arXiv subjects

Yilin Guo

Publications and source records attributed to Yilin Guo.

At least 19 recordsLinked to original sources

arXiv2026

Time-asymptotic stability of generic Riemann solutions for the system of heat-conductive ideal gas without viscosity

This paper is concerned with the time-asymptotic stability of the generic Riemann solution for the one-dimensional system of heat-conductive ideal gas without viscosity, where the generic Riemann solution consists of a shock, a contact discontinuity, and a rarefaction wave. We prove that, as time tends to infinity, the solution of the non-viscous and heat-conductive ideal gas system converges uniformly to a composite wave composed of rarefaction wave, viscous contact wave, and viscous shock wave with a time-dependent shift. Motivated by the recent work of Kang-Vasseur-Wang [Arch. Ration. Mech. Anal. 249: 42 (2025)], we overcome the difficulties arising from the concurrence of shock and rarefaction waves for the partially dissipative hyperbolic-parabolic system with dissipation acting only on a single variable. More notably, the absence of velocity dissipation gives rise to new and intrinsic difficulties when handling the terms associated with the density and velocity. To resolve this, we exploit the precise structure of the governing equations and the additional properties of shock waves. Furthermore, we utilize the wave structure of the system without viscosity and perform separate space-time estimates for the density and velocity.

math.AP↗

arXiv2026

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

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

astro-ph.SR↗

arXiv2026

PIML-OFEM: A New Large-Scale Structural Analysis Method Based on Problem-Independent Machine Learning and Overlapping Finite Element Technique

High-resolution analysis and design of large-scale heterogeneous structures require accurate reduced-order models and efficient online computation. Existing multiscale methods must repeatedly construct local basis functions for different material distributions, whereas substructure-based problem-independent machine learning (PIML) methods can be limited by prescribed boundary displacement interpolation. We propose PIML-OFEM, an overlapping finite element method accelerated by problem-independent machine learning. Each substructure retains only its corner-node degrees of freedom. Oversampled numerical basis functions are constructed by solving local elasticity problems on extended domains and restricting the solutions to the target substructure, eliminating prescribed displacement interpolation on its boundary. Independently constructed local bases are blended through a partition-of-unity overlapping formulation to obtain a globally continuous displacement field. A U-Net learns the mapping from local Young's modulus distributions to numerical basis functions, replacing repeated online local solves and allowing the model to be reused across load cases and global boundary conditions. Numerical examples show close agreement with fine-scale finite element results in displacement and elemental strain energy. PIML-OFEM reduces online computational cost relative to direct finite element analysis and improves accuracy over PIML substructure models based on linear boundary interpolation. In topology optimization, the method supports stable high-resolution iterations with small filter radii and preserves fine-scale features, including local patterns resembling rank-2 microstructures. The framework provides an efficient physics-data approach for large-scale heterogeneous structural analysis and high-resolution topology optimization.

math.NA↗

arXiv2026

An Ore-type condition for $H$-tilings in graphs

A graph $G$ admits an $H$-tiling if it contains a collection of vertex-disjoint copies of $H$. In this paper, we confirm a conjecture proposed by K\"{u}hn, Osthus, and Treglown by showing that for any given graph $H$, there exists a constant $C(H)$ such that the following holds. If $G$ is a sufficiently large $n$-vertex graph satisfying $d(x) + d(y) \geq 2\left(1 - 1/\chi_{\text{cr}}(H)\right)n$ for all nonadjacent vertices $x, y \in V(G)$, then $G$ contains an $H$-tiling covering all but at most $C(H)$ vertices. Here $\chi_{\text{cr}}(H)$ denotes the critical chromatic number of $H$.

math.CO↗

arXiv2026

Magnetic Evolution of Highly-Sheared Region in Active Region 13842 Producing Large X9.0 Flare

