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Junfeng Wang

Publications and source records attributed to Junfeng Wang.

At least 91 records · Page 5Linked to original sources

Explosive percolation in finite dimensions

Explosive percolation (EP) has received significant research attention due to its rich and anomalous phenomena near criticality. In our recent study [Phys. Rev. Lett. 130, 147101 (2023)], we demonstrated that the correct critical behaviors of EP in infinite dimensions (complete graph) can be accurately extracted using the event-based method, with finite-size scaling behaviors still described by the standard finite-size scaling theory. We perform an extensive simulation of EPs on hypercubic lattices ranging from dimensions $d=2$ to $6$, and find that the critical behaviors consistently obey the standard finite-size scaling theory. Consequently, we obtain a high-precision determination of the percolation thresholds and critical exponents, revealing that EPs governed by the product and sum rules belong to different universality classes. Remarkably, despite the mean of the dynamic pseudocritical point $\mathcal{T}_L$ deviating from the infinite-lattice criticality by a distance determined by the $d$-dependent correlation-length exponent, $\mathcal{T}_L$ follows a normal (Gaussian) distribution across all dimensions, with a standard deviation proportional to $1/\sqrt{V}$, where $V$ denotes the system volume. A theoretical argument associated with the central-limit theorem is further proposed to understand the probability distribution of $\mathcal{T}_L$. These findings offer a comprehensive understanding of critical behaviors in EPs across various dimensions, revealing a different dimension-dependence compared to standard bond percolation.

cond-mat.stat-mech↗

Environmental effects as a key factor in shaping star-forming S0 galaxies

The origins of lenticular galaxies (S0s) can be classified into two main categories: ``minor mergers" in low-density environments (LDEs) and ``faded spirals" in high-density environments (HDEs). The transitional phase in the evolution of S0s, namely, star-forming lenticular galaxies (SFS0s), can serve as an important probe for analyzing the complex processes involved in the transformation between different galaxy types and the quenching of star formation (SF). We attempt to find the impact of different environments on the global properties and spatially resolved quantities of SFS0s. We selected 71 SFS0s from the SDSS-IV MaNGA Survey, comprising 23 SFS0s in HDEs (SFS0s$\_$HE) and 48 SFS0s in LDEs (SFS0s$\_$LE). We examined the effects of the environment, by studying the global properties, concentration index, and radial profiles of the derived quantities. The varied environments of SFS0s do not lead to any significant difference in global properties (e.g., S$\acute{\rm e}$rsic index). By calculating $CI_{\rm H_α/cont}$, we observe that different environments may cause varying concentrations of SF. Specifically, SFS0s$\_$LE, affected by external gas mergers or inflow, exhibit a more centrally concentrated SF (i.e., larger $CI_{\rm H_α/cont}$). This trend is further supported by $CI_{\rm SFR, H_α}$, which only considers the gas disk of the galaxy. This observation is aligned with the observed shrinking of gas disks in galaxies affected by ram-pressure stripping in HDEs. Furthermore, their $Σ_{\rm SFR}$ or resolved sSFR are comparable. On average, SFS0s$\_$LE display significantly higher values for both quantities. Finally, the observed D$_{\rm n}4000$ and gas-phase metallicity gradient correspond well to their assumed origins. However, we did not find a significantly lower gas-phase metallicity in SFS0s$\_$LE. Abridged

astro-ph.GA↗

Ionized and cold gas components in low surface brightness galaxy AGC 102004

We present the integral field spectroscopic observations of ionized gas (H$α$ and [{\ion{N}{II}}]) using the PCWI, along with deep CO(2-1) observations by the $^\backprime\bar{\rm U}^\backprime\bar{\rm u}$ receiver on JCMT for AGC 102004. The velocity field of H$α$ shows an anomalous distribution in the North-Western (NW) disk. The H$α$ spectrum is well-fitted by two Gaussian components, and the weak Gaussian component is dominated by the anomalous H$α$ in the NW disk. The Gaussian fit center of H$α$ emission is offset by +24.2 km s$^{-1}$ from the systemic velocity obtained from the HI emission. We derive the gas-phase metallicity, 12+log(O/H), using [{\ion{N}{II}}]$λ$6583/H$α$ ratio as a proxy. The mean value of 12+log(O/H) is 8.30 $\pm$ 0.19 over the whole galaxy. The metallicity in the outer disk is lower than the detection limit of 7.72, indicating the metallicity gradient exists in AGC 102004. We speculate a minor/mini-merger event could have happened to the NW disk. CO(2-1) emission has non-detection in AGC 102004, reaching a noise level of 0.33 mK smoothed to 30 km s$^{-1}$. The upper limit of molecular gas mass in AGC 102004 is 2.1 $\times$ 10$^7$ M$\odot$ with X$_{\rm CO}$ = 3.02$\times$10$^{20}$ cm$^{-2}$ (K km s$^{-1}$)$^{-1}$. The M$_{\rm H_2}$/M$^{\rm corr}_{\rm HI}$ of AGC 102004 is lower than 0.0037 and lower than that of normal galaxies.

