arXiv subjects

Ting Li

Publications and source records attributed to Ting Li.

At least 73 records · Page 4Linked to original sources

arXiv2024

Fast Downflows Observed during a Polar Crown Filament Eruption

Solar filaments can undergo eruptions and result in the formation of coronal mass ejections (CMEs), which could significantly impact planetary space environments. Observations of eruptions involving polar crown filaments, situated in the polar regions of the Sun, are limited. In this study, we report a polar crown filament eruption (SOL2023-06-12), characterized by fast downflows below the filament. The downflows appear instantly after the onset of the filament eruption and persist for approximately 2 hours, exhibiting plane-of-sky (POS) velocities ranging between 92 and 144 km s$^{-1}$. They originate from the leading edge of the filament and no clear acceleration is observed. Intriguingly, these downflows appear at two distinct sites, symmetrically positioned at the opposite ends of the conjugate flare ribbons. Based on the observations, we propose that the filament might be supported by a magnetic flux rope (MFR), and these downflows possibly occur along the legs of the MFR. The downflows likely result from continuous reconnections between the MFR and the overlying magnetic field structures, and could either be reconnection outflows or redirected filament materials. We also observed horizontal drifting of the locations of downflows, which might correspond to the MFR's footpoint drifting. This type of downflows can potentially be utilized to track the footpoints of MFRs during eruptions.

astro-ph.SR↗

arXiv2024

Long-term variation of the solar polar magnetic fields at different latitudes

The polar magnetic fields of the Sun play an important role in governing solar activity and powering fast solar wind. However, because our view of the Sun is limited in the ecliptic plane, the polar regions remain largely uncharted. Using the high spatial resolution and polarimetric precision vector magnetograms observed by Hinode from 2012 to 2021, we investigate the long-term variation of the magnetic fields in polar caps at different latitudes. The Hinode magnetic measurements show that the polarity reversal processes in the north and south polar caps are non-simultaneous. The variation of the averaged radial magnetic flux density reveals that, in each polar cap, the polarity reversal is completed successively from the 70 degree latitude to the pole, reflecting a poleward magnetic flux migration therein. These results clarify the polar magnetic polarity reversal process at different latitudes.

astro-ph.SR↗

arXiv2024

New type of bubbling solutions to a critical fractional Schrödinger equation with double potentials

In this paper, we study the following critical fractional Schrödinger equation: \begin{equation} (-Δ)^s u+V(|y'|,y'')u=K(|y'|,y'')u^{\frac{n+2s}{n-2s}},\quad u>0,\quad y =(y',y'') \in \mathbb{R}^3\times\mathbb{R}^{n-3}, \qquad(0.1)\end{equation} where $n\geq 3$, $s\in(0,1)$, $V(|y'|,y'')$ and $K(|y'|,y'')$ are two bounded nonnegative potential functions. Under the conditions that $K(r,y'')$ has a stable critical point $(r_0,y_0'')$ with $r_0>0$, $K(r_0,y_0'')>0$ and $V(r_0,y_0'')>0$, we prove that equation (0.1) has a new type of infinitely many solutions that concentrate at points lying on the top and the bottom of a cylinder. In particular, the bubble solutions can concentrate at a pair of symmetric points with respect to the origin. Our proofs make use of a modified finite-dimensional reduction method and local Pohozaev identities.

math.AP↗

arXiv2024

Statistics of Solar White-Light Flares I: Optimization of Identification Methods and Application