Shearing motion and magnetic flux cancellation around the polarity inversion line (PIL) play significant roles in the build-up of free magnetic energy and magnetic flux rope (MFR) in source region of major solar flares. Here we investigate the magnetic evolution of a highly-sheared PIL in active region (AR) 13842, hosting the largest X9.0 flare of Solar Cycle 25. Since 2024 September 29, a positive-polarity pore persistently drifted northward along the western side of the AR's main negative-polarity sunspot. The main sunspot remained stationary until negative-polarity patches successively emerged to its east and approached. Rear-ended by these same-polarity patches, the sunspot then began moving westward toward the opposite-polarity pore around October 1, forming a collisional PIL. Meanwhile, on the PIL's other side, the pore was also rear-ended by same-polarity patches sequentially emerging behind it, accelerating the shearing motion around the PIL, where frequent flux cancellations were also observed. Synchronous rapid accumulation of free magnetic energy and formation of MFR were then observed in the PIL, where multiple major flares successively occurred within two days. Before these large flares, the area and total free energy of the high-free-energy-density PIL region gradually decreased in the photosphere, which could be caused by the initial ascent of MFR before eruption and serve as a precursor of solar eruptions. These results suggest that persistent flux emergences with cross separation directions facilitates rapid formation of collisional shearing PIL and frequent flux cancellations, leading to repeated MFR formations and multiple large flares in a relatively short time.

astro-ph.SR↗

arXiv2026

AdaGATE: Adaptive Gap-Aware Token-Efficient Evidence Assembly for Multi-Hop Retrieval-Augmented Generation

Retrieval-augmented generation (RAG) remains brittle on multi-hop questions in realistic deployment settings, where retrieved evidence may be noisy or redundant and only limited context can be passed to the generator. Existing controllers address parts of this problem, but typically either expand context additively, select from a fixed top-k set, or optimize relevance without explicitly repairing missing bridge facts. We propose AdaGATE, a training-free evidence controller for multi-hop RAG that frames evidence selection as a token-constrained repair problem. AdaGATE combines entity centric gap tracking, targeted micro-query generation, and a utility based selection mechanism that balances gap coverage, corroboration, novelty, redundancy, and direct question relevance. We evaluate AdaGATE on HotpotQA under clean, redundancy, and noise injected retrieval conditions. Across all three settings, AdaGATE achieves the best evidence F1 among the compared controllers, reaching 62.3% on clean data and 71.2% under redundancy injection, while using 2.6x fewer input tokens than Adaptive-k. These results suggest that explicit gap-aware repair, combined with token-efficient evidence selection, improves robustness in multi-hop RAG under imperfect retrieval. Our code and evaluation pipeline are available at https://github.com/eliguo/AdaGATE.

cs.CL↗

arXiv2025

KPLM-STA: Physically-Accurate Shadow Synthesis for Human Relighting via Keypoint-Based Light Modeling

Image composition aims to seamlessly integrate a foreground object into a background, where generating realistic and geometrically accurate shadows remains a persistent challenge. While recent diffusion-based methods have outperformed GAN-based approaches, existing techniques, such as the diffusion-based relighting framework IC-Light, still fall short in producing shadows with both high appearance realism and geometric precision, especially in composite images. To address these limitations, we propose a novel shadow generation framework based on a Keypoints Linear Model (KPLM) and a Shadow Triangle Algorithm (STA). KPLM models articulated human bodies using nine keypoints and one bounding block, enabling physically plausible shadow projection and dynamic shading across joints, thereby enhancing visual realism. STA further improves geometric accuracy by computing shadow angles, lengths, and spatial positions through explicit geometric formulations. Extensive experiments demonstrate that our method achieves state-of-the-art performance on shadow realism benchmarks, particularly under complex human poses, and generalizes effectively to multi-directional relighting scenarios such as those supported by IC-Light.

cs.CV↗

arXiv2025

RiverEcho: Real-Time Interactive Digital System for Ancient Yellow River Culture

The Yellow River is China's mother river and a cradle of human civilization. The ancient Yellow River culture is, moreover, an indispensable part of human art history. To conserve and inherit the ancient Yellow River culture, we designed RiverEcho, a real-time interactive system that responds to voice queries using a large language model and a cultural knowledge dataset, delivering explanations through a talking-head digital human. Specifically, we built a knowledge database focused on the ancient Yellow River culture, including the collection of historical texts and the processing pipeline. Experimental results demonstrate that leveraging Retrieval-Augmented Generation (RAG) on the proposed dataset enhances the response quality of the Large Language Model(LLM), enabling the system to generate more professional and informative responses. Our work not only diversifies the means of promoting Yellow River culture but also provides users with deeper cultural insights.