astro-ph.GA↗

VisLingInstruct: Elevating Zero-Shot Learning in Multi-Modal Language Models with Autonomous Instruction Optimization

This paper presents VisLingInstruct, a novel approach to advancing Multi-Modal Language Models (MMLMs) in zero-shot learning. Current MMLMs show impressive zero-shot abilities in multi-modal tasks, but their performance depends heavily on the quality of instructions. VisLingInstruct tackles this by autonomously evaluating and optimizing instructional texts through In-Context Learning, improving the synergy between visual perception and linguistic expression in MMLMs. Alongside this instructional advancement, we have also optimized the visual feature extraction modules in MMLMs, further augmenting their responsiveness to textual content. Our comprehensive experiments on MMLMs, based on FlanT5 and Vicuna, show that VisLingInstruct significantly improves zero-shot performance in visual multi-modal tasks. Notably, it achieves a 13.1% and 9% increase in accuracy over the prior state-of-the-art on the TextVQA and HatefulMemes datasets. Our main code is available at https://github.com/Zhudongsheng75/VisLingInstruct.

cs.AI↗

Serendipitous Catch of a Giant Jellyfish: an Ionized Nebula around 3C 275.1 with 170 kpc Long Tails

3C 275.1 is a blue quasar at $z=0.55522$, hosting powerful outflows and residing in a complex environment. We present a serendipitously detected giant nebula surrounding 3C 275.1, which shows morphological features resembling those of objects known as "jellyfish galaxy", with extremely long tails of ionized gas extending to 170 kpc in projection. We analyze its optical spectra taken by the MUSE on the VLT. The brighter part of this giant nebula exceeds 100 kpc, whose rotation curve does not flatten out, is very different from those of normal spiral galaxies. This system shares some characteristics common to those formed via ram pressure stripping (RPS), yet its long narrow tails and higher ionization are unusual compared to known tails in jellyfish galaxies, not fully consistent with a simple RPS scenario. Our photoionization simulation and the inferred short recombination timescale both suggest that besides the quasar 3C 275.1, an extra source of ionization is necessary to keep the gas ionized at such distance from the nucleus, which could be related to RPS, tidal interaction or AGN outflow, providing new evidence of active dynamical interaction of a galaxy with the intracluster medium.

astro-ph.GA↗

Spatially resolved analysis of Stellar Populations in NGC 2992: Impact of AGN feedback

In NGC 2992, a galaxy-scale ionized gas outflow driven by AGN has long been recognized, yet its impact on the host galaxy has remained elusive. In this paper, we utilize data from the archival Very Large Telescope (VLT)/MUSE to present a spatially resolved analysis of stellar populations in this galaxy. Two different stellar population templates are employed to fit the stellar continuum, allowing us to determine the light-weighted stellar age, metallicity, the fraction of the young stellar population (age $<100$ Myr, $P_{\rm Y}$), and the average age and metallicity of $P_{\rm Y}$. Our results reveal the presence of a very young stellar population ($\leq40$ Myr) within the dust lane and nearly along the galaxy's major axis. The light-weighted stellar age and the fraction of $P_{\rm Y}$ show negative trends along the major and minor axes. The average age and metallicity of $P_{\rm Y}$ present positive trends with increasing distance, except along the northern direction of the major axis. Within the circumnuclear region ($<1$ kpc), the distribution of the young stellar population is spatially anti-correlated with the AGN outflow cone. The highest fraction of $P_{\rm Y}$ is observed at the outskirts of the nuclear radio bubble in the northern region near the nucleus. Considering the coupling efficiency and timescales, we propose that the AGN outflow in this galaxy may exert both negative and positive feedback on its host. Additionally, the star formation and the AGN activities could be attributed to the interaction between NGC 2992 and NGC 2993.

