arXiv subjects

Jianling Wang

Publications and source records attributed to Jianling Wang.

At least 55 records · Page 3Linked to original sources

arXiv2021

Milky Way total Mass derived by Rotation Curve and Globular Cluster kinematics from Gaia EDR3

Using action-based distribution function for the dynamical model of the Milky Way we have estimated its total mass and its density profile. Constraints are coming from the globular cluster proper motions from Gaia EDR3, from the rotation curve based on Gaia DR2 data, and from the vertical force data. We use Bayesian Markov chain Monte Carlo method to explore the parameters, for which the globular cluster distribution function and the Galactic potential are fully constrained. Numerical simulations are used to study the uncertainties on the potential constraint if considering a possible massive Large Magellanic Could (LMC). We found that a massive LMC (1.5$\times10^{11}$ M$_{\odot}$) will affect the MW mass measurement at large radius, which includes both the Milky Way and the LMC. We also use the FIRE2 Latte cosmological hydrodynamic simulations to make mock data set from a Milky-Way like galaxy that includes many unrelaxed substructures. We test the effect of these unrelaxed substructures on the final results, and found that the measured rotation curve fluctuated around input value within 5 percent. By keeping a large freedom in choosing a priori mass profile for both baryonic and dark matter leads a total mass of the MW that ranges from $5.36_{-0.68}^{+0.81}\times10^{11}$ M$_{\odot}$ to $7.84_{-1.97}^{+3.08} \times 10^{11}$ M$\odot$. This includes the contribution of a putative massive LMC and significantly narrows the MW total mass range published earlier. Such total mass leads to dark matter density at solar position of $0.34_{-0.02}^{+0.02}$ GeV cm$^{-3}$.

astro-ph.GA↗

arXiv2021

Gaia EDR3 proper motions of Milky Way dwarfs. II: Velocities, Total Energy and Angular Momentum

Here we show that precise Gaia EDR3 proper motions have provided robust estimates of 3D velocities, angular momentum and total energy for 40 Milky Way dwarfs. The results are statistically robust and are independent of the Milky Way mass profile. Dwarfs do not behave like long-lived satellites of the Milky Way because of their excessively large velocities, angular momenta, and total energies. Comparing them to other MW halo population, we find that many are at first passage, $\le$ 2 Gyr ago, i.e., more recently than the passage of Sagittarius, $\sim$ 4-5 Gyr ago. We suggest that this is in agreement with the stellar populations of all dwarfs, for which we find that a small fraction of young stars cannot be excluded. We also find that dwarf radial velocities contribute too little to their kinetic energy when compared to satellite systems with motions only regulated by gravity, and some other mechanism must be at work such as ram pressure. The latter may have preferentially reduced radial velocities when dwarf progenitors entered the halo until they lost their gas. It could also explain why most dwarfs lie near their pericenter. We also discover a novel large scale structure perpendicular to the Milky Way disk, which is made by 20% of dwarfs orbiting or counter orbiting with the Sagittarius dwarf.

astro-ph.GA↗

arXiv2021

Which Milky Way masses are consistent with the slightly declining 5-25 kpc rotation curve?

Discoveries of extended rotation curves have suggested the presence of dark matter in spiral galaxy haloes. It has led to many studies that estimated the galaxy total mass, mostly by using the Navarro Frenk and White (NFW) density profile. We aim at verifying how the choice of the dark-matter profile may affect the predicted values of extrapolated total masses. We have considered the recent Milky Way (MW) rotation curve, firstly because of its unprecedented accuracy, and secondly because the Galactic disk is amongst the least affected by past major mergers having fully reshaped the initial disk. We find that the use of NFW profile (or its generalized form, gNFW) for calculating the dark-matter contribution to the MW rotation curve generates apparently inconsistent results, e.g., an increase of the baryonic mass leads to increase of the dark matter mass. Furthermore we find that NFW and gNFW profile narrow the total mass range, leading to a possible methodological bias particularly against small MW masses. By using the Einasto profile that is more appropriate to represent cold dark matter haloes, we finally find that the Milky Way slightly decreasing rotation curve favors total mass that can be as small as 2.6 $\times 10^{11}$ $M_{\odot}$, disregarding any other dynamical tracers further out in the MW. It is inconsistent with values larger than 18 $\times 10^{11}$ $M_{\odot}$ for any kind of CDM dark-matter halo profiles, under the assumption that stars and gas do not influence the predicted dark matter distribution in the MW. This methodological paper encourages the use of the Einasto profile for characterizing rotation curves with the aim of evaluating their total masses.

