arXiv subjects

Hui Li

Publications and source records attributed to Hui Li.

At least 397 records · Page 22Linked to original sources

arXiv2024

Plasma Dynamics and Nonthermal Particle Acceleration in 3D Nonrelativistic Magnetic Reconnection

Understanding plasma dynamics and nonthermal particle acceleration in 3D magnetic reconnection has been a long-standing challenge. In this paper, we explore these problems by performing large-scale fully kinetic simulations of multi-xline plasmoid reconnection with various parameters in both the weak and strong guide field regimes. In each regime, we have identified its unique 3D dynamics that leads to field-line chaos and efficient acceleration, and we have achieved nonthermal acceleration of both electrons and protons into power-law spectra. The spectral indices agree well with a simple Fermi acceleration theory that includes guide field dependence. In the low-guide-field regime, the flux-rope kink instability governs the 3D dynamics for efficient acceleration. The weak dependence of the spectra on the ion-to-electron mass ratio and $β$ ($\ll1$) implies that the particles are sufficiently magnetized for Fermi acceleration in our simulations. While both electrons and protons are injected at reconnection exhausts, protons are primarily injected by perpendicular electric fields through Fermi reflections and electrons are injected by a combination of perpendicular and parallel electric fields. The magnetic power spectra agree with in-situ magnetotail observations, and the spectral index may reflect a reconnection-driven size distribution of plasmoids instead of Goldreich-Sridhar vortex cascade. As the guide field becomes stronger, the oblique flux ropes of large sizes capture the main 3D dynamics for efficient acceleration. Intriguingly, the oblique flux ropes can also run into flux-rope kink instability to drive extra 3D dynamics. This work has broad implications for 3D reconnection dynamics and particle acceleration in heliophysics and astrophysics.

astro-ph.SR↗

arXiv2024

Enc2DB: A Hybrid and Adaptive Encrypted Query Processing Framework

As cloud computing gains traction, data owners are outsourcing their data to cloud service providers (CSPs) for Database Service (DBaaS), bringing in a deviation of data ownership and usage, and intensifying privacy concerns, especially with potential breaches by hackers or CSP insiders. To address that, encrypted database services propose encrypting every tuple and query statement before submitting to the CSP, ensuring data confidentiality when the CSP is honest-but-curious, or even compromised. Existing solutions either employ property preserving cryptography schemes, which can perform certain operations over ciphertext without decrypting the data over the CSP, or utilize trusted execution environment (TEE) to safeguard data and computations from the CSP. Based on these efforts, we introduce Enc2DB, a novel secure database system, following a hybrid strategy on PostgreSQL and openGauss. We present a micro-benchmarking test and self-adaptive mode switch strategy that can dynamically choose the best execution path (cryptography or TEE) to answer a given query. Besides, we also design and implement a ciphertext index compatible with native cost model and query optimizers to accelerate query processing. Empirical study over TPC-C test justifies that Enc2DB outperforms pure TEE and cryptography solutions, and our ciphertext index implementation also outperforms the state-of-the-art cryptographic-based system.

cs.CR↗

arXiv2024

eDIG-CHANGES II: Project Design and Initial Results on NGC 3556

The extraplanar diffuse ionized gas (eDIG) represents ionized gases traced by optical/UV lines beyond the stellar extent of galaxies. We herein introduce a novel multi-slit narrow-band spectroscopy method to conduct spatially resolved spectroscopy of the eDIG around a sample of nearby edge-on disk galaxies (eDIG-CHANGES). In this paper, we introduce the project design and major scientific goals, as well as a pilot study of NGC 3556 (M108). The eDIG is detected to a vertical extent of a few kpc above the disk, comparable to the X-ray and radio images. We do not see significant vertical variation of the [N II]/H$α$ line ratio. A rough examination of the pressure balance between different circum-galactic medium (CGM) phases indicates the magnetic field is in a rough pressure balance with the X-ray emitting hot gas, and may play an important role in the global motion of both the eDIG and the hot gas in the lower halo. At the location of an HST/COS observed UV bright background AGN $\sim29\rm~kpc$ from the center of NGC 3556, the magnetic pressure is much lower than that of the hot gas and the ionized gas traced by UV absorption lines, although the extrapolation of the pressure profiles may cause some biases in this comparison. By comparing the position-velocity diagrams of the optical and CO lines, we also find the dynamics of the two gas phases are consistent with each other, with no evidence of a global inflow/outflow and a maximum rotation velocity of $\sim150\rm~km~s^{-1}$.

