAASO

Recently the LHAASO Collaboration published the detection of 12 ultra-high-energy gamma-ray sources above 100 TeV, with the highest energy photon reaching 1.4 PeV. The first detection of PeV gamma rays from astrophysical sources may provide a very sensitive probe of the effect of the Lorentz invariance violation (LIV), which results in decay of high-energy gamma rays in the superluminal scenario and hence a sharp cutoff of the energy spectrum. Two highest energy sources are studied in this work. No signature of the existence of LIV is found in their energy spectra, and the lower limits on the LIV energy scale are derived. Our results show that the first-order LIV energy scale should be higher than about 10^5 times the Planck scale M_{pl} and that the second-order LIV scale is >10^{-3}M_{pl}. Both limits improve by at least one order of magnitude the previous results.

0 citations0 reviewsNo code linkedOpen access
preprint2026arXiv

Extended Very-High-Energy Gamma-Ray Emission Surrounding PSR J0622 + 3749 Observed by LHAASO-KM2A

We report the discovery of an extended very-high-energy (VHE) gamma-ray source around the location of the middle-aged (207.8 kyr) pulsar PSR J0622+3749 with the Large High Altitude Air Shower Observatory (LHAASO). The source is detected with a significance of $8.2σ$ for $E>25$~TeV assuming a Gaussian template. The best-fit location is (R.A., Dec.)$=(95^{\circ}\!.47\pm0^{\circ}\!.11,\,37^{\circ}\!.92 \pm0^{\circ}\!.09)$, and the extension is $0^{\circ}\!.40\pm0^{\circ}\!.07$. The energy spectrum can be described by a power-law spectrum with an index of ${-2.92 \pm 0.17_{\rm stat} \pm 0.02_{\rm sys} }$. No clear extended multi-wavelength counterpart of the LHAASO source has been found from the radio to sub-TeV bands. The LHAASO observations are consistent with the scenario that VHE electrons escaped from the pulsar, diffused in the interstellar medium, and scattered the interstellar radiation field. If interpreted as the pulsar halo scenario, the diffusion coefficient, inferred for electrons with median energies of $\sim160$~TeV, is consistent with those obtained from the extended halos around Geminga and Monogem and much smaller than that derived from cosmic ray secondaries. The LHAASO discovery of this source thus likely enriches the class of so-called pulsar halos and confirms that high-energy particles generally diffuse very slowly in the disturbed medium around pulsars.

0 citations0 reviewsNo code linkedOpen access
preprint2026arXiv

From Flatland to Space: Teaching Vision-Language Models to Perceive and Reason in 3D

Recent advances in LVLMs have improved vision-language understanding, but they still struggle with spatial perception, limiting their ability to reason about complex 3D scenes. Unlike previous approaches that incorporate 3D representations into models to improve spatial understanding, we aim to unlock the potential of VLMs by leveraging spatially relevant image data. To this end, we introduce a novel 2D spatial data generation and annotation pipeline built upon scene data with 3D ground-truth. This pipeline enables the creation of a diverse set of spatial tasks, ranging from basic perception tasks to more complex reasoning tasks. Leveraging this pipeline, we construct SPAR-7M, a large-scale dataset generated from thousands of scenes across multiple public datasets. In addition, we introduce SPAR-Bench, a benchmark designed to offer a more comprehensive evaluation of spatial capabilities compared to existing spatial benchmarks, supporting both single-view and multi-view inputs. Training on both SPAR-7M and large-scale 2D datasets enables our models to achieve state-of-the-art performance on 2D spatial benchmarks. Further fine-tuning on 3D task-specific datasets yields competitive results, underscoring the effectiveness of our dataset in enhancing spatial reasoning.

0 citations0 reviewsNo code linkedOpen access
preprint2026arXiv

Kagome goldene with flat bands and Dirac nodal line fermions via line-graph epitaxy

The kagome lattice has emerged as a promising platform for investigating exotic quantum phases. However, achieving a single-atomic-layer kagome lattice in elemental materials remains a significant challenge. Here, we introduce line-graph epitaxy, a novel approach that enables the atomic-scale synthesis of goldene, a monolayer of elemental gold atoms arranged in a kagome lattice. Through scanning tunneling microscopy/spectroscopy (STM/STS), and density functional theory (DFT) calculations, we demonstrate the formation of kagome goldene, featuring a flat band with a van Hove singularity approximately 1.1 eV below the Fermi level, signaling strong electron correlation effects. Notably, the flat band is disrupted at the zigzag edges of goldene nanoflakes, revealing substantial edge effects. Furthermore, our calculations show that weak interlayer interactions between goldene and the underlying Au2Ge substrate generate dual Dirac nodal lines through a proximity effect. These findings offer not only a novel strategy for constructing elemental kagome lattices, but also a generalizable framework for fabricating and controlling line-graph materials. This research advances the exploration of quantum phases driven by strong correlations and the design of materials for next-generation quantum technologies.

