arXiv subjects

Haifeng Yang

Publications and source records attributed to Haifeng Yang.

At least 19 recordsLinked to original sources

arXiv2026

Azimuthal Dust Polarization from Aerodynamically Aligned Grains as Evidence for the Streaming Instability in Protoplanetary Disks

(Sub)millimeter dust polarization in protoplanetary disks has revealed the presence of large (~ 100 um) dust grains that are aligned along their long axis following the azimuthal direction of the disk. The novel badminton birdie-like aerodynamic alignment predicts large grains to align with their long axes following the direction of gas flow experienced by the dust, denoted as the A-field. With 3D streaming instability (SI) simulations, we find that the A-field is predominantly in the radial direction in regions of low dust-to-gas ratio, but in the azimuthal direction in regions of high dust-to-gas ratio. Through polarized radiation transfer, we find that the resulting polarization angle indeed follows the disk azimuthal direction in the high dust density regions. Therefore, ongoing SI is an attractive candidate for producing the azimuthal dust polarization pattern as observed in an increasing number of disks.

astro-ph.EP↗

arXiv2026

Capture and Stability of Resonant Planet Pairs in Turbulent Disk

We present a theoretical framework for the resonance capture and stability of two-planet systems in turbulent disks. By incorporating stochastic forcing (parameterized by $\kappa$) alongside laminar angular momentum and eccentricity damping timescales ($\tau_{\rm m}, \tau_{e}$), we derive an analytical criterion for the general $j:j-1$ mean motion resonances, and validate it through N-body simulations. The outcome is mapped in $\kappa$-$\tau_{\rm m}/\tau_{e}$ parameter space, revealing two distinct regimes: resonance trapping and turbulence-induced disruption -- which occurs either directly cross or via temporary capture followed by escape through turbulent diffusion. Crucially, our analysis identifies turbulence as a universal destabilizer. It amplifies the intrinsic overstability mechanism: In laminar disks, escape requires $\tau_{\rm m}/\tau_{e}$ to drop below a critical limit due to excessive eccentricity excitation. We demonstrate that turbulent diffusion lowers this limit, demanding stronger damping (larger $\tau_{\rm m}/\tau_{e}$) for stability. Thus, greater turbulence promotes escape, and sufficiently strong diffusion precludes resonance retention irrespective of eccentricity damping.

astro-ph.EP↗

arXiv2026

Effects of Stellar X-ray Photoevaporation on Planetesimal Formation via the Streaming Instability

The formation of planetesimals via the streaming instability (SI) is a crucial step in planet formation, yet its triggering conditions and efficiency are highly sensitive to both disk properties and specific evolutionary processes. We aim to study the planetesimal formation via the SI, driven by the stellar X-ray photoevaporation during the late stages of disk dispersal, and quantify its dependence on key disk and stellar parameters. We use the DustPy code to simulate the dust dynamics including coagulation, fragmentation, and radial drift in a viscously accreting disk undergoing stellar X-ray photoevaporation. Stellar X-rays drive the disk dispersal, opening a cavity at a few au orbital distance and inducing the formation of an associated local pressure maximum. This pressure maximum acts as a trap for radially drifting dust, therefore enhancing the dust density to the critical level required to initiate the streaming instability and the subsequent collapse into planetesimals. The fiducial model produces 31.4 M_\oplus of planetesimals with an initial dust to final planetesimal conversion efficiency of 20.4%. This pathway is most efficient in larger disks with higher metallicities, lower viscosities, higher dust fragmentation threshold velocities, and/or around stars with higher X-ray luminosities. This work demonstrates that stellar X-ray photoevaporation is a robust and feasible mechanism for triggering planetesimal formation via the SI during the final clearing phase of protoplanetary disk evolution.

astro-ph.EP↗

arXiv2025

Multi-band ALMA Polarization Observations of BHB07-11 Reveal Aligned Dust Grains in Complex Spiral Arm Structures

