arXiv subjects

Yang Su

Publications and source records attributed to Yang Su.

At least 37 records · Page 2Linked to original sources

arXiv2026

Physics Informed Bayesian Machine Learning of Sparse and Imperfect Nuclear Data

The prevailing data-driven machine learning has been plagued by the absence of physics knowledge and the scarcity of data. We implement the physics-model informed prior into Bayesian machine learning to evaluate the energy dependence of independent fission product yields, which are crucial for advanced nuclear energy applications but only sparse and imperfect experimental data are available. The informative prior is the posterior after learning the generated data from fission models. Furthermore, cumulative fission yields are included as a physical constraint via a conversion matrix to provide augmented energy dependence. Our work demonstrated a truly Bayesian machine learning by incorporating comprehensive physics knowledges as a powerful tool to exploit the sparse but expensive nuclear data.

nucl-th↗

arXiv2026

How is Cold Gas Loaded into Galactic Nuclear Outflows?

The origin of the multiphase gas within the Fermi/eROSITA bubbles is crucial for understanding Galactic Center (GC) feedback. We use HI4PI data to investigate the kinematics and physical properties of high-velocity clouds (HVCs) toward the GC. Our results reveal that the HVCs exhibit a distinct asymmetric distribution, closely associated with the bar-driven tilted dust lanes and the distorted overshooting streams. We propose that powerful nuclear outflows interact with these gas-rich, off-plane structures, striping and entraining cold gas from the outer Galactic regions (R_GC~0.5--1.7 kpc) rather than solely from the region of the central molecular zone (CMZ; R_GC<0.3 kpc). In this scenario, as the Galactic bar drives gas inflows along the dust lanes, nuclear outflows simultaneously break through the CMZ, sweeping up and ablating cold gas from the boundary layer of these pre-existing structures. This process naturally accounts for the observed high turbulence, complex spectral signatures, and anomalous spatial-kinematic gas patterns, as well as multiwavelength asymmetries of the bubbles. The HVCs are accelerated to about 230--340 km/s over a dynamical time of ~3--6 Myr. When the multiphase, inhomogeneous composition of the gas is included, the estimated gas outflow rate reaches ~1 Msun/yr. This value is comparable to the bar-driven inflow rate, indicating a tightly coupled gas cycle in the inner Galaxy. Our research highlights the critical role of bar-driven gas dynamics and nuclear feedback in the secular evolution of the Milky Way, offering a valuable paradigm for investigating gas cycles in external galaxies.

astro-ph.GA↗

arXiv2026

MAJORS II: HCO+& HCN Abundances in W40

We present observations of HCN and HCO$^+$ J = $3 - 2$ in the central $424'' \times 424''$ region of the W40 massive star forming region. The observations were taken as part of a pilot project for the MAJORS large program at the JCMT telescope. By incorporating prior knowledge of N(H$_2$) and $T_K$, assuming a constant density, and using the RADEX radiative transfer code we found that the HCN and HCO$^+$ abundances range from $X$(HCN) = $0.4-7.0 \times 10^{-8}$ and $X$(HCO$^+$) = $0.4-7.3 \times 10^{-9}$. Additional modelling using the NAUTILUS chemical evolution code, that takes H$_2$ density variations into account, however, suggests the HCN and HCO$^+$ abundances may be fairly constant. Careful modelling of three different positions finds $X$(HCN) = $1.3-1.7 \times 10^{-8}$, $X$(HCO$^+$) = $1.3-3.1 \times 10^{-9}$. Cross-comparison of the two models also provides a crude estimate of the gas density producing the HCN and HCO$^+$ emission, with H$_2$ densities in the range $5 \times 10^4 - 5 \times 10^5$ cm$^{-3}$, suggesting that the HCN and HCO$^+$ emission does indeed arise from dense gas. High UV intensity (e.g. $G_o >$ a few thousand) has no effect on the abundances in regions where the visual extinction is large enough to effectively shield the gas from the UV field. In regions where $A_V < 6$, however, the abundance of both species is lowered due to destructive reactions with species that are directly affected by the radiation field.

astro-ph.GA↗

arXiv2026

DeepPlanning: Benchmarking Long-Horizon Agentic Planning with Verifiable Constraints