astro-ph.GA↗

arXiv2021

Sequential Recommendation for Cold-start Users with Meta Transitional Learning

A fundamental challenge for sequential recommenders is to capture the sequential patterns of users toward modeling how users transit among items. In many practical scenarios, however, there are a great number of cold-start users with only minimal logged interactions. As a result, existing sequential recommendation models will lose their predictive power due to the difficulties in learning sequential patterns over users with only limited interactions. In this work, we aim to improve sequential recommendation for cold-start users with a novel framework named MetaTL, which learns to model the transition patterns of users through meta-learning. Specifically, the proposed MetaTL: (i) formulates sequential recommendation for cold-start users as a few-shot learning problem; (ii) extracts the dynamic transition patterns among users with a translation-based architecture; and (iii) adopts meta transitional learning to enable fast learning for cold-start users with only limited interactions, leading to accurate inference of sequential interactions.

cs.IR↗

arXiv2021

Gaia EDR3 proper motions of Milky Way dwarfs I: 3D Motions and Orbits

Based on Gaia Early Data Release 3 (EDR3), we estimate the proper motions for 46 dwarf spheroidal galaxies (dSphs) of the Milky Way. The uncertainties in proper motions, determined by combining both statistical and systematic errors, are smaller by a factor 2.5, when compared with Gaia Data Release 2. We have derived orbits in four Milky Way potential models that are consistent with the MW rotation curve, with total mass ranging from $2.8\times10^{11}$ $M_{\odot}$ to $15\times10^{11}$ $M_{\odot}$. Although the type of orbit (ellipse or hyperbola) are very dependent on the potential model, the pericenter values are firmly determined, largely independent of the adopted MW mass model. By analyzing the orbital phases, we found that the dSphs are highly concentrated close to their pericenter, rather than to their apocenter as expected from Kepler's law. This may challenge the fact that most dSphs are Milky Way satellites, or alternatively indicates an unexpected large number of undiscovered dSphs lying very close to their apocenters. Between half and two thirds of the satellites have orbital poles that indicate them to orbit along the Vast Polar Structure (VPOS), with the vast majority of these co-orbiting in a common direction also shared by the Magellanic Clouds, which is indicative of a real structure of dSphs.

astro-ph.GA↗

arXiv2021

Fairness-aware Personalized Ranking Recommendation via Adversarial Learning

Recommendation algorithms typically build models based on historical user-item interactions (e.g., clicks, likes, or ratings) to provide a personalized ranked list of items. These interactions are often distributed unevenly over different groups of items due to varying user preferences. However, we show that recommendation algorithms can inherit or even amplify this imbalanced distribution, leading to unfair recommendations to item groups. Concretely, we formalize the concepts of ranking-based statistical parity and equal opportunity as two measures of fairness in personalized ranking recommendation for item groups. Then, we empirically show that one of the most widely adopted algorithms -- Bayesian Personalized Ranking -- produces unfair recommendations, which motivates our effort to propose the novel fairness-aware personalized ranking model. The debiased model is able to improve the two proposed fairness metrics while preserving recommendation performance. Experiments on three public datasets show strong fairness improvement of the proposed model versus state-of-the-art alternatives. This is paper is an extended and reorganized version of our SIGIR 2020~\cite{zhu2020measuring} paper. In this paper, we re-frame the studied problem as `item recommendation fairness' in personalized ranking recommendation systems, and provide more details about the training process of the proposed model and details of experiment setup.

cs.IR↗

arXiv2021

Most dwarf spheroidal galaxies surrounding the Milky Way cannot be dark-matter dominated satellites

Milky Way dwarf spheroidal galaxies are the tiniest observed galaxies and are currently associated with the largest fractions of dark matter, which is revealed by their too large velocity dispersions. However, most of them are found near their orbital pericenters. This leads to a very low probability, P = 2 $10^{-7}$, that they could be long-lived satellites such as sub-halos predicted by cosmological simulations. Their proximity to their pericenters suggests instead that they are affected by tidal shocks, which provide sufficient kinematic energy to explain their high velocity dispersions. Dependency of the dark matter properties to their distance to the Milky Way appears to favor tidally shocked and out of equilibrium dSphs instead of self-equilibrium systems dominated by dark matter.