0 citations0 reviewsNo code linkedOpen access
preprint2026arXiv

Language as Prior, Vision as Calibration: Metric Scale Recovery for Monocular Depth Estimation

Relative-depth foundation models transfer well, yet monocular metric depth remains ill-posed due to unidentifiable global scale and heightened domain-shift sensitivity. Under a frozen-backbone calibration setting, we recover metric depth via an image-specific affine transform in inverse depth and train only lightweight calibration heads while keeping the relative-depth backbone and the CLIP text encoder fixed. Since captions provide coarse but noisy scale cues that vary with phrasing and missing objects, we use language to predict an uncertainty-aware envelope that bounds feasible calibration parameters in an unconstrained space, rather than committing to a text-only point estimate. We then use pooled multi-scale frozen visual features to select an image-specific calibration within this envelope. During training, a closed-form least-squares oracle in inverse depth provides per-image supervision for learning the envelope and the selected calibration. Experiments on NYUv2 and KITTI improve in-domain accuracy, while zero-shot transfer to SUN-RGBD and DDAD demonstrates improved robustness over strong language-only baselines.

0 citations0 reviewsNo code linkedOpen access
preprint2026arXiv

LHAASO Detection of Ultra-High-Energy Gamma-Ray Emission toward the Giant Molecular Clouds

The $γ$-ray from Giant molecular clouds (GMCs) is regarded as the most ideal tool to perform in-situ measurement of cosmic ray (CR) density and spectra in our Galaxy. We report the first detection of $γ$-ray emissions in the very-high-energy (VHE) domain from the five nearby GMCs with a stacking analysis based on a 4.5-year $γ$-ray observation with the Large High Altitude Air Shower Observatory (LHAASO) experiment. The spectral energy distributions derived from the GMCs are consistent with the expected $γ$-ray flux produced via CR interacting with the ISM in the energy interval 1 - 100 $~\rm$ TeV. In addition, we investigate the presence of the CR spectral `knee' by introducing a spectral break in the $γ$-ray data. While no significant evidence for the CR knee is found, the current KM2A measurements from GMCs strongly favor a proton CR knee located above 0.9$~\rm$ PeV, which is consistent with the latest measurement of the CR spectrum by ground-based experiments.

0 citations0 reviewsNo code linkedOpen access
preprint2026arXiv

Measurement of attenuation length of the muon content in extensive air showers from 0.3 to 30 PeV with LHAASO

The attenuation length of the muon content in extensive air showers provides important information regarding the generation and development of air showers. This information can be used not only to improve the description of such showers but also to test fundamental models of hadronic interactions. Using data from the LHAASO-KM2A experiment, the development of the muon content in high-energy air showers was studied. The attenuation length of muon content in the air showers was measured from experimental data in the energy range from 0.3 to 30 PeV using the constant intensity cut method. By comparing the attenuation length of the muon content with predictions from high-energy hadronic interaction models (QGSJET-II-04, SIBYLL 2.3d, and EPOS-LHC), it is evident that LHAASO results are significantly shorter than those predicted by the first two models (QGSJET-II-04 and SIBYLL 2.3d) but relatively close to those predicted by the third model (EPOS-LHC). Thus, the LHAASO data favor the EPOS-LHC model over the other two models. The three interaction models confirmed an increasing trend in the attenuation length as the cosmic-ray energy increases.