While agent evaluation has shifted toward long-horizon tasks, most benchmarks still emphasize local, step-level reasoning rather than the global constrained optimization (e.g., time and financial budgets) that demands genuine planning ability. Meanwhile, existing LLM planning benchmarks underrepresent the active information gathering and fine-grained local constraints typical of real-world settings. To address this, we introduce DeepPlanning, a challenging benchmark for practical long-horizon agent planning. It features multi-day travel planning and multi-product shopping tasks that require proactive information acquisition, local constrained reasoning, and global constrained optimization. Evaluations on DeepPlanning show that even frontier agentic LLMs struggle with these problems, highlighting the importance of reliable explicit reasoning patterns and parallel tool use for achieving better effectiveness-efficiency trade-offs. Error analysis further points to promising directions for improving agentic LLMs over long planning horizons. We open-source the code and data to support future research.

cs.AI↗

arXiv2026

ToolRM: Towards Agentic Tool-Use Reward Modeling

Reward models (RMs) play a critical role in aligning large language models (LLMs) with human preferences. Yet in the domain of tool learning, the lack of RMs specifically designed for function-calling tasks has limited progress toward more capable agentic AI. We introduce ToolRM, a family of lightweight reward models tailored for general tool-use scenarios. To build these models, we propose a novel pipeline that constructs high-quality pairwise preference data using rule-based scoring and multidimensional sampling. This yields ToolPref-Pairwise-30K, a diverse, balanced, and challenging preference dataset that supports both generative and discriminative reward modeling. We also introduce TRBench$_{BFCL}$, a benchmark built on the agent evaluation suite BFCL to evaluate RMs on tool calling tasks. Trained on our constructed data, models from the Qwen3-4B/8B series achieve up to 17.94% higher accuracy, substantially outperforming frontier LLMs and RMs in pairwise reward judgments. Beyond training objectives, generative ToolRM generalizes to broader critique tasks, including Best-of-N sampling and self-correction. Experiments on ACEBench highlight its effectiveness and efficiency, enabling inference-time scaling while reducing output token usage by over 66%. Its support for downstream RL training further validates its practical utility. We release data to facilitate future research.

cs.AI↗

arXiv2025

Solar jet-induced perturbation propagating through coronal loops and in-loop electron beam transport indicated by type II and type N radio bursts

Solar type II radio bursts are commonly attributed to coronal shocks driven by coronal mass ejections (CMEs). However, some metric type II bursts have occasionally been reported to occur in the absence of a CME and to be associated with weak solar activities. This study aims to identify the driver of the coronal shock in this kind of type II event. We investigate a high-frequency metric type II burst with clear band splitting, observed simultaneously by the Chashan Broadband Solar radio spectrograph and the Nançay Radioheliograph. It is associated with a C3.1-class flare and a small-scale jet, but without a detectable CME in the coronagraphs. The type II burst is preceded by multiple type III bursts, one of which exhibits characteristics of a type N burst. The type II burst source is associated with the jet-induced perturbation front propagating through nearby closed loops at a speed of $\sim$880 km s$^{-1}$, rather than the much slower jet front. This suggests that the disturbance initiated by the jet can convert to a shock wave within low Alfvénic coronal loops, providing the necessary conditions for electron acceleration and subsequent radio emission. Our findings offer new insights into the formation mechanism of high-frequency type II bursts associated with weak flares and jets.

astro-ph.SR↗

arXiv2025

The Milky Way Imaging Scroll Painting Survey: Data Release 1

We present the first data release (DR1) of the Milky Way Imaging Scroll Painting (MWISP) survey, a mapping in the J=(1-0) transition lines of 12CO, 13CO, and C18O toward the northern Galactic plane during 2011-2022. The MWISP survey was conducted using the PMO 13.7 m telescope at a spatial resolution of approximately 50" and a velocity resolution of 0.16 km/s at 115 GHz. DR1 fully covered 2310 square degrees within the Galactic longitude (l) and latitude (b) range of 9.75 deg =< l =< 229.75 deg and |b| =< 5.25 deg. The surveyed area was divided into cell units of 30'x30' for practical purposes and On-The-Fly (OTF) mapping was performed toward each target cell unit. The data were regridded into a regular 3D datacube in l-b-V_LSR with a pixel size of 30" in l-b axes and 0.16 km/s in theV_LSR axis. The median rms noise is 0.47 K, 0.25 K, and 0.25 K for 12CO, 13CO, and C18O, respectively. The equivalent 3 sigma sensitivity in 12CO luminosity is approximately 0.23 K km/s, making MWISP the most sensitive survey of its kind. In this paper, we describe the survey data, including the calibration, data cleaning, data mosaic processes, and the data products. The final mosaicked data cubes contain about 3.33x10^7 spectra (pixels) for each CO isotopologue line. Color composite images, made from the intensities of the isotopologue lines, and some concise descriptions are provided. We constructed a molecular cloud catalog based on the mosaicked 12CO data cube using the clustering algorithm DBSCAN, detecting 103,517 molecular clouds, 10,790 of which exhibit 13CO emission and 304 of which show C18O emission. Based on the histogram of voxel brightness temperature, we estimated a total 12CO flux of 7.69+/-0.38x10^7 K km/s arcmin^2, 82% of which is captured by the DBSCAN algorithm. The data, together with the cloud sample, provide unique information on molecular gas in the northern Milky Way.