astro-ph.GA↗

arXiv2024

SLSM : An Efficient Strategy for Lazy Schema Migration on Shared-Nothing Databases

By introducing intermediate states for metadata changes and ensuring that at most two versions of metadata exist in the cluster at the same time, shared-nothing databases are capable of making online, asynchronous schema changes. However, this method leads to delays in the deployment of new schemas since it requires waiting for massive data backfill. To shorten the service vacuum period before the new schema is available, this paper proposes a strategy named SLSM for zero-downtime schema migration on shared-nothing databases. Based on the lazy migration of stand-alone databases, SLSM keeps the old and new schemas with the same data distribution, reducing the node communication overhead of executing migration transactions for shared-nothing databases. Further, SLSM combines migration transactions with user transactions by extending the distributed execution plan to allow the data involved in migration transactions to directly serve user transactions, greatly reducing the waiting time of user transactions. Experiments demonstrate that our strategy can greatly reduce the latency of user transactions and improve the efficiency of data migration compared to existing schemes.

cs.DB↗

arXiv2024

Crowdsourcing Fraud Detection over Heterogeneous Temporal MMMA Graph

The rise of the click farm business using Multi-purpose Messaging Mobile Apps (MMMAs) tempts cybercriminals to perpetrate crowdsourcing frauds that cause financial losses to click farm workers. In this paper, we propose a novel contrastive multi-view learning method named CMT for crowdsourcing fraud detection over the heterogeneous temporal graph (HTG) of MMMA. CMT captures both heterogeneity and dynamics of HTG and generates high-quality representations for crowdsourcing fraud detection in a self-supervised manner. We deploy CMT to detect crowdsourcing frauds on an industry-size HTG of a representative MMMA WeChat and it significantly outperforms other methods. CMT also shows promising results for fraud detection on a large-scale public financial HTG, indicating that it can be applied in other graph anomaly detection tasks. We provide our implementation at https://github.com/KDEGroup/CMT.

cs.SI↗

arXiv2024

Novel_Authentication_Protocols_Tailored_for_Ambient_IoT_Devices_in_3GPP_5G_Networks

AIoT devices have attracted significant attention within the 3GPP organization. These devices, distinguished from conventional IoT devices, do not rely on additional batteries or have extremely small battery capacities, offering features such as low cost, easy deployment, and maintenance-free operation. Authentication and secure transmission are fundamental security requirements for AIoT devices. However, existing standard security mechanisms are not specifically designed for AIoT devices due to their complex key hierarchies and multi-round interactions, making them unsuitable. Besides, AIoT devices would have more various communication topologies. Therefore, we propose dedicated ultra-lightweight access authentication protocols based on various technologies and algorithms to serve as a forward-looking reference for future research and standardization. Analysis and simulation experiments using chips that closely resemble real AIoT devices, demonstrate that the existing standard protocols are indeed not suitable for such devices, and our protocols outperform existing standard protocols in terms of computational time and energy consumption. After the successful execution of proposed protocols, they can achieve secure transmission of application data, striking a balance between performance and security.

cs.CR↗

arXiv2024

Machine Learning-Based Identification of Contaminated Images in Light Curves Data Preprocessing

Attitude is one of the crucial parameters for space objects and plays a vital role in collision prediction and debris removal. Analyzing light curves to determine attitude is the most commonly used method. In photometric observations, outliers may exist in the obtained light curves due to various reasons. Therefore, preprocessing is required to remove these outliers to obtain high quality light curves. Through statistical analysis, the reasons leading to outliers can be categorized into two main types: first, the brightness of the object significantly increases due to the passage of a star nearby, referred to as "stellar contamination," and second, the brightness markedly decreases due to cloudy cover, referred to as "cloudy contamination." Traditional approach of manually inspecting images for contamination is time-consuming and labor-intensive. However, We propose the utilization of machine learning methods as a substitute. Convolutional Neural Networks (CNN) and Support Vector Machines (SVM) are employed to identify cases of stellar contamination and cloudy contamination, achieving F1 scores of 1.00 and 0.98 on test set, respectively. We also explored other machine learning methods such as Residual Network-18 (ResNet-18) and Light Gradient Boosting Machine (lightGBM), then conducted comparative analyses of the results.