astro-ph.GA↗

Sub-kiloparsec scaling relations between hot gas, dense gas and star formation rate in five nearby star-forming galaxies

Based on the newly acquired dense gas observations from the JCMT MALATANG survey and X-ray data from Chandra, we explore the correlation between hot gas and HCN $J=4 \rightarrow 3$, HCO$^+\ J=4 \rightarrow 3$ emission for the first time at sub-kiloparsec scale of five nearby star-forming galaxies, namely M82, M83, IC 342, NGC 253, and NGC 6946. We find that both HCN $J=4 \rightarrow 3$ and HCO$^+\ J=4 \rightarrow 3$ line luminosity show a statistically significant correlation with the 0.5${-}$2 keV X-ray emission of the diffuse hot gas ($L_{\rm 0.5 - 2\,keV}^{\rm gas}$). The Bayesian regression analysis gives the best fit of ${\rm log}(L_{\rm 0.5-2\,keV}^{\rm gas} /{\rm erg\,s^{-1}})=2.39\,{\rm log}(L'_{\rm HCN(4-3)} /{\rm K\,km\,s^{-1}\,pc^{2}})+24.83$ and ${\rm log}(L_{\rm 0.5-2\,keV}^{\rm gas} /{\rm erg\,s^{-1}})=2.48\,{\rm log}(L'_{\rm HCO^{+}(4-3)} /{\rm K\,km\,s^{-1}\,pc^{2}})+23.84$, with dispersion of $\thicksim$0.69 dex and 0.54 dex, respectively. At the sub-kiloparsec scale, we find that the power-law index of the $L_{\rm 0.5 - 2\,keV}^{\rm gas}$ ${-}$ star formation rate (SFR) relation is ${\rm log}(L_{\rm 0.5-2\,keV}^{\rm gas} /{\rm erg\,s^{-1}})=1.80\,{\rm log} ({\rm SFR} /M_\odot\,{\rm yr}^{-1})+39.16$, deviated from previous linear relations at global scale. This implies that the global property of hot gas significantly differs from individual resolved regions, which is influenced by the local physical conditions close to the sites of star formation.

astro-ph.GA↗

1/3 and other magnetization plateaus in a quasi-one-dimensional Ising magnet $\mathbf{TbTi_3Bi_4}$ with zigzag spin chain

We report the magnetic properties of newly synthesized, single crystals of $\mathrm{TbTi_3Bi_4}$ whose crystal structure is highlighted by the stacking of terbium-based zigzag chains and titanium-based kagome lattices. This compound demonstrates extreme easy-axis magnetic anisotropy due to the crystalline-electric-field effect which aligns the $\mathrm{Tb^{3+}}$ moments along the zigzag chain direction. As the result of the strong single-ion anisotropy and multiple magnetic interactions, $\mathrm{TbTi_3Bi_4}$ behaves as a quasi-one-dimensional Ising magnet with a remarkable antiferromagnetic ordering at $T_\mathrm{N}$ = 20.4 K. When a magnetic field is applied along the direction of the zigzag chain, multiple meta-magnetic transitions occur between 1/3 and other magnetization plateaus. We have created a field-temperature phase diagram and mapped out the complex magnetic structures resulting from frustration.

cond-mat.str-el↗

Discovery of a Magnetic Topological Semimetal Eu$_3$In$_2$As$_4$ with a Single Pair of Weyl Points

Magnetic Weyl semimetal (MWS) is a unique topological state with open surface Fermi arc states and other exotic transport phenomena. However, most reported MWSs show multiple pairs of Weyl points and complicated Fermi surfaces, which increases the difficulty of the investigation into the intrinsic chiral transport property. In this wor, we successfully synthesized a soft magnetic Weyl semimetal Eu$_3$In$_2$As$_4$ with a single pair of Weyl points under magnetic fields. The Shubnikov de Haas (SdH) oscillation with a single frequency, as well as a linear hall resistance with the same carrier density, is observed up to 50 Tesla, indicating a single pair of Weyl points around the Fermi level with a massless fermion ($m^* = 0.121 m_0$, $π$ Berry phase). Such a single pair of Weyl points is further confirmed by the density functional theory calculations. The magnetic ordering and band topology can be easily tuned by the external magnetic field. The field-induced MWS Eu$_3$In$_2$As$_4$ with a single pair of Weyl points is a good platform to detect chiral transport properties, including possible quantum anomalous Hall effect.