0 citations0 reviewsNo code linkedOpen access
preprint2026arXiv

Measurement of Very-high-energy Diffuse Gamma-ray Emissions from the Galactic Plane with LHAASO-WCDA

The diffuse Galactic gamma-ray emission is a very important tool used to study the propagation and interaction of cosmic rays in the Milky Way. In this work, we report the measurements of the diffuse emission from the Galactic plane, covering Galactic longitudes from $15^{\circ}$ to $235^{\circ}$ and latitudes from $-5^{\circ}$ to $+5^{\circ}$, in an energy range of 1 TeV to 25 TeV, with the Water Cherenkov Detector Array (WCDA) of the Large High Altitude Air Shower Observatory (LHAASO). After masking the sky regions of known sources, the diffuse emission is detected with $24.6σ$ and $9.1σ$ significance in the inner Galactic plane and outer Galactic plane, respectively. The WCDA spectra in both regions can be well described by a power-law function, with spectral indices of $-2.67\pm0.05_{\rm stat}$ in the inner region and $-2.83\pm0.19_{\rm stat}$ in the outer region, respectively. Combined with the Square Kilometer Array (KM2A) measurements at higher energies, a clear softening of the spectrum is found in the inner region, with change of spectral indices by $\sim0.5$ at a break energy around $30$ TeV. The fluxes of the diffuse emission are higher by a factor of $1.5-2.7$ than the model prediction assuming local CR spectra and the gas column density, which are consistent with those measured by the KM2A. Along Galactic longitude, the spatial distribution of the diffuse emission shows deviation from that of the gas column density. The spectral shape of the diffuse emission are possibly variation in different longitude region. The WCDA measurements bridge the gap between the low-energy measurements by space detectors and the ultra-high-energy observations by LHAASO-KM2A and other experiments. These results suggest that improved modeling of the wide-band diffuse emission is required.

0 citations0 reviewsNo code linkedOpen access
preprint2026arXiv

Radiation Resistance of Ge-doped Multi-Mode Fiber for Optical Links in Collider Experiments

The applications of optical links in collider experiments provide the advantage of high-speed data transmission with low mass fibers over distances of a few hundred meters. Ge-doped multi-mode fibers are evaluated for radiation tolerance in ionizing doses of Co-60 gamma rays. The Radiation-Induced Attenuation (RIA) varies significantly depending on doping substances and fabrication technologies. A type of telecom-grade fiber has demonstrated an RIA of 0.05 dB/m under a total ionizing dose of 300 kGy(SiO2). The dependence on dose rate is compared in the range between 5 Gy/hr and 1.4 kGy/hr, and the annealing recovery is observed after the Co-60 source is shielded. The temperature dependence is investigated across a range of -15 oC to room temperature. At cold temperatures, stagnant annealing leads to a substantially higher RIA during irradiation. The recovery of radiation-induced defects is typically within a few hours, resulting in similar RIA levels regardless of the dose rate and temperature during exposure. Ge-doped fibers of chosen fabrication methods are capable of enduring high ionizing doses for use in high-energy physics experiments.

0 citations0 reviewsNo code linkedOpen access
preprint2026arXiv

SGDrive: Scene-to-Goal Hierarchical World Cognition for Autonomous Driving

Recent end-to-end autonomous driving approaches have leveraged Vision-Language Models (VLMs) to enhance planning capabilities in complex driving scenarios. However, VLMs are inherently trained as generalist models, lacking specialized understanding of driving-specific reasoning in 3D space and time. When applied to autonomous driving, these models struggle to establish structured spatial-temporal representations that capture geometric relationships, scene context, and motion patterns critical for safe trajectory planning. To address these limitations, we propose SGDrive, a novel framework that explicitly structures the VLM's representation learning around driving-specific knowledge hierarchies. Built upon a pre-trained VLM backbone, SGDrive decomposes driving understanding into a scene-agent-goal hierarchy that mirrors human driving cognition: drivers first perceive the overall environment (scene context), then attend to safety-critical agents and their behaviors, and finally formulate short-term goals before executing actions. This hierarchical decomposition provides the structured spatial-temporal representation that generalist VLMs lack, integrating multi-level information into a compact yet comprehensive format for trajectory planning. Extensive experiments on the NAVSIM benchmark demonstrate that SGDrive achieves state-of-the-art performance among camera-only methods on both PDMS and EPDMS, validating the effectiveness of hierarchical knowledge structuring for adapting generalist VLMs to autonomous driving.