cs.MM↗

arXiv2025

Quasiperiodic Slow-Propagating EUV "Wave" Trains After the Filament Eruption

The eruption of the filament/flux rope generates the coronal perturbations, which further form EUV waves. There are two types of EUV waves, including fast-mode magnetosonic waves and slow waves. In this paper, we first report an event showing the Quasiperiodic Slow-Propagating (QSP) EUV "wave" trains during an M6.4-class flare (SOL2023-02-25T18:40), using multiple observations from SDO/AIA, CHASE/HIS, ASO-S/FMG, SUTRI, and LASCO/C2. The QSP "wave" trains occurred as the filament showed a rapid rise. The QSP "wave" trains have the projected speeds of 50-130 km s$^{-1}$ on the plane of the sky, which is slower than the fast-mode magnetosonic speed in the solar corona. And the calculated period of the QSP wave trains is 117.9 s, which is in good agreement with the associated flare Quasi-Periodic Pulsation (140.3 s). The QSP wave trains could be observed during the entire impulsive phase of the flare and lasted about 30 minutes in the field of view (FOV) of SDO/AIA. About 30 minutes later, they appeared in the FOV of LASCO/C2 and propagated to the northwest. We suggest that the QSP wave trains are probably apparent waves that are caused by the successive stretching of the inclined field lines overlying the eruptive filament. The periodic pattern of the QSP wave trains may be related to the intermittent energy release during the flare.

astro-ph.SR↗

arXiv2025

UCFE: A User-Centric Financial Expertise Benchmark for Large Language Models

This paper introduces the UCFE: User-Centric Financial Expertise benchmark, an innovative framework designed to evaluate the ability of large language models (LLMs) to handle complex real-world financial tasks. UCFE benchmark adopts a hybrid approach that combines human expert evaluations with dynamic, task-specific interactions to simulate the complexities of evolving financial scenarios. Firstly, we conducted a user study involving 804 participants, collecting their feedback on financial tasks. Secondly, based on this feedback, we created our dataset that encompasses a wide range of user intents and interactions. This dataset serves as the foundation for benchmarking 11 LLMs services using the LLM-as-Judge methodology. Our results show a significant alignment between benchmark scores and human preferences, with a Pearson correlation coefficient of 0.78, confirming the effectiveness of the UCFE dataset and our evaluation approach. UCFE benchmark not only reveals the potential of LLMs in the financial domain but also provides a robust framework for assessing their performance and user satisfaction.

q-fin.CP↗

arXiv2025

Signal-to-noise ratio aware minimax analysis of sparse linear regression

We consider parameter estimation under sparse linear regression -- an extensively studied problem in high-dimensional statistics and compressed sensing. While the minimax framework has been one of the most fundamental approaches for studying statistical optimality in this problem, we identify two important issues that the existing minimax analyses face: (i) The signal-to-noise ratio appears to have no effect on the minimax optimality, while it shows a major impact in numerical simulations. (ii) Estimators such as best subset selection and Lasso are shown to be minimax optimal, yet they exhibit significantly different performances in simulations. In this paper, we tackle the two issues by employing a minimax framework that accounts for variations in the signal-to-noise ratio (SNR), termed the SNR-aware minimax framework. We adopt a delicate higher-order asymptotic analysis technique to obtain the SNR-aware minimax risk. Our theoretical findings determine three distinct SNR regimes: low-SNR, medium-SNR, and high-SNR, wherein minimax optimal estimators exhibit markedly different behaviors. The new theory not only offers much better elaborations for empirical results, but also brings new insights to the estimation of sparse signals in noisy data.

math.ST↗

arXiv2024

Formation and Evolution of Transient Prominence Bubbles Driven by Erupting Mini-filaments