cond-mat.mes-hall↗

A reverberation mapping study of a highly variable AGN 6dFGS gJ022550.0-060145

We use LCOGT observations (MJD $59434-59600$) with a total exposure time of $\simeq 50$ hours and a median cadence of $0.5$ days to measure the inter-band time delays (with respect to $u$) in the $g$, $r$, and $i$ continua of a highly variable AGN, 6dFGS gJ022550.0-060145. We also calculate the expected time delays of the X-ray reprocessing of a static Shakura \& Sunyaev disk (SSD) according to the sources' luminosity and virial black-hole mass; the two parameters are measured from the optical spectrum of our spectroscopic observation via the Lijiang \SI{2.4}{\meter} telescope. It is found that the ratio of the measured time delays to the predicted ones is $2.6_{-1.3}^{+1.3}$. With optical light curves (MJD $53650-59880$) from our new LCOGT and archival ZTF, Pan-SATRRS, CSS, and ATLAS observations, and infrared (IR) WISE data (MJD $55214-59055$), we also measured time delays between WISE $W1$/$W2$ and the optical emission. $W1$ and $W2$ have time delays (with respect to V), $9.6^{+2.9}_{-1.6}\times 10^2$ days and $1.18^{+0.13}_{-0.10}\times 10^3$ days in the rest-frame, respectively; hence, the dusty torus of 6dFGS gJ022550.0-060145 should be compact. The time delays of $W1$ and $W2$ bands are higher than the dusty torus size-luminosity relationship of~\cite{Lyu2019}. By comparing the IR and optical variability amplitude, we find that the dust covering factors of $W1$ and $W2$ emission regions are 0.7 and 0.6, respectively. Future broad emission-line reverberation mapping of this target and the results of this work enable us to determine the sizes of the AGN main components simultaneously.

astro-ph.HE↗

A Unified Model for Multi-epoch Neutrino Events and Broadband Spectral Energy Distribution of $\rm TXS~0506+056$

The blazar $TXS~0506+056$ has been proposed as a high-energy neutrino emitter. However, it has been shown that the standard one-zone model cannot produce sufficiently high neutrino flux due to constraints from the X-ray data, implying more complex properties of the radiation zones in the blazar than that described by the standard one-zone model. In this work we investigate multi-epoch high-energy muon neutrino events associated with the blazar $TXS~0506+056$ occured in 2014-2015, 2017-2018, 2021-2022 and 2022-2023, respectively. We applied the so-called ``stochastic dissipation model'' to account for the neutrino-blazar associations detected in the four epochs simultaenously. This model describes a scenario in which the emission of the blazar arise from the superimposition of two components: a persistent component related to the quasi-stable state of the blazar and a transient component responsible for the sudden enhancement of the blazar's flux, either in electromagnetic radiation or in neutrino emission. The latter component could form at a random distance along the jet by a strong energy dissipation event. Under such assumption, the multi-epoch broadband spectral energy distribution (SED) can be well explained and the expected number of high-energy neutrino events is statistically realistic. The expected number of neutrino events in half-year is around 8.2, 0.07, 0.73 and 0.41, corresponding to the epoch in 2014-2015, 2017-2018, 2021-2022 and 2022-2023, respectively. Hence, our model self-consistently explains the episodic neutrino emission from $TXS~0506+056$.