Polarization-mode observations from the Atacama Large Millimeter/submillimeter Array (ALMA) are powerful tools for studying the dust grain populations in circumstellar disks. Many sources exhibit polarization signatures consistent with aligned dust grains, yet the physical origin of this alignment remains uncertain. One such source is BHB07-11, a Class I protobinary object in the Pipe Nebula with complex spiral arm structures in its circumbinary disk. While magnetic fields are often invoked to explain grain alignment in the interstellar medium, the contrasting conditions in circumstellar disk environments demand further investigation into grain alignment mechanisms. To determine BHB07-11's dominant polarization mechanism, we leverage ALMA polarization-mode dust continuum observations in Bands 3 ($\lambda$=3.1 mm), 6 ($\lambda$=1.3 mm), and 7 ($\lambda$=0.87 mm), in combination with high-resolution dust continuum and spectral line observations in Band 6. Observed polarization vectors in each band are consistent with emission from aligned grains and follow the structure of the spiral arms as shown in the high-resolution observations. Given the relationship between the observed polarization vector orientation and the spiral arms, we find that the polarization morphology is most consistent with grains aligned through a relative velocity flow between gas and dust in the spiral arms, as envisioned in the recently developed badminton birdie-like alignment mechanism, rather than alignment with a magnetic field or other known alignment mechanisms.

astro-ph.SR↗

arXiv2025

Kratos-polrad: Novel GPU system for Monte-Carlo simulations with consistent polarization calculations

Polarized radiation serves as a vital diagnostic tool in astrophysics, providing unique insights into magnetic field geometries, scattering processes, and three-dimensional structures in diverse astrophysical scenarios. To address these applications, we present Kratos-polrad, a novel GPU-accelerated Monte Carlo Radiative Transfer code built upon the heterogeneous computing framework of Kratos, designed for self-consistent and efficient polarization calculations. It utlizes comprehensive treatment of Stokes parameters throughout photon propagation, featuring transforms the grain-lab frame transforms using quaternion algebra and consistent non-linear polarization extinction in cells, which are useful in modeling radiative transfer processes with scatterings by aligned dust grains. The code implements two-step polarimetry imaging that decouples Monte Carlo sampling of scattering physics from imaging geometry, enabling efficient synthesis maximizing the utilization of photon packets. Extensive validation against analytical solutions and established codes demonstrates accurate treatment of diverse polarization phenomena, including self-scattering polarization, dichroic extinction in aligned dust grains, and complex polarization patterns in twisted magnetic field configurations. By leveraging massive GPU parallelism, optimized memory access patterns, and analytical approaches for optically thick cells, Kratos-polrad achieves performance improvements of $\sim 10^{2}$ times compared to CPU-based methods, enabling previously prohibitive studies in polarimetric astrophysics.

astro-ph.IM↗

arXiv2025

Adsorption of volatiles on dust grains in protoplanetary disks

The adsorption of volatile molecules onto dust grain surfaces fundamentally influences dust-related processes, including condensation of gas-phase molecules, dust coagulation, and planet formation in protoplanetary disks. Using advanced ab-initio density functional theory with r$^2$SCAN+rVV10 van der Waals functionals, we calculate adsorption energies of H$_2$, H$_2$O, and CO on carbonaceous (graphene, amorphous carbon) and silicate (MgSiO$_3$) surfaces. Results reveal fundamentally different adsorption mechanisms: weak physisorption on carbonaceous surfaces ($|\Delta\epsilon_{\rm ad}|\sim 0.1-0.2~{\rm eV}$) versus strong chemisorption on silicates ($|\Delta\epsilon_{\rm ad}|\sim 0.5-1.5~{\rm eV}$) via coordination bonds. Kinetic Monte Carlo simulations incorporating these energies demonstrate divergent surface evolution: carbonaceous grains exhibit distinct condensation radius compared to silicates, while the cocrystal of H$_2$O and CO significantly increases the desorption temperature of CO. The actual radii of gas-phase molecule depletion could thus be a comprehensive result of temperatures, chemical compositions, and even evolution tracks. Meanwhile, silicates maintain chemisorbed molecular coatings throughout most disk regions. Such dichotomy in surface coverage could also provide a natural mechanism for carbon depletion in inner planetary systems.