astro-ph.GA↗

arXiv2025

Mastering Diverse, Unknown, and Cluttered Tracks for Robust Vision-Based Drone Racing

Most reinforcement learning(RL)-based methods for drone racing target fixed, obstacle-free tracks, leaving the generalization to unknown, cluttered environments largely unaddressed. This challenge stems from the need to balance racing speed and collision avoidance, limited feasible space causing policy exploration trapped in local optima during training, and perceptual ambiguity between gates and obstacles in depth maps-especially when gate positions are only coarsely specified. To overcome these issues, we propose a two-phase learning framework: an initial soft-collision training phase that preserves policy exploration for high-speed flight, followed by a hard-collision refinement phase that enforces robust obstacle avoidance. An adaptive, noise-augmented curriculum with an asymmetric actor-critic architecture gradually shifts the policy's reliance from privileged gate-state information to depth-based visual input. We further impose Lipschitz constraints and integrate a track-primitive generator to enhance motion stability and cross-environment generalization. We evaluate our framework through extensive simulation and ablation studies, and validate it in real-world experiments on a computationally constrained quadrotor. The system achieves agile flight while remaining robust to gate-position errors, developing a generalizable drone racing framework with the capability to operate in diverse, partially unknown and cluttered environments. https://yufengsjtu.github.io/MasterRacing.github.io/

cs.RO↗

arXiv2025

Microclimatic variation in tropical canopies: A glimpse into the processes of community assembly in epiphytic bryophyte communities

Epiphytic communities offer an original framework to disentangle the contributions of environmental filters, biotic interactions and dispersal limitations to community structure at fine spatial scales. We determine here whether variations in light, microclimatic conditions and host tree size affect the variation in species composition and phylogenetic structure of epiphytic bryophyte communities, and hence, assess the contribution of environmental filtering, phylogenetic constraints and competition to community assembly.A canopy crane giving access to 1.1 ha of tropical rainforest in Yunnan (China) was employed to record hourly light and microclimatic conditions from 54 dataloggers and epiphytic bryophyte communities from 408 plots. Generalized Dissimilarity Modelling was implemented to analyse the relationship between taxonomic and phylogenetic turnover among epiphytic communities, host-tree characteristics and microclimatic variation.Within-tree vertical turnover of bryophyte communities was significantly about 30% higher than horizontal turnover among-trees. Thus, the sharp vertical variations in microclimatic conditions from tree base to canopy are more important than differences in age, reflecting the likelihood of colonization, area, and habitat conditions between young and old trees, in shaping the composition of epiphytic bryophyte communities.

q-bio.PE↗

arXiv2025

Two-Stage Nature of a Solar Flare with Parallel and Semi-Circular Ribbons

Flare ribbons with parallel and circular morphologies are typically associated with different magnetic reconnection models, and the simultaneous observation of both types in a single event remains rare. Using multi-wavelength observations from a tandem of instruments, we present an M8.2-class flare that occurred on 2023 September 20, which produced quasi-parallel and semi-circular ribbons. The complex evolution of the flare includes two distinct brightening episodes in the quasi-parallel ribbons, corresponding to the two major peaks in the hard X-ray (HXR) light curve. In contrast, the brightening of semi-circular ribbons temporally coincides with the local minimum between the two peaks. Using potential field extrapolation, we reconstruct an incomplete dome-like magnetic structure with a negative polarity embedded within the northwestern part of the semi-circular positive polarity. Consequently, the magnetic configuration comprises two sets of field lines with distinct magnetic connectivities. We suggest that the standard flare reconnection accounts for the two-stage brightening of quasi-parallel ribbons associated with the two HXR peaks. Between the two stages, this process is constrained by the interaction of eruptive structures with the dome. The interaction drives the quasi-separatrix layer reconnection, leading to the brightening of semi-circular ribbons. It also suppresses the standard flare reconnection, resulting in a delayed second HXR peak.

astro-ph.SR↗

arXiv2025

Self-covering, finiteness, commutativity, and fibering over tori

A topological space is called self-covering if it is a nontrivial cover of itself. We prove that, under mild assumptions, a closed self-covering manifold with an abelian fundamental group fibers over a torus in various senses. As a corollary, if its dimension is above $5$ and its fundamental group is free abelian, then it is a fiber bundle over a circle. We also construct non-fibering examples when these assumptions are not fulfilled. In particular, one class of examples illustrates that the structure of self-covering manifolds is more complicated when the fundamental groups are nonabelian, and the corresponding fibering problem encounters significant difficulties.