astro-ph.HE↗

Deep Chandra Observation of the Remarkable Ionization Cones of NGC 5252

Seyfert galaxy NGC 5252 harbors enormously extended ionization cones, which have been previously detected in the optical and X-ray band, offering a unique opportunity to investigate the interaction between the central active galactic nucleus (AGN) and the surrounding gas in the AGN host galaxy. We present deep Chandra imaging spectroscopy of NGC 5252 with a total exposure time of 230 ks. The morphology in the soft X-rays shows resolved extended structure from nucleus to a large radial distance, and for the first time we detect the outermost X-ray arc at $\sim$20 kpc. The X-ray cone mostly follows the direction of the optical ionization cones in the southeast and northwest direction, about 20 degrees misaligned with the major axis of the galactic disk of NGC 5252. Fitting the spectra extracted from radial sectors with photoionization models supports that extended emission is mainly photoionized by the central AGN. We also examine the variation of the photoionization parameter along the radial extension, and infer a decreasing ionizing continuum of the central engine by a factor of $\sim$50 over the past 64000 years. These findings are consistent with previous suggestion that NGC 5252 resembles a quasar relic with a $M\sim 10^9 M_{\odot}$ supermassive black hole, which went through a minor merger event and switched to a low accretion rate state.

astro-ph.HE↗

LLMRec: Large Language Models with Graph Augmentation for Recommendation

The problem of data sparsity has long been a challenge in recommendation systems, and previous studies have attempted to address this issue by incorporating side information. However, this approach often introduces side effects such as noise, availability issues, and low data quality, which in turn hinder the accurate modeling of user preferences and adversely impact recommendation performance. In light of the recent advancements in large language models (LLMs), which possess extensive knowledge bases and strong reasoning capabilities, we propose a novel framework called LLMRec that enhances recommender systems by employing three simple yet effective LLM-based graph augmentation strategies. Our approach leverages the rich content available within online platforms (e.g., Netflix, MovieLens) to augment the interaction graph in three ways: (i) reinforcing user-item interaction egde, (ii) enhancing the understanding of item node attributes, and (iii) conducting user node profiling, intuitively from the natural language perspective. By employing these strategies, we address the challenges posed by sparse implicit feedback and low-quality side information in recommenders. Besides, to ensure the quality of the augmentation, we develop a denoised data robustification mechanism that includes techniques of noisy implicit feedback pruning and MAE-based feature enhancement that help refine the augmented data and improve its reliability. Furthermore, we provide theoretical analysis to support the effectiveness of LLMRec and clarify the benefits of our method in facilitating model optimization. Experimental results on benchmark datasets demonstrate the superiority of our LLM-based augmentation approach over state-of-the-art techniques. To ensure reproducibility, we have made our code and augmented data publicly available at: https://github.com/HKUDS/LLMRec.git

cs.IR↗

Text-Video Retrieval via Variational Multi-Modal Hypergraph Networks

Text-video retrieval is a challenging task that aims to identify relevant videos given textual queries. Compared to conventional textual retrieval, the main obstacle for text-video retrieval is the semantic gap between the textual nature of queries and the visual richness of video content. Previous works primarily focus on aligning the query and the video by finely aggregating word-frame matching signals. Inspired by the human cognitive process of modularly judging the relevance between text and video, the judgment needs high-order matching signal due to the consecutive and complex nature of video contents. In this paper, we propose chunk-level text-video matching, where the query chunks are extracted to describe a specific retrieval unit, and the video chunks are segmented into distinct clips from videos. We formulate the chunk-level matching as n-ary correlations modeling between words of the query and frames of the video and introduce a multi-modal hypergraph for n-ary correlation modeling. By representing textual units and video frames as nodes and using hyperedges to depict their relationships, a multi-modal hypergraph is constructed. In this way, the query and the video can be aligned in a high-order semantic space. In addition, to enhance the model's generalization ability, the extracted features are fed into a variational inference component for computation, obtaining the variational representation under the Gaussian distribution. The incorporation of hypergraphs and variational inference allows our model to capture complex, n-ary interactions among textual and visual contents. Experimental results demonstrate that our proposed method achieves state-of-the-art performance on the text-video retrieval task.

cs.CV↗

Agent4Ranking: Semantic Robust Ranking via Personalized Query Rewriting Using Multi-agent LLM