astro-ph.EP↗

arXiv2025

Sky Background Building of Multi-objective Fiber spectra Based on Mutual Information Network

Sky background subtraction is a critical step in Multi-objective Fiber spectra process. However, current subtraction relies mainly on sky fiber spectra to build Super Sky. These average spectra are lacking in the modeling of the environment surrounding the objects. To address this issue, a sky background estimation model: Sky background building based on Mutual Information (SMI) is proposed. SMI based on mutual information and incremental training approach. It utilizes spectra from all fibers in the plate to estimate the sky background. SMI contains two main networks, the first network applies a wavelength calibration module to extract sky features from spectra, and can effectively solve the feature shift problem according to the corresponding emission position. The second network employs an incremental training approach to maximize mutual information between representations of different spectra to capturing the common component. Then, it minimizes the mutual information between adjoining spectra representations to obtain individual components. This network yields an individual sky background at each location of the object. To verify the effectiveness of the method in this paper, we conducted experiments on the spectra of LAMOST. Results show that SMI can obtain a better object sky background during the observation, especially in the blue end.

cs.CV↗

arXiv2025

Structure-Aware Temporal Modeling for Chronic Disease Progression Prediction

This study addresses the challenges of symptom evolution complexity and insufficient temporal dependency modeling in Parkinson's disease progression prediction. It proposes a unified prediction framework that integrates structural perception and temporal modeling. The method leverages graph neural networks to model the structural relationships among multimodal clinical symptoms and introduces graph-based representations to capture semantic dependencies between symptoms. It also incorporates a Transformer architecture to model dynamic temporal features during disease progression. To fuse structural and temporal information, a structure-aware gating mechanism is designed to dynamically adjust the fusion weights between structural encodings and temporal features, enhancing the model's ability to identify key progression stages. To improve classification accuracy and stability, the framework includes a multi-component modeling pipeline, consisting of a graph construction module, a temporal encoding module, and a prediction output layer. The model is evaluated on real-world longitudinal Parkinson's disease data. The experiments involve comparisons with mainstream models, sensitivity analysis of hyperparameters, and graph connection density control. Results show that the proposed method outperforms existing approaches in AUC, RMSE, and IPW-F1 metrics. It effectively distinguishes progression stages and improves the model's ability to capture personalized symptom trajectories. The overall framework demonstrates strong generalization and structural scalability, providing reliable support for intelligent modeling of chronic progressive diseases such as Parkinson's disease.

cs.LG↗

arXiv2025

Detailed radial scale height profile of dust grains as probed by dust self-scattering in HL Tau

The vertical settling of dust grains in a circumstellar disk, characterized by their scale height, is a pivotal process in the formation of planets. This study offers in-depth analysis and modeling of the radial scale height profile of dust grains in the HL Tau system, leveraging high-resolution polarization observations. We resolve the inner disk's polarization, revealing a significant near-far side asymmetry, with the near side being markedly brighter than the far side in polarized intensity. This asymmetry is attributed to a geometrically thick inner dust disk, suggesting a large aspect ratio of $H/R \ge 0.15$. The first ring at 20 au exhibits an azimuthal contrast, with polarization enhanced along the minor axis, indicating a moderately thick dust ring with $H/R \approx 0.1$. The absence of the near-far side asymmetry at larger scales implies a thin dust layer, with $H/R < 0.05$. Taken together, these findings depict a disk with a turbulent inner region and a settled outer disk, requiring a variable turbulence model with $\alpha$ increasing from $10^{-5}$ at 100 au to $10^{-2.5}$ at 20 au. This research sheds light on dust settling and turbulence levels within protoplanetary disks, providing valuable insights into the mechanisms of planet formation.