White-light flares (WLFs) are energetic activity in stellar atmosphere. However, the observed solar WLF is relatively rare compared to stellar WLFs or solar flares observed at other wavelengths, limiting our further understanding solar/stellar WLFs through statistical studies. By analyzing flare observations from the \emph{Solar Dynamics Observatory (SDO)}, here we improve WLF identification methods for obtaining more solar WLFs and their accurate light curves from two aspects: 1) imposing constraints defined by the typical temporal and spatial distribution characteristics of WLF-induced signals; 2) setting the intrinsic threshold for each pixel in the flare ribbon region according to its inherent background fluctuation rather than a fixed threshold for the whole region. Applying the optimized method to 90 flares (30 C-class ones, 30 M-class ones, and 30 X-class ones) for a statistical study, we identified a total of 9 C-class WLFs, 18 M-class WLFs, and 28 X-class WLFs. The WLF identification rate of C-class flares reported here reaches 30\%, which is the highest to date to our best knowledge. It is also revealed that in each GOES energy level, the proportion of WLFs is higher in confined flares than that in eruptive flares. Moreover, a power-law relation is found between the WLF energy (\emph{E}) and duration ($τ$): $τ\propto {E}^{0.22}$, similar to those of solar hard/soft X-ray flares and other stellar WLFs. These results indicate that we could recognize more solar WLFs through optimizing the identification method, which will lay a base for future statistical and comparison study of solar and stellar WLFs.

astro-ph.SR↗

arXiv2024

Meridional flow in the solar polar caps revealed by magnetic field observation and simulation

As a large-scale motion on the Sun, the meridional flow plays an important role in determining magnetic structure and strength and solar cycle. However, the meridional flow near the solar poles is still unclear. The Hinode observations show that the magnetic flux density in polar caps decreases from the lower latitudes to the poles. Using a surface flux transport model, we simulate the global radial magnetic field to explore the physical process leading to the observed polar magnetic distribution pattern. For the first time, the high-resolution observations of the polar magnetic fields observed by Hinode are used to directly constrain the simulation. Our simulation reproduces the observed properties of the polar magnetic fields, suggesting the existence of a counter-cell meridional flow in the solar polar caps with a maximum amplitude of about 3 m s$^{-1}$.

astro-ph.SR↗

arXiv2024

Quasi-periodic oscillations of flare loops and slipping motion of ribbon substructures during a C-class flare

Quasi-periodic oscillations in solar flaring emission have been observed over the past few decades. To date, the underpinning processes resulting in the quasi-periodic oscillations remain unknown. In this paper, we report a unique event that exhibits both the long-duration quasi-periodic intensity oscillations of flare loops and the quasi-periodic slipping motion of ribbon substructures during a C9.1-class flare (SOL2015-03-15-T01:15), using the observations from Solar Dynamics Observatory and Interface Region Imaging Spectrograph. The high-temperature flare loops rooted in the straight part of ribbons display a "bright-dim" intensity oscillation, with a period of about 4.5 minutes. The oscillation starts just after the flare onset and lasts over 3 hours. Meanwhile, the substructures within the ribbon tip display the quasi-periodic slipping motion along the ribbon at 1400 Åimages which has a similar periodicity to the stationary intensity oscillation of the flare loops in the straight part of the flare ribbons. We suggest that the quasi-periodic pattern is probably related to the loop-top dynamics caused by the reconnection outflow impinging on the flare loops.

astro-ph.SR↗

arXiv2024

Bayesian Power Steering: An Effective Approach for Domain Adaptation of Diffusion Models

We propose a Bayesian framework for fine-tuning large diffusion models with a novel network structure called Bayesian Power Steering (BPS). We clarify the meaning behind adaptation from a \textit{large probability space} to a \textit{small probability space} and explore the task of fine-tuning pre-trained models using learnable modules from a Bayesian perspective. BPS extracts task-specific knowledge from a pre-trained model's learned prior distribution. It efficiently leverages large diffusion models, differentially intervening different hidden features with a head-heavy and foot-light configuration. Experiments highlight the superiority of BPS over contemporary methods across a range of tasks even with limited amount of data. Notably, BPS attains an FID score of 10.49 under the sketch condition on the COCO17 dataset.