math.GT↗

arXiv2025

RMTBench: Benchmarking LLMs Through Multi-Turn User-Centric Role-Playing

Recent advancements in Large Language Models (LLMs) have shown outstanding potential for role-playing applications. Evaluating these capabilities is becoming crucial yet remains challenging. Existing benchmarks mostly adopt a \textbf{character-centric} approach, simplify user-character interactions to isolated Q&A tasks, and fail to reflect real-world applications. To address this limitation, we introduce RMTBench, a comprehensive \textbf{user-centric} bilingual role-playing benchmark featuring 80 diverse characters and over 8,000 dialogue rounds. RMTBench includes custom characters with detailed backgrounds and abstract characters defined by simple traits, enabling evaluation across various user scenarios. Our benchmark constructs dialogues based on explicit user motivations rather than character descriptions, ensuring alignment with practical user applications. Furthermore, we construct an authentic multi-turn dialogue simulation mechanism. With carefully selected evaluation dimensions and LLM-based scoring, this mechanism captures the complex intention of conversations between the user and the character. By shifting focus from character background to user intention fulfillment, RMTBench bridges the gap between academic evaluation and practical deployment requirements, offering a more effective framework for assessing role-playing capabilities in LLMs. All code and datasets will be released soon. We release the datasets at https://huggingface.co/datasets/xiangh/RMTBENCH.

cs.CL↗

arXiv2025

Dust extinction map of the Galactic plane based on the UKIDSS survey data

Dust plays a critical role in the study of the interstellar medium (ISM). Extinction maps derived from optical surveys often fail to capture regions with high column density due to the limited photometric depth in optical wavelengths. To address these limitations, we developed the XPNICER method based on near-infrared (NIR) photometric survey data. This method combines the previously established PNICER and Xpercentile techniques, enabling effective mitigation of foreground contamination and improved handling of complex dust structures in the Galactic plane, which thus can provide more accurate extinction estimates, particularly in highly obscured regions. By applying XPNICER to the Galactic Plane Survey from the UKIRT Infrared Deep Sky Survey, we have generated a series of two-dimensional (2D) dust extinction maps that span roughly 1800 deg2 of the Galactic plane (0< l < 110deg and 140< l < 232deg, |b| < 5deg). These maps, with spatial resolutions between 30arcsec and 300arcsec, can trace extinction up to Av ~ 30-40 mag. This new approach offers higher spatial resolution and better detection of high-extinction regions compared to previous large-scale dust-based maps of the Galactic plane, providing an independent and complementary measure of dust column densities.

astro-ph.GA↗

arXiv2025

Open TeleDex: A Hardware-Agnostic Teleoperation System for Imitation Learning based Dexterous Manipulation

Accurate and high-fidelity demonstration data acquisition is a critical bottleneck for deploying robot Imitation Learning (IL) systems, particularly when dealing with heterogeneous robotic platforms. Existing teleoperation systems often fail to guarantee high-precision data collection across diverse types of teleoperation devices. To address this, we developed Open TeleDex, a unified teleoperation framework engineered for demonstration data collection. Open TeleDex specifically tackles the TripleAny challenge, seamlessly supporting any robotic arm, any dexterous hand, and any external input device. Furthermore, we propose a novel hand pose retargeting algorithm that significantly boosts the interoperability of Open TeleDex, enabling robust and accurate compatibility with an even wider spectrum of heterogeneous master and slave equipment. Open TeleDex establishes a foundational, high-quality, and publicly available platform for accelerating both academic research and industry development in complex robotic manipulation and IL.

cs.RO↗

arXiv2025

Investigations of MWISP Clumps: 13CO Clump Source Catalog and Physical Properties

We present the first comprehensive catalogs of $^{13}$CO clumps from the Milky Way Imaging Scroll Painting (MWISP) project. By developing an equivalent global detection scheme integrated with the FacetClumps algorithm, we successfully extract 71,661 molecular clumps across a high-resolution $^{13}$CO data cube spanning 2310 deg$^2$ from the MWISP Phase I survey. To determine accurate distances, we design an automatic hierarchical distance decision method using signal regions as fundamental objects, effectively resolving the kinematic distance ambiguity problem and obtaining reliable measurements for 97.94% of the sample. Statistical analysis reveals that 65.3% of clumps are gravitationally bound, accounting for approximately 96.3% of the statistical total mass. Scaling relation analysis across multiple surveys reveals universal power-law behaviors in clump populations. Maser-associated clumps exhibit modified parameter distributions and scaling relations, revealing how active star formation alters clump dynamics and structure. These extensive catalogs establish a foundation for investigating molecular clump properties, star formation processes, and Galactic evolution.