astro-ph.EP↗

arXiv2025

Clinical NLP with Attention-Based Deep Learning for Multi-Disease Prediction

This paper addresses the challenges posed by the unstructured nature and high-dimensional semantic complexity of electronic health record texts. A deep learning method based on attention mechanisms is proposed to achieve unified modeling for information extraction and multi-label disease prediction. The study is conducted on the MIMIC-IV dataset. A Transformer-based architecture is used to perform representation learning over clinical text. Multi-layer self-attention mechanisms are employed to capture key medical entities and their contextual relationships. A Sigmoid-based multi-label classifier is then applied to predict multiple disease labels. The model incorporates a context-aware semantic alignment mechanism, enhancing its representational capacity in typical medical scenarios such as label co-occurrence and sparse information. To comprehensively evaluate model performance, a series of experiments were conducted, including baseline comparisons, hyperparameter sensitivity analysis, data perturbation studies, and noise injection tests. Results demonstrate that the proposed method consistently outperforms representative existing approaches across multiple performance metrics. The model maintains strong generalization under varying data scales, interference levels, and model depth configurations. The framework developed in this study offers an efficient algorithmic foundation for processing real-world clinical texts and presents practical significance for multi-label medical text modeling tasks.

cs.CL↗

arXiv2025

Magnetic Fields in the Pillars of Creation

Due to dust grain alignment with magnetic fields, dust polarization observations of far-infrared emission from cold molecular clouds are often used to trace magnetic fields, allowing a probe of the effects of magnetic fields on the star formation process. We present inferred magnetic field maps of the Pillars of Creation region within the larger M16 emission nebula, derived from dust polarization data in the 89 and 154 micron continuum using SOFIA/HAWC+. We derive magnetic field strength estimates using the Davis-Chandrasekhar-Fermi method. We compare the polarization and magnetic field strengths to column densities and dust continuum intensities across the region to build a coherent picture of the relationship between star forming activity and magnetic fields in the region. The projected magnetic field strengths derived are in the range of 50-130 microGauss, which is typical for clouds of similar n(H2), i.e., molecular hydrogen volume density on the order of 10^4-10^5 cm^(-3). We conclude that star formation occurs in the finger tips when the magnetic fields are too weak to prevent radial collapse due to gravity but strong enough to oppose OB stellar radiation pressure, while in the base of the fingers the magnetic fields hinder mass accretion and consequently star formation. We also support an initial weak field model (<50 microGauss) with subsequent strengthening through realignment and compression, resulting in a dynamically important magnetic field.

astro-ph.GA↗

arXiv2025

L1448 IRS3B: Dust Polarization Aligned with Spiral Features, Tracing Gas Flows

Circumstellar disk dust polarization in the (sub)millimeter is, for the most part, not from dust grain alignment with magnetic fields but rather indicative of a combination of dust self-scattering with a yet unknown alignment mechanism that is consistent with mechanical alignment. While the observational evidence for scattering has been well established, that for mechanical alignment is less so. Circum-multiple dust structures in protostellar systems provide a unique environment to probe different polarization alignment mechanisms. We present ALMA Band 4 and Band 7 polarization observations toward the multiple young system L1448 IRS3B. The polarization in the two Bands is consistent with each other, presenting multiple polarization morphologies. On the size scale of the inner envelope surrounding the circum-multiple disk, the polarization is consistent with magnetic field dust grain alignment. On the very small scale of compact circumstellar regions, we see polarization that is consistent with scattering around source a and c, which are likely the most optically thick components. Finally, we see polarization that is consistent with mechanical alignment of dust grains along the spiral dust structures, which would suggest that the dust is tracing the relative gas flow along the spiral arms. If the gas-flow dust grain alignment mechanism is dominant in these cases, disk dust polarization may provide a direct probe of the small-scale kinematics of the gas flow relative to the dust grains.