cs.LG↗

arXiv2024

Combining Experimental and Historical Data for Policy Evaluation

This paper studies policy evaluation with multiple data sources, especially in scenarios that involve one experimental dataset with two arms, complemented by a historical dataset generated under a single control arm. We propose novel data integration methods that linearly integrate base policy value estimators constructed based on the experimental and historical data, with weights optimized to minimize the mean square error (MSE) of the resulting combined estimator. We further apply the pessimistic principle to obtain more robust estimators, and extend these developments to sequential decision making. Theoretically, we establish non-asymptotic error bounds for the MSEs of our proposed estimators, and derive their oracle, efficiency and robustness properties across a broad spectrum of reward shift scenarios. Numerical experiments and real-data-based analyses from a ridesharing company demonstrate the superior performance of the proposed estimators.

stat.ML↗

arXiv2024

A Study of the Spectral properties of Gamma-Ray Bursts with the Precursors and Main bursts

There is no consensus yet on whether the precursor and the main burst of gamma-ray bursts (GRBs) have the same origin, and their jet composition is still unclear. In order to further investigate this issue, we systematically search 21 Fermi GRBs with both precursor and main burst for spectral analysis. We first perform Bayesian time-resolved spectral analysis and find that almost all the precursors and the main bursts (94.4$\%$) exhibit thermal components, and the vast majority of them have low-energy spectral index ($α$) (72.2$\%$) that exceed the limit of synchrotron radiation. We then analyse the evolution and correlation of the spectral parameters and find that approximately half of the $α$ (50$\%$) of the precursors and the main bursts evolve in a similar pattern, while peak energy ($E_{p}$) (55.6$\%$) behave similarly, and their evolution is mainly characterized by flux tracking; for the $α-F$ (the flux) relation, more than half of the precursors and the main bursts (61.1$\%$) exhibit roughly similar patterns; the $E_{p}-F$ relation in both the precursor and main burst (100$\%$) exhibits a positive correlation of at least moderate strength. Next, we constrain the outflow properties of the precursors and the main bursts and find that most of them exhibit typical properties of photosphere radiation. Finally, we compare the time-integrated spectra of the precursors and the main bursts and find that nearly all of them are located in similar regions of the Amati relation and follow the Yonetoku relation. Therefore, we conclude that main bursts are continuations of precursors and they may share a common physical origin.

astro-ph.HE↗

arXiv2024

The Solar Origin of an Intense Geomagnetic Storm on 2023 December 1st: Successive Slipping and Eruption of Multiple Magnetic Flux Ropes

The solar eruption that occurred on 2023 November 28 (SOL2023-11-28) triggered an intense geomagnetic storm on Earth on 2023 December 1. The associated Earth's auroras manifested at the most southern latitudes in the northern hemisphere observed in the past two decades. In order to explore the profound geoeffectiveness of this event, we conducted a comprehensive analysis of its solar origin to offer potential factors contributing to its impact. Magnetic flux ropes (MFRs) are twisted magnetic structures recognized as significant contributors to coronal mass ejections (CMEs), thereby impacting space weather greatly. In this event, we identified multiple MFRs in the solar active region and observed distinct slipping processes of the three MFRs: MFR1, MFR2, and MFR3. All three MFRs exhibit slipping motions at a speed of 40--137 km s$^{-1}$, extending beyond their original locations. Notably, the slipping of MFR2 extends to $\sim$30 Mm and initiate the eruption of MFR3. Ultimately, MFR1's eruption results in an M3.4-class flare and a CME, while MFR2 and MFR3 collectively produce an M9.8-class flare and another halo CME. This study shows the slipping process in a multi-MFR system, showing how one MFR's slipping can trigger the eruption of another MFR. We propose that the CME--CME interactions caused by multiple MFR eruptions may contribute to the significant geoeffectiveness.

astro-ph.SR↗

arXiv2024

Synchronization of High-Dimensional Linear Networks over Finite Fields

This paper investigates the synchronization problems for general high-dimensional linear networks over finite fields. By using the technique of linear transformations and invariant subspaces for linear spaces over finite fields, several necessary and sufficient conditions for the synchronization of high-dimensional linear networks over finite fields are proposed. This paper not only generalizes the existing results from 1-dimensional to high-dimensional linear networks but also adopts a new approach. Finally, some numerical examples are given to illustrate the effectiveness of our theoretical results.