astro-ph.GA↗

arXiv2025

Communication-Aware Knowledge Distillation for Federated LLM Fine-Tuning over Wireless Networks

Federated learning (FL) for large language models (LLMs) offers a privacy-preserving scheme, enabling clients to collaboratively fine-tune locally deployed LLMs or smaller language models (SLMs) without exchanging raw data. While parameter-sharing methods in traditional FL models solves number of technical challenges, they still incur high communication overhead and struggle with adapting to heterogeneous model architectures. Federated distillation, a framework for mutual knowledge transfer via shared logits, typically offers lower communication overhead than parameter-sharing methods. However, transmitting logits from LLMs remains challenging for bandwidth-limited clients due to their high dimensionality. In this work, we focus on a federated LLM distillation with efficient communication overhead. To achieve this, we first propose an adaptive Top-k logit selection mechanism, dynamically sparsifying logits according to real-time communication conditions. Then to tackle the dimensional inconsistency introduced by the adaptive sparsification, we design an adaptive logits aggregation scheme, effectively alleviating the artificial and uninformative inputs introduced by conventional zero-padding methods. Finally, to enhance the distillation effect, we incorporate LoRA-adapted hidden-layer projection from LLM into the distillation loss, reducing the communication overhead further while providing richer representation. Experimental results demonstrate that our scheme achieves superior performance compared to baseline methods while effectively reducing communication overhead by approximately 50%.

cs.LG↗

arXiv2025

Particle Acceleration and Transport in the Large-scale Current Sheet under an Erupting Magnetic Flux Rope

We investigate the acceleration and transport of electrons in the highly fine-structured current sheet that develops during magnetic flux rope (MFR) eruptions. Our work combines ultra-resolved MHD simulations of MFR eruption, with test-particle studies performed using the guiding center approximation. Our grid-adaptive, fully three-dimensional, high-resolution magnetohydrodynamic simulations model MFR eruptions that form complex current sheet topologies, serving as background electromagnetic fields for particle acceleration. Within the current sheet, tearing-mode instabilities give rise to mini flux ropes. Electrons become temporarily trapped within these elongated structures, undergoing acceleration and transport processes that significantly differ from those observed in two-dimensional or two-and-a-half-dimensional simulations. Our findings reveal that these fine-scale structures act as efficient particle accelerators, surpassing the acceleration efficiency of single X-line reconnection events, and are capable of energizing electrons to energies exceeding 100 keV. High-energy electrons accelerated in different mini flux ropes follow distinct trajectories due to spatially varying magnetic field connectivity, ultimately precipitating onto opposite sides of flare ribbons. Remarkably, double electron sources at the flare ribbons originate from different small flux rope acceleration regions, rather than from the same reconnecting field line as previously suggested. Distinct small flux ropes possess opposite magnetic helicity to accelerate electrons to source regions with different magnetic polarities, establishing a novel conjugate double source configuration. Furthermore, electrons escaping from the lower regions exhibit a broken power-law energy spectrum.

astro-ph.SR↗

arXiv2025

Probing Solar Polar Regions

The magnetic fields and dynamical processes in the solar polar regions play a crucial role in the solar magnetic cycle and in supplying mass and energy to the fast solar wind, ultimately being vital in controlling solar activities and driving space weather. Despite numerous efforts to explore these regions, to date no imaging observations of the Sun's poles have been achieved from vantage points out of the ecliptic plane, leaving their behavior and evolution poorly understood. This observation gap has left three top-level scientific questions unanswered, 1) How does the solar dynamo work and drive the solar magnetic cycle? 2) What drives the fast solar wind? 3) How do space weather processes globally originate from the Sun and propagate throughout the solar system? The Solar Polar-orbit Observatory (SPO) mission, a solar polar exploration spacecraft, is proposed to address these three unanswered scientific questions by imaging the Sun's poles from high heliolatitudes. In order to achieve its scientific goals, SPO will carry six remote-sensing and four in-situ instruments to measure the vector magnetic fields and Doppler velocity fields in the photosphere, to observed the Sun in the extreme ultraviolet, X-ray, and radio wavelengths, to image the corona and the heliosphere up to 45 $R_\odot$, and to perform in-situ detection of magnetic fields, and low- and high-energy particles in the solar wind.

astro-ph.SR↗