Prominence bubbles, the dark arch-shaped "voids" below quiescent prominences, are generally believed to be caused by the interaction between the prominences and the slowly-emerging or quasi-stable underlying magnetic loops. However, this scenario could not explain some short-lived bubbles with extremely dynamic properties of evolution. Based on high-resolution H$α$ observations, here we propose that bubbles should be classified into two categories according to their dynamic properties: quasi-steady (Type-I) bubbles and transient (Type-II) bubbles. Type-I bubbles could remain relatively stable and last for several hours, indicating the existence of a quasi-stable magnetic topology, while Type-II bubbles grow and collapse quickly within one hour without stability duration, which are usually associated with erupting mini-filaments. Analysis of several typical Type-II bubbles from different views, especially including an on-disk event, reveals that Type-II bubbles quickly appear and expand at a velocity of $\thicksim$5--25 km s$^{-1}$ accompanied by an erupting mini-filament below. The mini-filament's rising velocity is slightly larger than that of the Type-II bubbles' boundary, which will lead to the collision with each other in a short time, subsequent collapse of Type-II bubbles, and formation of a large plume into the above prominence. We also speculate that only if the angle between the axis of the erupting mini-filament and the line-of-sight is large enough, the interaction between the erupting mini-filament and the overlying prominence could trigger a Type-II bubble with a typical arch-shaped but quickly-expanding bright boundary.

astro-ph.SR↗

arXiv2024

A note on the minimax risk of sparse linear regression

Sparse linear regression is one of the classical and extensively studied problems in high-dimensional statistics and compressed sensing. Despite the substantial body of literature dedicated to this problem, the precise determination of its minimax risk remains elusive. This paper aims to fill this gap by deriving asymptotically constant-sharp characterization for the minimax risk of sparse linear regression. More specifically, the paper focuses on scenarios where the sparsity level, denoted as k, satisfies the condition $(k \log p)/n {\to} 0$, with p and n representing the number of features and observations respectively. We establish that the minimax risk under isotropic Gaussian random design is asymptotically equal to $2{\sigma}^2k/n log(p/k)$, where ${\sigma}$ denotes the standard deviation of the noise. In addition to this result, we will summarize the existing results in the literature, and mention some of the fundamental problems that have still remained open.

math.ST↗

arXiv2024

Shell-infill composite structure design based on a hybrid explicit-implicit topology optimization method

The present paper introduces a hybrid explicit-implicit topology optimization method for shell-infill composite structure design. The proposed approach effectively combines the advantages of the explicit Moving Morphable Component (MMC) method, which describes structural topology only using a set of geometric parameters, and the implicit Solid Isotropic Material with Penalization (SIMP) method, which offers greater design freedom for characterizing the structural features. Compared to the existing methods for shell-infill structure design, the proposed approach can obtain optimized shell-infill structures with complex infill topology without resorting to complex filtering/projection operations. Numerical examples demonstrate the effectiveness of the proposed approach.

math.OC↗

arXiv2023

Signal-to-noise ratio aware minimaxity and higher-order asymptotics

Since its development, the minimax framework has been one of the corner stones of theoretical statistics, and has contributed to the popularity of many well-known estimators, such as the regularized M-estimators for high-dimensional problems. In this paper, we will first show through the example of sparse Gaussian sequence model, that the theoretical results under the classical minimax framework are insufficient for explaining empirical observations. In particular, both hard and soft thresholding estimators are (asymptotically) minimax, however, in practice they often exhibit sub-optimal performances at various signal-to-noise ratio (SNR) levels. The first contribution of this paper is to demonstrate that this issue can be resolved if the signal-to-noise ratio is taken into account in the construction of the parameter space. We call the resulting minimax framework the signal-to-noise ratio aware minimaxity. The second contribution of this paper is to showcase how one can use higher-order asymptotics to obtain accurate approximations of the SNR-aware minimax risk and discover minimax estimators. The theoretical findings obtained from this refined minimax framework provide new insights and practical guidance for the estimation of sparse signals.

math.ST↗

arXiv2023

Partial Eruption of Solar Filaments. I. Configuration and Formation of Double-decker Filaments