math.OC↗

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

Style Adaptation for Domain-adaptive Semantic Segmentation

Unsupervised Domain Adaptation (UDA) refers to the method that utilizes annotated source domain data and unlabeled target domain data to train a model capable of generalizing to the target domain data. Domain discrepancy leads to a significant decrease in the performance of general network models trained on the source domain data when applied to the target domain. We introduce a straightforward approach to mitigate the domain discrepancy, which necessitates no additional parameter calculations and seamlessly integrates with self-training-based UDA methods. Through the transfer of the target domain style to the source domain in the latent feature space, the model is trained to prioritize the target domain style during the decision-making process. We tackle the problem at both the image-level and shallow feature map level by transferring the style information from the target domain to the source domain data. As a result, we obtain a model that exhibits superior performance on the target domain. Our method yields remarkable enhancements in the state-of-the-art performance for synthetic-to-real UDA tasks. For example, our proposed method attains a noteworthy UDA performance of 76.93 mIoU on the GTA->Cityscapes dataset, representing a notable improvement of +1.03 percentage points over the previous state-of-the-art results.

cs.CV↗

arXiv2024

Magnetic helicity evolution during active region emergence and subsequent flare productivity

Aims. Solar active regions (ARs), which are formed by flux emergence, serve as the primary sources of solar eruptions. However, the specific physical mechanism that governs the emergence process and its relationship with flare productivity remains to be thoroughly understood. Methods. We examined 136 emerging ARs, focusing on the evolution of their magnetic helicity and magnetic energy during the emergence phase. Based on the relation between helicity accumulation and magnetic flux evolution, we categorized the samples and investigated their flare productivity. Results. The emerging ARs we studied can be categorized into three types, Type-I, Type-II, and Type-III, and they account for 52.2%, 25%, and 22.8% of the total number in our sample, respectively. Type-I ARs exhibit a synchronous increase in both the magnetic flux and magnetic helicity, while the magnetic helicity in Type-II ARs displays a lag in increasing behind the magnetic flux. Type-III ARs show obvious helicity injections of opposite signs. Significantly, 90% of the flare-productive ARs (flare index > 6) were identified as Type-I ARs, suggesting that this type of AR has a higher potential to become flare productive. In contrast, Type-II and Type-III ARs exhibited a low and moderate likelihood of becoming active, respectively. Our statistical analysis also revealed that Type-I ARs accumulate more magnetic helicity and energy, far beyond what is found in Type-II and Type-III ARs. Moreover, we observed that flare-productive ARs consistently accumulate a significant amount of helicity and energy during their emergence phase. Conclusions. These findings provide valuable insight into the flux emergence phenomena, offering promising possibilities for early-stage predictions of solar eruptions.

astro-ph.SR↗

arXiv2024

Node Centrality Approximation For Large Networks Based On Inductive Graph Neural Networks

Closeness Centrality (CC) and Betweenness Centrality (BC) are crucial metrics in network analysis, providing essential reference for discerning the significance of nodes within complex networks. These measures find wide applications in critical tasks, such as community detection and network dismantling. However, their practical implementation on extensive networks remains computationally demanding due to their high time complexity. To mitigate these computational challenges, numerous approximation algorithms have been developed to expedite the computation of CC and BC. Nevertheless, even these approximations still necessitate substantial processing time when applied to large-scale networks. Furthermore, their output proves sensitive to even minor perturbations within the network structure. In this work, We redefine the CC and BC node ranking problem as a machine learning problem and propose the CNCA-IGE model, which is an encoder-decoder model based on inductive graph neural networks designed to rank nodes based on specified CC or BC metrics. We incorporate the MLP-Mixer model as the decoder in the BC ranking prediction task to enhance the model's robustness and capacity. Our approach is evaluated on diverse synthetic and real-world networks of varying scales, and the experimental results demonstrate that the CNCA-IGE model outperforms state-of-the-art baseline models, significantly reducing execution time while improving performance.