astro-ph.IM↗

arXiv2024

Modeling the inner part of the jet in M87: Confronting jet morphology with theory

The formation of jets in black hole accretion systems is a long-standing problem. It has been proposed that a jet can be formed by extracting the rotation energy of the black hole ("BZ-jet") or the accretion flow ("disk-jet"). While both models can produce collimated relativistic outflows, neither has successfully explained the observed jet morphology. By employing general relativistic magnetohydrodynamic simulations, and considering nonthermal electrons accelerated by magnetic reconnection that is likely driven by magnetic eruption in the underlying accretion flow, we obtain images by radiative transfer calculations and compared them to millimeter observations of the jet in M87. We find that the BZ-jet originating from a magnetically arrested disk around a high-spin black hole can well reproduce the jet morphology, including its width and limb-brightening feature.

astro-ph.HE↗

arXiv2024

Towards Lossless Dataset Distillation via Difficulty-Aligned Trajectory Matching

The ultimate goal of Dataset Distillation is to synthesize a small synthetic dataset such that a model trained on this synthetic set will perform equally well as a model trained on the full, real dataset. Until now, no method of Dataset Distillation has reached this completely lossless goal, in part due to the fact that previous methods only remain effective when the total number of synthetic samples is extremely small. Since only so much information can be contained in such a small number of samples, it seems that to achieve truly loss dataset distillation, we must develop a distillation method that remains effective as the size of the synthetic dataset grows. In this work, we present such an algorithm and elucidate why existing methods fail to generate larger, high-quality synthetic sets. Current state-of-the-art methods rely on trajectory-matching, or optimizing the synthetic data to induce similar long-term training dynamics as the real data. We empirically find that the training stage of the trajectories we choose to match (i.e., early or late) greatly affects the effectiveness of the distilled dataset. Specifically, early trajectories (where the teacher network learns easy patterns) work well for a low-cardinality synthetic set since there are fewer examples wherein to distribute the necessary information. Conversely, late trajectories (where the teacher network learns hard patterns) provide better signals for larger synthetic sets since there are now enough samples to represent the necessary complex patterns. Based on our findings, we propose to align the difficulty of the generated patterns with the size of the synthetic dataset. In doing so, we successfully scale trajectory matching-based methods to larger synthetic datasets, achieving lossless dataset distillation for the very first time. Code and distilled datasets are available at https://gzyaftermath.github.io/DATM.

cs.CV↗

arXiv2024

Evolution and distribution of superbubbles in simulated Milky Way-like galaxies

Stellar feedback plays a crucial role in regulating baryon cycles of a galactic ecosystem, and may manifest itself in the formation of superbubbles in the interstellar medium. In this work, we used a set of high-resolution simulations to systematically study the properties and evolution of superbubbles in galactic environments. The simulations were based on the SMUGGLE galaxy formation framework using the hydrodynamical moving-mesh code Arepo, reaching a spatial resolution of $\sim 4 \, \rm pc$ and mass resolution of $\sim 10^3 \, \rm M_{\odot}$. We identified superbubbles and tracked their time evolution using the parent stellar associations within the bubbles. The X-ray luminosity-size distribution of superbubbles in the fiducial run is largely consistent with the observations of nearby galaxies. The size of superbubbles shows a double-peaked distribution, with the peaks attributed to early feedback (radiative and stellar wind feedback) and supernova feedback. The early feedback tends to suppress the subsequent supernova feedback, and it is strongly influenced by star formation efficiency, which regulates the environmental density. Our results show that the volume filling factor of hot gas ($T > 10^{5.5} ~\mathrm{K}$) is about $12 \%$ averaged over a region of 4 kpc in height and 20 kpc in radius centered on the disk of the galaxy. Overall, the properties of superbubbles are sensitive to the choice of subgrid galaxy formation models and can, therefore, be used to constrain these models.