astro-ph.GA↗

arXiv2020

Graph Prototypical Networks for Few-shot Learning on Attributed Networks

Attributed networks nowadays are ubiquitous in a myriad of high-impact applications, such as social network analysis, financial fraud detection, and drug discovery. As a central analytical task on attributed networks, node classification has received much attention in the research community. In real-world attributed networks, a large portion of node classes only contain limited labeled instances, rendering a long-tail node class distribution. Existing node classification algorithms are unequipped to handle the \textit{few-shot} node classes. As a remedy, few-shot learning has attracted a surge of attention in the research community. Yet, few-shot node classification remains a challenging problem as we need to address the following questions: (i) How to extract meta-knowledge from an attributed network for few-shot node classification? (ii) How to identify the informativeness of each labeled instance for building a robust and effective model? To answer these questions, in this paper, we propose a graph meta-learning framework -- Graph Prototypical Networks (GPN). By constructing a pool of semi-supervised node classification tasks to mimic the real test environment, GPN is able to perform \textit{meta-learning} on an attributed network and derive a highly generalizable model for handling the target classification task. Extensive experiments demonstrate the superior capability of GPN in few-shot node classification.

cs.LG↗

arXiv2020

Be More with Less: Hypergraph Attention Networks for Inductive Text Classification

Text classification is a critical research topic with broad applications in natural language processing. Recently, graph neural networks (GNNs) have received increasing attention in the research community and demonstrated their promising results on this canonical task. Despite the success, their performance could be largely jeopardized in practice since they are: (1) unable to capture high-order interaction between words; (2) inefficient to handle large datasets and new documents. To address those issues, in this paper, we propose a principled model -- hypergraph attention networks (HyperGAT), which can obtain more expressive power with less computational consumption for text representation learning. Extensive experiments on various benchmark datasets demonstrate the efficacy of the proposed approach on the text classification task.

cs.CL↗

arXiv2020

A Recent Major Merger Tale for the Closest Giant Elliptical Galaxy Centaurus A

We have used hydrodynamical simulations to model the formation of the closest giant elliptical galaxy, Centaurus A. We find that a single major merger event with a mass ratio up to 1.5, and which has happened ~2 Gyr ago, is able to reproduce many of its properties, including galaxy kinematics, the inner gas disk, stellar halo ages and metallicities, and numerous faint features observed in the halo. The elongated halo shape is mostly made of progenitor residuals deposited by the merger, which also contribute to stellar shells observed in the Centaurus A halo. The current model also reproduces the measured Planetary Nebulae line of sight velocity and their velocity dispersion. Models with small mass ratio and relatively low gas fraction result in a de Vaucouleurs profile distribution, which is consistent with observations and model expectations. A recent merger left imprints in the age distribution that are consistent with the young stellar and Globular Cluster populations (2-4 Gyrs) found within the halo. We conclude that even if not all properties of Centaurus A have been accurately reproduced, a recent major merger has likely occurred to form the Centaurus A galaxy as we observe it at present day.

astro-ph.GA↗

arXiv2020

Orbital evidences for dark-matter-free Milky Way dwarf spheroidal galaxies

The nature of Milky Way dwarf spheroidals (MW dSphs) has been questioned, in particular whether they are dominated by dark matter (DM). Here we investigate an alternative scenario, for which tidal shocks are exerted by the MW to DM-free dSphs after a first infall of their gas-rich progenitors, and for which theoretical calculations have been verified by pure N-body simulations. Whether or not the dSphs are on their first infall cannot be resolved on the sole basis of their star formation history. In fact, gas removal may cause complex gravitational instabilities and near-pericenter passages can give rise to tidal disruptive processes. Advanced precision with the Gaia satellite in determining both their past orbital motions and the MW velocity curve is, however, providing crucial results. First, tidal shocks explain why DM-free dSphs are found preferentially near their pericenter, where they are in a destructive process, while their chance to be long-lived satellites is associated with a very low probability P~ 2 10^-7, which is at odds with the current DM-dominated dSph scenario. Second, most dSph binding energies are consistent with a first infall. Third, the MW tidal shocks that predict the observed dSph velocity dispersions are themselves predicted in amplitude by the most accurate MW velocity curve. Fourth, tidal shocks accurately predict the forces or accelerations exerted at half-light radius of dSphs, including the MW and the Magellanic System gravitational attractions. The above is suggestive of dSphs that are DM-free and tidally shocked near their pericenters, which may provoke a significant quake in our understanding of near-field cosmology.