Partial eruptions of solar filaments are the typical representative of solar eruptive behavior diversity. Here we investigate a typical filament partial eruption event and present integrated evidence for configuration of the pre-eruption filament and its formation. The CHASE H$α$ observations reveal structured Doppler velocity distribution within the pre-eruption filament, where distinct redshift only appeared in the east narrow part of the south filament region and then disappeared after the partial eruption while the north part dominated by blueshift remained. Combining the SDO, ASO-S observations, and NLFFF modeling results, we verify that there were two independent material flow systems within the pre-flare filament, whose magnetic topology is a special double-decker configuration consisting of two magnetic flux ropes (MFRs) with opposite magnetic twist. During the formation of this filament system, continuous magnetic flux cancellation and footpoint motion were observed around its north end. Therefore, we propose a new double-decker formation scenario that the two MFRs composing such double-decker configuration originated from two magnetic systems with different initial connections and opposite magnetic twist. Subsequent magnetic reconnection with surrounding newly-emerging fields resulted in the motion of footpoint of the upper MFR to the region around footpoint of the lower MFR, thus leading to eventual formation of the double-decker configuration consisting of two MFRs with similar footpoints but opposite signs of magnetic twist. These results provide a potential way to determine unambiguously the progenitor configuration of a partial-eruptive filament and reveal a special type of double-decker MFR configuration and a new double-decker formation scenario.

astro-ph.SR↗

arXiv2022

An efficient and easy-to-extend Matlab code of the Moving Morphable Component (MMC) method for three-dimensional topology optimization

Explicit topology optimization methods have received ever-increasing interest in recent years. In particular, a 188-line Matlab code of the two-dimensional (2D) Moving Morphable Component (MMC)-based topology optimization method was released by Zhang et al. (Struct Multidiscip Optim 53(6):1243-1260, 2016). The present work aims to propose an efficient and easy-to-extend 256-line Matlab code of the MMC method for three-dimensional (3D) topology optimization implementing some new numerical techniques. To be specific, by virtue of the function aggregation technique, accurate sensitivity analysis, which is also easy-to-extend to other problems, is achieved. Besides, based on an efficient identification algorithm for load transmission path, the degrees of freedoms (DOFs) not belonging to the load transmission path are removed in finite element analysis (FEA), which significantly accelerates the optimization process. As a result, compared to the corresponding 188-line 2D code, the performance of the optimization results, the computational efficiency of FEA, and the convergence rate and the robustness of optimization process are greatly improved. For the sake of completeness, a refined 218-line Matlab code implementing the 2D-MMC method is also provided.

math.OC↗

arXiv2022

Various Activities above Sunspot Light Bridges in IRIS Observations: Classification and Comparison

Light bridges (LBs) are among the most striking sub-structures in sunspots, where various activities have been revealed by recent high-resolution observations from the Interface Region Imaging Spectrograph (IRIS). According to the variety of physical properties, we classified these activities into four distinct categories: transient brightening (TB), intermittent jet (IJ), type-I light wall (LW-I), and type-II light wall (LW-II). In IRIS 1400/1330 Å observations, TBs are characterized by abrupt emission enhancements, and IJs appear as collimated plasma ejections with a width of 1-2 Mm at some LB sites. Most observed TBs are associated with IJs and show superpositions of some chromosphere absorption lines on enhanced and broadened wings of C II and Si IV lines, which could be driven by intermittent magnetic reconnection in the lower atmosphere. LW-I and LW-II are wall-shaped structures with bright fronts above the whole LB. An LW-I has a continuous oscillating front with a typical height of several Mm and an almost stationary period of 4-5 minutes. On the contrary, an LW-II has a indented front with a height of over 10 Mm, which has no stable period and is accompanied by recurrent TBs in the entire LB. These results support that LW-IIs are driven by frequent reconnection occurring along the whole LB due to large-scale magnetic flux emergence or intrusion, rather than the leakage of waves producing LW-Is. Our observations reveal a highly dynamical scenario of activities above LBs driven by different basic physical processes, including magneto-convection, magnetic reconnection, and wave leakage.

astro-ph.SR↗