astro-ph.GA↗

arXiv2024

High precision proton beam monitor system concept design on CSNS based on SiC

A high precision beam monitor system based on silicon carbide PIN sensor is designed for China Spallation Neutron Source 1.6 GeV proton beam to monitor the proton beam fluence.The concept design of the beam monitor system is finished together with front-end electronics with silicon carbide PIN sensors, readout system and mechanical system.Several tests are performed to study the performance of each component of the system.The charge collection of the SiC PIN sensors after proton radiation is studied with 80 MeV proton beam for continuous running. Research on the performance of the front-end electronics and readout system is finished for better data acquisition.The uncertainty of proton beam fluence is below 1% in the beam monitor system.

physics.acc-ph↗

arXiv2024

MMAPS: End-to-End Multi-Grained Multi-Modal Attribute-Aware Product Summarization

Given the long textual product information and the product image, Multi-modal Product Summarization (MPS) aims to increase customers' desire to purchase by highlighting product characteristics with a short textual summary. Existing MPS methods can produce promising results. Nevertheless, they still 1) lack end-to-end product summarization, 2) lack multi-grained multi-modal modeling, and 3) lack multi-modal attribute modeling. To improve MPS, we propose an end-to-end multi-grained multi-modal attribute-aware product summarization method (MMAPS) for generating high-quality product summaries in e-commerce. MMAPS jointly models product attributes and generates product summaries. We design several multi-grained multi-modal tasks to better guide the multi-modal learning of MMAPS. Furthermore, we model product attributes based on both text and image modalities so that multi-modal product characteristics can be manifested in the generated summaries. Extensive experiments on a real large-scale Chinese e-commence dataset demonstrate that our model outperforms state-of-the-art product summarization methods w.r.t. several summarization metrics. Our code is publicly available at: https://github.com/KDEGroup/MMAPS.

cs.MM↗

arXiv2024

The nature of diffuse ionised gas in star-forming galaxies

We present an analysis of the diffuse ionised gas (DIG) in a high-resolution simulation of an isolated Milky Way-like galaxy, incorporating on-the-fly radiative transfer and non-equilibrium thermochemistry. We utilise the Monte-Carlo radiative transfer code COLT to self-consistently obtain ionisation states and line emission in post-processing. We find a clear bimodal distribution in the electron densities of ionised gas ($n_{\rm e}$), allowing us to define a threshold of $n_{\rm e}=10\,\mathrm{cm}^{-3}$ to differentiate DIG from HII regions. The DIG is primarily ionised by stars aged 5-25 Myr, which become exposed directly to low-density gas after HII regions have been cleared. Leakage from recently formed stars ($<5$ Myr) is only moderately important for DIG ionisation. We forward model local observations and validate our simulated DIG against observed line ratios in [SII]/H$α$, [NII]/H$α$, [OI]/H$α$, and [OIII]/H$β$ against $Σ_{\rm Hα}$. The mock observations not only reproduce observed correlations, but also demonstrate that such trends are related to an increasing temperature and hardening ionising radiation field with decreasing $n_{\rm e}$. The hardening of radiation within the DIG is caused by the gradual transition of the dominant ionising source with decreasing $n_{\rm e}$ from 0 Myr to 25 Myr stars, which have progressively harder intrinsic ionising spectra primarily due to the extended Wolf-Rayet phase caused by binary interactions. Consequently, the DIG line ratio trends can be attributed to ongoing star formation, rather than secondary ionisation sources, and therefore present a potent test for stellar feedback and stellar population models.

astro-ph.GA↗

arXiv2024

Bridging the Sim-to-Real Gap with Dynamic Compliance Tuning for Industrial Insertion

Contact-rich manipulation tasks often exhibit a large sim-to-real gap. For instance, industrial assembly tasks frequently involve tight insertions where the clearance is less than 0.1 mm and can even be negative when dealing with a deformable receptacle. This narrow clearance leads to complex contact dynamics that are difficult to model accurately in simulation, making it challenging to transfer simulation-learned policies to real-world robots. In this paper, we propose a novel framework for robustly learning manipulation skills for real-world tasks using simulated data only. Our framework consists of two main components: the "Force Planner" and the "Gain Tuner". The Force Planner plans both the robot motion and desired contact force, while the Gain Tuner dynamically adjusts the compliance control gains to track the desired contact force during task execution. The key insight is that by dynamically adjusting the robot's compliance control gains during task execution, we can modulate contact force in the new environment, thereby generating trajectories similar to those trained in simulation and narrowing the sim-to-real gap. Experimental results show that our method, trained in simulation on a generic square peg-and-hole task, can generalize to a variety of real-world insertion tasks involving narrow and negative clearances, all without requiring any fine-tuning. Videos are available at https://dynamic-compliance.github.io.