cs.SI↗

arXiv2024

Survey of Magnetic Field Parameters Associated With Large Solar Flares

Until now, how the magnetic fields in M/X-class flaring active regions (ARs) differ from C-class flaring ARs remains unclear. Here, we calculate the key magnetic field parameters within the area of high photospheric free energy density (HED region) for 323 ARs (217 C- and 106 M$/$X-flaring ARs), including total photospheric free magnetic energy density E$_{free}$, total unsigned magnetic flux $Φ$$_{HED}$, mean unsigned current helicity h$_{c}$, length of the polarity inversion lines $L$$_{PIL}$ with a steep horizontal magnetic gradient, etc., and compare these with flare/coronal mass ejection (CME) properties. We first show the quantitative relations among the flare intensity, the eruptive character and $Φ$$_{HED}$. We reveal that $Φ$$_{HED}$ is a measure for the GOES flux upper limit of the flares in a given region. For a given $Φ$$_{HED}$, there exists the lower limit of F$_\mathrm{SXR}$ for eruptive flares. This means that only the relatively strong flares with the large fraction of energy release compared to the total free energy are likely to generate a CME. We also find that the combinations of E$_{free}$-$L$$_{PIL}$ and E$_{free}$-h$_{c}$ present a good ability to distinguish between C-class and M$/$X-class flaring ARs. Using determined critical values of E$_{free}$ and $L$$_{PIL}$, one predicts correctly 93 out of 106 M/X-class flaring ARs and 159/217 C-class flaring ARs. The large $L$$_{PIL}$ or h$_{c}$ for M$/$X-class flaring ARs probably implies the presence of a compact current with twisted magnetic fields winding about it.

astro-ph.SR↗

arXiv2024

A Quick Framework for Evaluating Worst Robustness of Complex Networks

Robustness is pivotal for comprehending, designing, optimizing, and rehabilitating networks, with simulation attacks being the prevailing evaluation method. Simulation attacks are often time-consuming or even impractical, however, a more crucial yet persistently overlooked drawback is that any attack strategy merely provides a potential paradigm of disintegration. The key concern is: in the worst-case scenario or facing the most severe attacks, what is the limit of robustness, referred to as ``Worst Robustness'', for a given system? Understanding a system's worst robustness is imperative for grasping its reliability limits, accurately evaluating protective capabilities, and determining associated design and security maintenance costs. To address these challenges, we introduce the concept of Most Destruction Attack (MDA) based on the idea of knowledge stacking. MDA is employed to assess the worst robustness of networks, followed by the application of an adapted CNN algorithm for rapid worst robustness prediction. We establish the logical validity of MDA and highlight the exceptional performance of the adapted CNN algorithm in predicting the worst robustness across diverse network topologies, encompassing both model and empirical networks.

cs.SI↗

arXiv2024

CodeFuse-13B: A Pretrained Multi-lingual Code Large Language Model

Code Large Language Models (Code LLMs) have gained significant attention in the industry due to their wide applications in the full lifecycle of software engineering. However, the effectiveness of existing models in understanding non-English inputs for multi-lingual code-related tasks is still far from well studied. This paper introduces CodeFuse-13B, an open-sourced pre-trained code LLM. It is specifically designed for code-related tasks with both English and Chinese prompts and supports over 40 programming languages. CodeFuse achieves its effectiveness by utilizing a high quality pre-training dataset that is carefully filtered by program analyzers and optimized during the training process. Extensive experiments are conducted using real-world usage scenarios, the industry-standard benchmark HumanEval-x, and the specially designed CodeFuseEval for Chinese prompts. To assess the effectiveness of CodeFuse, we actively collected valuable human feedback from the AntGroup's software development process where CodeFuse has been successfully deployed. The results demonstrate that CodeFuse-13B achieves a HumanEval pass@1 score of 37.10%, positioning it as one of the top multi-lingual code LLMs with similar parameter sizes. In practical scenarios, such as code generation, code translation, code comments, and testcase generation, CodeFuse performs better than other models when confronted with Chinese prompts.

cs.SE↗