astro-ph.GA↗

arXiv2019

A Hierarchical Self-Attentive Model for Recommending User-Generated Item Lists

User-generated item lists are a popular feature of many different platforms. Examples include lists of books on Goodreads, playlists on Spotify and YouTube, collections of images on Pinterest, and lists of answers on question-answer sites like Zhihu. Recommending item lists is critical for increasing user engagement and connecting users to new items, but many approaches are designed for the item-based recommendation, without careful consideration of the complex relationships between items and lists. Hence, in this paper, we propose a novel user-generated list recommendation model called AttList. Two unique features of AttList are careful modeling of (i) hierarchical user preference, which aggregates items to characterize the list that they belong to, and then aggregates these lists to estimate the user preference, naturally fitting into the hierarchical structure of item lists; and (ii) item and list consistency, through a novel self-attentive aggregation layer designed for capturing the consistency of neighboring items and lists to better model user preference. Through experiments over three real-world datasets reflecting different kinds of user-generated item lists, we find that AttList results in significant improvements in NDCG, Precision@k, and Recall@k versus a suite of state-of-the-art baselines. Furthermore, all code and data are available at https://github.com/heyunh2015/AttList.

cs.IR↗

arXiv2019

On the absence of dark matter in dwarf galaxies surrounding the Milky Way

This paper presents an alternative scenario to explain the observed properties of the Milky Way dwarf Spheroidals (MW dSphs). We show that instead of resulting from large amounts of dark matter (DM), the large velocity dispersions observed along their lines of sight can be entirely accounted for by dynamical heating of DM-free systems resulting from MW tidal shocks. Such a regime is expected if the progenitors of the MW dwarfs are infalling gas-dominated galaxies. In this case, gas lost through ram-pressure leads to a strong decrease of self-gravity, a phase during which stars can radially expand, while leaving a gas-free dSph in which tidal shocks can easily develop. The DM content of dSphs is widely derived from the measurement of the dSphs self-gravity acceleration projected along the line of sight. We show that the latter strongly anti-correlates with the dSph distance from the MW, and that it is matched in amplitude by the acceleration caused by MW tidal shocks on DM-free dSphs. If correct, this implies that the MW dSphs would have negligible DM content, putting in question, e.g., their use as targets for DM direct searches, or our understanding of the Local Group mass assembly history. Most of the progenitors of the MW dSphs are likely extremely tiny dIrrs, and deeper observations and more accurate modeling are necessary to infer their properties as well as to derive star formation histories of the faintest dSphs.

astro-ph.GA↗

arXiv2019

Toward a Complete Understanding of the Magellanic Stream Formation

The Magellanic Clouds have lost most of their gas during their passage by the Milky Way, a property that has never been successfully modeled. Here we use accurate and mesh-free hydrodynamic simulations to reproduce the Magellanic Stream and the Magellanic Clouds in the frame of a 'ram-pressure plus collision' model. This model reproduces many of the observed properties of the HI Stream including most of its density profile along its length and its dual filamentary structure. Besides this, ram-pressure combined with Kelvin-Helmholtz instabilities extracts amounts of ionized and HI gas consistent with those observed. The modeled scenario also reproduces the Magellanic Bridge, including the offset between young and old stars, and the collision between the Clouds, which is responsible of the very elongated morphology of the Small Magellanic Cloud along the line of sight. This model has solved most of the mysteries linked to the formation of the Magellanic Stream. The Leading Arm is not reproduced in the current model because it requires an alternative origin.

astro-ph.GA↗

arXiv2018

Fairness-Aware Recommendation of Information Curators

This paper highlights our ongoing efforts to create effective information curator recommendation models that can be personalized for individual users, while maintaining important fairness properties. Concretely, we introduce the problem of information curator recommendation, provide a high-level overview of a fairness-aware recommender, and introduce some preliminary experimental evidence over a real-world Twitter dataset. We conclude with some thoughts on future directions.