astro-ph.SR↗

arXiv2024

Dust mass in protoplanetary disks with porous dust opacities

ALMA surveys have suggested that protoplanetary disks are not massive enough to form the known exoplanet population, under the assumption that the millimeter continuum emission is optically thin. In this work, we investigate how the mass determination is influenced when the porosity of dust grains is considered in radiative transfer models. The results show that disks with porous dust opacities yield similar dust temperature, but systematically lower millimeter fluxes compared to disks incorporating compact dust grains. Moreover, we recalibrate the relation between dust temperature and stellar luminosity for a wide range of stellar parameters, and calculate the dust masses of a large sample of disks using the traditionally analytic approach. The median dust mass from our calculation is about 6 times higher than the literature result, and this is mostly driven by the different opacities of porous and compact grains. A comparison of the cumulative distribution function between disk dust masses and exoplanet masses show that the median exoplanet mass is about 2 times lower than the median dust mass, if grains are porous, and there are no exoplanetary systems with masses higher than the most massive disks. Our analysis suggests that adopting porous dust opacities may alleviate the mass budget problem for planet formation. As an example illustrating the combined effects of optical depth and porous dust opacities on the mass estimation, we conduct new IRAM/NIKA-2 observations toward the IRAS 04370+2559 disk and perform a detailed radiative transfer modeling of the spectral energy distribution. The best-fit dust mass is roughly 100 times higher than the value from the traditionally analytic calculation. Future spatially resolved observations at various wavelengths are required to better constrain the dust mass.

astro-ph.EP↗

arXiv2024

Polarization Substructure in the Spiral-Dominated HH 111 Disk: Evidence for Grain Growth

The HH 111 protostellar disk has recently been found to host a pair of spiral arms. Here we report the dust polarization results in the disk as well as the inner envelope around it, obtained with the Atacama Large Millimeter/submillimeter Array in continuum at lambda ~ 870 micron and ~ 0. 05" resolution. In the inner envelope, polarization is detected with a polarization degree of ~ 6% and an orientation almost everywhere parallel to the minor axis of the disk, and thus likely to be due to the dust grains magnetically aligned mainly by toroidal fields. In the disk, the polarization orientation is roughly azimuthal on the far side and becomes parallel to the minor axis on the near side, with a polarization gap in between on the far side near the central protostar. The disk polarization degree is ~ 2%. The polarized intensity is higher on the near side than the far side, showing a near-far side asymmetry. More importantly, the polarized intensity and thus polarization degree are lower in the spiral arms, but higher in between the arms, showing an anticorrelation of the polarized intensity with the spiral arms. Our modeling results indicate that this anticorrelation is useful for constraining the polarization mechanism and is consistent with the dust self-scattering by the grains that have grown to a size of ~ 150 micron. The interarms are sandwiched and illuminated by two brighter spiral arms and thus have higher polarized intensity. Our dust self-scattering model can also reproduce the observed polarization orientation parallel to the minor axis on the near side and the observed azimuthal polarization orientation at the two disk edges in the major axis.

astro-ph.GA↗

arXiv2024

Badminton Birdie-Like Aerodynamic Alignment of Drifting Dust Grains by Subsonic Gaseous Flows in Protoplanetary Disks

Recent (sub)millimeter polarization observations of protoplanetary disks reveal toroidally aligned, effectively prolate dust grains large enough (at least ~100 $\mu$m) to efficiently scatter millimeter light. The alignment mechanism for these grains remains unclear. We explore the possibility that gas drag aligns grains through gas-dust relative motion when the grain's center of mass is offset from its geometric center, analogous to a badminton birdie's alignment in flight. A simple grain model of two non-identical spheres illustrates how a grain undergoes damped oscillations from flow-induced restoring torques which align its geometric center in the flow direction relative to its center of mass. Assuming specular reflection and subsonic flow, we derive an analytical equation of motion for spheroids where the center of mass can be shifted away from the spheroid's geometric center. We show that a prolate or an oblate grain can be aligned with the long axis parallel to the gas flow when the center of mass is shifted along that axis. Both scenarios can explain the required effectively prolate grains inferred from observations. Application to a simple disk model shows that the alignment timescales are shorter than or comparable to the orbital time. The grain alignment direction in a disk depends on the disk (sub-)structure and grain Stokes number (St) with azimuthal alignment for large St grains in sub-Keplerian smooth gas disks and for small St grains near the gas pressure extrema, such as rings and gaps.