cs.RO↗

arXiv2024

ASAP: Automated Sequence Planning for Complex Robotic Assembly with Physical Feasibility

The automated assembly of complex products requires a system that can automatically plan a physically feasible sequence of actions for assembling many parts together. In this paper, we present ASAP, a physics-based planning approach for automatically generating such a sequence for general-shaped assemblies. ASAP accounts for gravity to design a sequence where each sub-assembly is physically stable with a limited number of parts being held and a support surface. We apply efficient tree search algorithms to reduce the combinatorial complexity of determining such an assembly sequence. The search can be guided by either geometric heuristics or graph neural networks trained on data with simulation labels. Finally, we show the superior performance of ASAP at generating physically realistic assembly sequence plans on a large dataset of hundreds of complex product assemblies. We further demonstrate the applicability of ASAP on both simulation and real-world robotic setups. Project website: asap.csail.mit.edu

cs.RO↗

arXiv2024

Code Search Debiasing:Improve Search Results beyond Overall Ranking Performance

Code search engine is an essential tool in software development. Many code search methods have sprung up, focusing on the overall ranking performance of code search. In this paper, we study code search from another perspective by analyzing the bias of code search models. Biased code search engines provide poor user experience, even though they show promising overall performance. Due to different development conventions (e.g., prefer long queries or abbreviations), some programmers will find the engine useful, while others may find it hard to get desirable search results. To mitigate biases, we develop a general debiasing framework that employs reranking to calibrate search results. It can be easily plugged into existing engines and handle new code search biases discovered in the future. Experiments show that our framework can effectively reduce biases. Meanwhile, the overall ranking performance of code search gets improved after debiasing.

cs.CL↗

arXiv2024

The White-light Emissions in Two X-class Flares Observed by ASO-S and CHASE

The white-light continuum emissions in solar flares (i.e., white-light flares) are usually observed on the solar disk but, in a few cases, off the limb. Here we present on-disk as well as off-limb continuum emissions at 3600 Å (in the Balmer continuum) in an X2.1 flare (SOL2023-03-03T17:52) and an X1.5 flare (SOL2023-08-07T20:46), respectively, observed by the White-light Solar Telescope (WST) on the Advanced Space-based Solar Observatory (ASO-S). These continuum emissions are seen at the ribbons for the X2.1 flare and on loops during the X1.5 event, in which the latter also appears in the decay phase. These emissions also show up in the pseudo-continuum images at Fe I λ6173 from the Helioseismic and Magnetic Imager (HMI) on the Solar Dynamics Observatory (SDO). In addition, the ribbon sources in the X2.1 flare exhibit significant enhancements in the Fe I line at 6569.2 Å and the nearby continuum observed by the Chinese Hα Solar Explorer (CHASE). It is found that the on-disk continuum emissions in the X2.1 flare are related to a nonthermal electron-beam heating either directly or indirectly, while the off-limb emissions in the X1.5 flare are associated with thermal plasma cooling or due to Thomson scattering. These comprehensive continuum observations can provide good constraints on flare energy deposition models, which helps well understand the physical mechanism of white-light flares.

astro-ph.SR↗

arXiv2024

Modeling the inner part of M87 jet: confronting jet morphology with theory

The formation of jets in black hole accretion systems is a long-standing problem. It has been proposed that a jet can be formed by extracting the rotation energy of the black hole ("BZ-jet") or the accretion flow ("disk-jet"). While both models can produce collimated relativistic outflows, neither has successfully explained the observed jet morphology. In this paper, by employing general relativistic magnetohydrodynamic simulations, and considering nonthermal electrons accelerated by magnetic reconnection driven by kink instability of the jet, we have obtained images by radiative transfer calculations and compared them to millimeter observations of the jet in M87. We find that the BZ-jet originated from a magnetically arrested disk around a high-spin black hole can well reproduce the jet morphology, including its width and limb-brightening feature.

astro-ph.HE↗