cs.IR↗

arXiv2018

Galactic forces rule dynamics of Milky Way dwarf galaxies

Dwarf galaxies populating the Galactic halo are assumed to host the largest fractions of dark matter, as calculated from their velocity dispersions. Their major axes are preferentially aligned with the Vast Polar Structure (VPOS) that is perpendicular to the Galactic disk, and we find their velocity gradients aligned as well. It suggests that tidal forces exerted by the Milky Way are distorting dwarf galaxies. Here we demonstrate on the basis of the impulse approximation that the Galactic gravitational acceleration induces the dwarf line-of-sight velocity dispersion, which is also evidenced by strong dependences between both quantities. Since this result is valid for any dwarf mass value, it implies that dark matter estimate in Milky Way dwarfs cannot be deduced from the product of their radius to the square of their line-of-sight velocity dispersion. This questions the high dark-matter fractions reported for these evanescent systems, and the universally adopted total-to-stellar mass relationship in the dwarf regime. It suggests that many dwarfs are at their first passage and are dissolving into the Galactic halo. It opens a promising way to estimate the Milky Way total mass profile at large distances.

astro-ph.GA↗

arXiv2017

LAMOST Spectroscopic Survey of the Galactic Anticentre (LSS-GAC): the second release of value-added catalogues

We present the second release of value-added catalogues of the LAMOST Spectroscopic Survey of the Galactic Anticentre (LSS-GAC DR2). The catalogues present values of radial velocity $V_{\rm r}$, atmospheric parameters --- effective temperature $T_{\rm eff}$, surface gravity log$g$, metallicity [Fe/H], $α$-element to iron (metal) abundance ratio [$α$/Fe] ([$α$/M]), elemental abundances [C/H] and [N/H], and absolute magnitudes ${\rm M}_V$ and ${\rm M}_{K_{\rm s}}$ deduced from 1.8 million spectra of 1.4 million unique stars targeted by the LSS-GAC since September 2011 until June 2014. The catalogues also give values of interstellar reddening, distance and orbital parameters determined with a variety of techniques, as well as proper motions and multi-band photometry from the far-UV to the mid-IR collected from the literature and various surveys. Accuracies of radial velocities reach 5kms$^{-1}$ for late-type stars, and those of distance estimates range between 10 -- 30 per cent, depending on the spectral signal-to-noise ratios. Precisions of [Fe/H], [C/H] and [N/H] estimates reach 0.1dex, and those of [$α$/Fe] and [$α$/M] reach 0.05dex. The large number of stars, the contiguous sky coverage, the simple yet non-trivial target selection function and the robust estimates of stellar radial velocities and atmospheric parameters, distances and elemental abundances, make the catalogues a valuable data set to study the structure and evolution of the Galaxy, especially the solar-neighbourhood and the outer disk.

astro-ph.GA↗

arXiv2016

Estimating stellar atmospheric parameters, absolute magnitudes and elemental abundances from the LAMOST spectra with Kernel-based Principal Component Analysis

Accurate determination of stellar atmospheric parameters and elemental abundances is crucial for Galactic archeology via large-scale spectroscopic surveys. In this paper, we estimate stellar atmospheric parameters -- effective temperature T_{\rm eff}, surface gravity log g and metallicity [Fe/H], absolute magnitudes M_V and M_{Ks}, α-element to metal (and iron) abundance ratio [α/M] (and [α/Fe]), as well as carbon and nitrogen abundances [C/H] and [N/H] from the LAMOST spectra with amultivariate regressionmethod based on kernel-based principal component analysis, using stars in common with other surveys (Hipparcos, Kepler, APOGEE) as training data sets. Both internal and external examinations indicate that given a spectral signal-to-noise ratio (SNR) better than 50, our method is capable of delivering stellar parameters with a precision of ~100K for Teff, ~0.1 dex for log g, 0.3 -- 0.4mag for M_V and M_{Ks}, 0.1 dex for [Fe/H], [C/H] and [N/H], and better than 0.05 dex for [α/M] ([α/Fe]). The results are satisfactory even for a spectral SNR of 20. The work presents first determinations of [C/H] and [N/H] abundances from a vast data set of LAMOST, and, to our knowledge, the first reported implementation of absolute magnitude estimation directly based on the observed spectra. The derived stellar parameters for millions of stars from the LAMOST surveys will be publicly available in the form of value-added catalogues.

astro-ph.SR↗