Search engines are crucial as they provide an efficient and easy way to access vast amounts of information on the internet for diverse information needs. User queries, even with a specific need, can differ significantly. Prior research has explored the resilience of ranking models against typical query variations like paraphrasing, misspellings, and order changes. Yet, these works overlook how diverse demographics uniquely formulate identical queries. For instance, older individuals tend to construct queries more naturally and in varied order compared to other groups. This demographic diversity necessitates enhancing the adaptability of ranking models to diverse query formulations. To this end, in this paper, we propose a framework that integrates a novel rewriting pipeline that rewrites queries from various demographic perspectives and a novel framework to enhance ranking robustness. To be specific, we use Chain of Thought (CoT) technology to utilize Large Language Models (LLMs) as agents to emulate various demographic profiles, then use them for efficient query rewriting, and we innovate a robust Multi-gate Mixture of Experts (MMoE) architecture coupled with a hybrid loss function, collectively strengthening the ranking models' robustness. Our extensive experimentation on both public and industrial datasets assesses the efficacy of our query rewriting approach and the enhanced accuracy and robustness of the ranking model. The findings highlight the sophistication and effectiveness of our proposed model.

cs.IR↗

A symbolic-arithmetic for teaching double-black node removal in red-black trees

A red-black (RB) tree is a data structure with red and black nodes coloration. The red and black color of nodes make up the principal component for balancing a RB tree. A balanced tree has an equal number of black nodes on any simple path. But when a black leaf node is deleted, a double-black (DB) node is formed, thus, causing a reduction in black heights and the tree becomes unbalanced. Rebalancing a RB tree with a DB node is a fairly complex process. Teaching and learning the removal of DB nodes is also challenging. This paper introduces a simplified novel method which is a symbolic-algebraic arithmetic procedure for the removal of DB nodes and the rebalancing of black heights in RB trees. This simplified approach has enhanced student learning of the DB node removal in RB trees. Feedback from students showed the learnability, workability and acceptance of the symbolic-algebraic method in balancing RB trees after a delete operation.

cs.DS↗

Risk-based decision making: estimands for sequential prediction under interventions

Prediction models are used amongst others to inform medical decisions on interventions. Typically, individuals with high risks of adverse outcomes are advised to undergo an intervention while those at low risk are advised to refrain from it. Standard prediction models do not always provide risks that are relevant to inform such decisions: e.g., an individual may be estimated to be at low risk because similar individuals in the past received an intervention which lowered their risk. Therefore, prediction models supporting decisions should target risks belonging to defined intervention strategies. Previous works on prediction under interventions assumed that the prediction model was used only at one time point to make an intervention decision. In clinical practice, intervention decisions are rarely made only once: they might be repeated, deferred and re-evaluated. This requires estimated risks under interventions that can be reconsidered at several potential decision moments. In the current work, we highlight key considerations for formulating estimands in sequential prediction under interventions that can inform such intervention decisions. We illustrate these considerations by giving examples of estimands for a case study about choosing between vaginal delivery and cesarean section for women giving birth. Our formalization of prediction tasks in a sequential, causal, and estimand context provides guidance for future studies to ensure that the right question is answered and appropriate causal estimation approaches are chosen to develop sequential prediction models that can inform intervention decisions.

stat.ME↗

The Clumpy Structure Of Five Star-bursting Dwarf Galaxies In The MaNGA Survey

The star-forming clumps in star-bursting dwarf galaxies provide valuable insights into the understanding of the evolution of dwarf galaxies. In this paper, we focus on five star-bursting dwarf galaxies featuring off-centered clumps in the Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey. Using the stellar population synthesis software FADO, we obtain the spatially-resolved distribution of the star formation history, which allows us to construct the $g$-band images of the five galaxies at different ages. These images can help us to probe the evolution of the morphological structures of these galaxies. While images of stellar population older than 1 Gyr are typically smooth, images of stellar population younger than 1 Gyr reveal significant clumps, including multiple clumps which appear at different locations and even different ages. To study the evolutionary connections of these five galaxies to other dwarf galaxies before their star-forming clumps appear, we construct the images of the stellar populations older than three age nodes, and define them to be the images of the "host" galaxies. We find that the properties such as the central surface brightness and the effective radii of the hosts of the five galaxies are in between those of dwarf ellipticals (dEs) and dwarf irregulars (dIrrs), with two clearly more similar to dEs and one more similar to dIrrs. Among the five galaxies, 8257-3704 is particularly interesting, as it shows a previous starburst event that is not quite visible from its $gri$ image, but only visible from images of the stellar population at a few hundred million years. The star-forming clump associated with this event may have appeared at around 600 Myr and disappeared at around 40 Myr.

astro-ph.GA↗