astro-ph.EP↗

arXiv2024

Massive 1D Dirac Line, Solitons and Reversible Manipulation on the Surface of a Prototype Obstructed Atomic Insulator, Silicon

Topologically trivial insulators can be classified into atomic insulators (AIs) and obstructed atomic insulators (OAIs) depending on whether the Wannier charge centers are localized or not at spatial positions occupied by atoms. An OAI can possess unusual properties such as surface states along certain crystalline surfaces, which advantageously appear in materials with much larger bulk energy gap than topological insulators, making them more attractive for potential applications. In this work, we show that a well-known crystal, silicon (Si) is a model OAI, which naturally explains some of Si's unusual properties such as its famous (111) surface states. On this surface, using angle resolved photoemission spectroscopy (ARPES), we reveal sharp quasi-1D massive Dirac line dispersions; we also observe, using scanning tunneling microscopy/spectroscopy (STM/STS), topological solitons at the interface of the two atomic chains. Remarkably, we show that the different chain domains can be reversibly switched at the nanometer scale, suggesting the application potential in ultra-high density storage devices.

cond-mat.mes-hall↗

arXiv2024

A Versatile Framework for Analyzing Galaxy Image Data by Implanting Human-in-the-loop on a Large Vision Model

The exponential growth of astronomical datasets provides an unprecedented opportunity for humans to gain insight into the Universe. However, effectively analyzing this vast amount of data poses a significant challenge. Astronomers are turning to deep learning techniques to address this, but the methods are limited by their specific training sets, leading to considerable duplicate workloads too. Hence, as an example to present how to overcome the issue, we built a framework for general analysis of galaxy images, based on a large vision model (LVM) plus downstream tasks (DST), including galaxy morphological classification, image restoration, object detection, parameter extraction, and more. Considering the low signal-to-noise ratio of galaxy images and the imbalanced distribution of galaxy categories, we have incorporated a Human-in-the-loop (HITL) module into our large vision model, which leverages human knowledge to enhance the reliability and interpretability of processing galaxy images interactively. The proposed framework exhibits notable few-shot learning capabilities and versatile adaptability to all the abovementioned tasks on galaxy images in the DESI legacy imaging surveys. Expressly, for object detection, trained by 1000 data points, our DST upon the LVM achieves an accuracy of 96.7%, while ResNet50 plus Mask R-CNN gives an accuracy of 93.1%; for morphology classification, to obtain AUC ~0.9, LVM plus DST and HITL only requests 1/50 training sets compared to ResNet18. Expectedly, multimodal data can be integrated similarly, which opens up possibilities for conducting joint analyses with datasets spanning diverse domains in the era of multi-message astronomy.

astro-ph.IM↗

arXiv2024

Dynamic Against Dynamic: An Open-set Self-learning Framework

In open-set recognition, existing methods generally learn statically fixed decision boundaries using known classes to reject unknown classes. Though they have achieved promising results, such decision boundaries are evidently insufficient for universal unknown classes in dynamic and open scenarios as they can potentially appear at any position in the feature space. Moreover, these methods just simply reject unknown class samples during testing without any effective utilization for them. In fact, such samples completely can constitute the true instantiated representation of the unknown classes to further enhance the model's performance. To address these issues, this paper proposes a novel dynamic against dynamic idea, i.e., dynamic method against dynamic changing open-set world, where an open-set self-learning (OSSL) framework is correspondingly developed. OSSL starts with a good closed-set classifier trained by known classes and utilizes available test samples for model adaptation during testing, thus gaining the adaptability to changing data distributions. In particular, a novel self-matching module is designed for OSSL, which can achieve the adaptation in automatically identifying known class samples while rejecting unknown class samples which are further utilized to enhance the discriminability of the model as the instantiated representation of unknown classes. Our method establishes new performance milestones respectively in almost all standard and cross-data benchmarks.

cs.LG↗