0 citations0 reviewsNo code linkedOpen access
preprint2026arXiv

Sparsity-Aware Streaming SNN Accelerator with Output-Channel Dataflow for Automatic Modulation Classification

The rapid advancement of wireless communication technologies, including 5G, emerging 6G networks, and the large-scale deployment of the Internet of Things (IoT), has intensified the need for efficient spectrum utilization. Automatic modulation classification (AMC) plays a vital role in cognitive radio systems by enabling real-time identification of modulation schemes for dynamic spectrum access and interference mitigation. While deep neural networks (DNNs) offer high classification accuracy, their computational and energy demands pose challenges for real-time edge deployment. Spiking neural networks (SNNs), with their event-driven nature, offer inherent energy efficiency, but achieving both high throughput and low power under constrained hardware resources remains challenging. This work proposes a sparsity-aware SNN streaming accelerator optimized for AMC tasks. Unlike traditional systolic arrays that exploit sparsity but suffer from low throughput, or streaming architectures that achieve high throughput but cannot fully utilize input and weight sparsity, our design integrates both advantages. By leveraging the fixed nature of kernels during inference, we apply the gated one-to-all product (GOAP) algorithm to compute only on non-zero input-weight intersections. Extra or empty iterations are precomputed and embedded into the inference dataflow, eliminating dynamic data fetches and enabling fully pipelined, control-free inter-layer execution. Implemented on an FPGA, our sparsity-aware output-channel dataflow streaming (SAOCDS) accelerator achieves 23.5 MS/s (approximately double the baseline throughput) on the RadioML 2016 dataset, while reducing dynamic power and maintaining comparable classification accuracy. These results demonstrate strong potential for real-time, low-power deployment in edge cognitive radio systems.

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preprint2026arXiv

Transient Large-Scale Anisotropy in TeV Cosmic Rays due to an Interplanetary Coronal Mass Ejection

Large- or medium-scale cosmic ray anisotropy at TeV energies has not previously been confirmed to vary with time. Transient anisotropy changes have been observed below 150 GeV, especially near the passage of an interplanetary shock and coronal mass ejection containing a magnetic flux rope ejected by a solar storm, which can trigger a geomagnetic storm with practical consequences. In such events, cosmic rays provide remote sensing of the magnetic field properties. Here we report the observation of transient large-scale anisotropy in TeV cosmic ray ions using data from the Large High Altitude Air Shower Observatory (LHAASO). We analyze hourly skymaps of the transient cosmic ray intensity excess or deficit, the gradient of which indicates the direction and magnitude of transient large-scale anisotropy across the field of view. We observe enhanced anisotropy above typical hourly fluctuations with $>$5$σ$ significance during some hours of November 4, 2021, in separate data sets for four primary cosmic ray energy ranges of median energy from $E$=0.7 to 3.1 TeV. The gradient varies with energy as $E^γ$, where $γ\approx-0.5$. At a median energy $\leq$1.0 TeV, this gradient corresponds to a dipole anisotropy of at least 1\%, or possibly a weaker anisotropy of higher order. This new type of observation opens the opportunity to study interplanetary magnetic structures using air shower arrays around the world, complementing existing in situ and remote measurements of plasma properties.

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preprint2025arXiv

Do LLMs Truly Understand When a Precedent Is Overruled?

Large language models (LLMs) with extended context windows show promise for complex legal reasoning tasks, yet their ability to understand long legal documents remains insufficiently evaluated. Developing long-context benchmarks that capture realistic, high-stakes tasks remains a significant challenge in the field, as most existing evaluations rely on simplified synthetic tasks that fail to represent the complexity of real-world document understanding. Overruling relationships are foundational to common-law doctrine and commonly found in judicial opinions. They provide a focused and important testbed for long-document legal understanding that closely resembles what legal professionals actually do. We present an assessment of state-of-the-art LLMs on identifying overruling relationships from U.S. Supreme Court cases using a dataset of 236 case pairs. Our evaluation reveals three critical limitations: (1) era sensitivity -- the models show degraded performance on historical cases compared to modern ones, revealing fundamental temporal bias in their training; (2) shallow reasoning -- models rely on shallow logical heuristics rather than deep legal comprehension; and (3) context-dependent reasoning failures -- models produce temporally impossible relationships in complex open-ended tasks despite maintaining basic temporal awareness in simple contexts. Our work contributes a benchmark that addresses the critical gap in realistic long-context evaluation, providing an environment that mirrors the complexity and stakes of actual legal reasoning tasks.

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