arXiv subjects

Jie Wang

Publications and source records attributed to Jie Wang.

At least 595 records · Page 33Linked to original sources

arXiv2018

Infection Analysis on Irregular Networks through Graph Signal Processing

In a networked system, functionality can be seriously endangered when nodes are infected, due to internal random failures or a contagious virus that develops into an epidemic. Given a snapshot of the network representing the nodes' states (infected or healthy), infection analysis refers to distinguishing an epidemic from random failures and gathering information for effective countermeasure design. This analysis is challenging due to irregular network structure, heterogeneous epidemic spreading, and noisy observations. This paper treats a network snapshot as a graph signal, and develops effective approaches for infection analysis based on graph signal processing. For the macro (network-level) analysis aiming to distinguish an epidemic from random failures, 1) multiple detection metrics are defined based on the graph Fourier transform (GFT) and neighborhood characteristics of the graph signal; 2) a new class of graph wavelets, distance-based graph wavelets (DBGWs), are developed; and 3) a machine learning-based framework is designed employing either the GFT spectrum or the graph wavelet coefficients as features for infection analysis. DBGWs also enable the micro (node-level) infection analysis, through which the performance of epidemic countermeasures can be improved. Extensive simulations are conducted to demonstrate the effectiveness of all the proposed algorithms in various network settings.

cs.SI↗

arXiv2018

The effect of air exposure on SEY and surface composition of laser treated copper applied in accelerators

In this paper, the effect of air exposure and acetone cleaning on the secondary electron yield (SEY) of laser treated copper were investigated and discussed. The SEY of laser treated copper samples after acetone cleaning and air exposure were measured. After 10 to 21 months air exposure, the maximum SEY increased by about 11%~20%. Furthermore, changes of carbon, copper, and oxygen chemistry states from sample surface after acetone and air exposure were studied by means of XPS. The XPS results show that the concentration of Cu decreased by about 61%~70% after acetone cleaning and decreased by a further 36%~70% after 10 to 21 months air exposure. Moreover, the XPS measurement reflects the significant increase of the total percentages of C and O after acetone cleaning, and further increase after 10 to 21 months air exposure. The increase of SEY is explained in terms of the introduction of impurities, such as oxide, carbide etc.

physics.acc-ph↗

arXiv2018

Nonlinear Shape Regression For Filtering Segmentation Results From Calcium Imaging

A shape filter is presented to repair segmentation results obtained in calcium imaging of neurons in vivo. This post-segmentation algorithm can automatically smooth the shapes obtained from a preliminary segmentation, while precluding the cases where two neurons are counted as one combined component. The shape filter is realized using a square-root velocity to project the shapes on a shape manifold in which distances between shapes are based on elastic changes. Two data-driven weighting methods are proposed to achieve a trade-off between shape smoothness and consistency with the data. Intuitive comparisons of proposed methods via projection onto Cartesian maps demonstrate the smoothing ability of the shape filter. Quantitative measures also prove the superiority of our methods over models that do not employ any weighting criterion.

eess.IV↗

arXiv2018

Density-dependent clustering: I. Pulling back the curtains on motions of the BAO peak

The most common statistic used to analyze large-scale structure surveys is the correlation function, or power spectrum. Here, we show how `slicing' the correlation function on local density brings sensitivity to interesting non-Gaussian features in the large-scale structure, such as the expansion or contraction of baryon acoustic oscillations (BAO) according to the local density. The sliced correlation function measures the large-scale flows that smear out the BAO, instead of just correcting them as reconstruction algorithms do. Thus, we expect the sliced correlation function to be useful in constraining the growth factor, and modified gravity theories that involve the local density. Out of the studied cases, we find that the run of the BAO peak location with density is best revealed when slicing on a $\sim 40$ Mpc/$h$ filtered density. But slicing on a $\sim100$ Mpc/$h$ filtered density may be most useful in distinguishing between underdense and overdense regions, whose BAO peaks are separated by a substantial $\sim 5$ Mpc/$h$ at $z=0$. We also introduce `curtain plots' showing how local densities drive particle motions toward or away from each other over the course of an $N$-body simulation.

astro-ph.CO↗

arXiv2018

Resolution of the apparent discrepancy between the number of massive subhaloes in Abell 2744 and ΛCDM

Schwinn et al. (2017) have recently compared the abundance and distribution of massive substructures identified in a gravitational lensing analysis of Abell 2744 by Jauzac et al. (2016) and N-body simulation and found no cluster in ΛCDM simulation that is similar to Abell 2744. Schwinn et al.(2017) identified the measured projected aperture masses with the actual masses associated with subhaloes in the MXXL N-body simulation. We have used the high resolution Phoenix cluster simulations to show that such an identification is incorrect: the aperture mass is dominated by mass in the body of the cluster that happens to be projected along the line-of-sight to the subhalo. This enhancement varies from factors of a few to factors of more than 100, particularly for subhaloes projected near the centre of the cluster. We calculate aperture masses for subhaloes in our simulation and compare them to the measurements for Abell 2744. We find that the data for Abell 2744 are in excellent agreement with the matched predictions from ΛCDM. We provide further predictions for aperture mass functions of subhaloes in idealized surveys with varying mass detection thresholds.

astro-ph.GA↗

arXiv2018

The Large-scale Effect of Environment on Galactic Conformity

We use a volume-limited galaxy sample from the SDSS Data Release 7 to explore the dependence of galactic conformity on the large-scale environment, measured on $\sim$ 4 Mpc scales. We find that the star formation activity of neighbour galaxies depends more strongly on the environment than on the activity of their primary galaxies. In under-dense regions most neighbour galaxies tend to be active, while in over-dense regions neighbour galaxies are mostly passive, regardless of the activity of their primary galaxies. At a given stellar mass, passive primary galaxies reside in higher density regions than active primary galaxies, leading to the apparently strong conformity signal. The dependence of the activity of neighbour galaxies on environment can be explained by the corresponding dependence of the fraction of satellite galaxies. Similar results are found for galaxies in a semi-analytical model, suggesting that no new physics is required to explain the observed large-scale conformity.

astro-ph.GA↗

arXiv2018

The irreducible components of the primal cohomology of the theta divisor of an abelian fivefold

The primal cohomology $\mathbb{K}_\mathbb{Q}$ of the theta divisor $Θ$ of a principally polarized abelian fivefold (ppav) is the direct sum of its invariant and anti-invariant parts $\mathbb{K}_\mathbb{Q}^{+1}$, resp. $\mathbb{K}_\mathbb{Q}^{-1}$ under the action of $-1$. For smooth $Θ$, these have dimension $6$ and $72$ respectively. We show that $\mathbb{K}_\mathbb{Q}^{+1}$ consists of Hodge classes and, for a very general ppav, $\mathbb{K}_\mathbb{Q}^{-1}$ is a simple Hodge structure of level $2$.

math.AG↗

arXiv2018

SDSS-IV MaNGA: A Distinct Mass Distribution Explored in Slow-Rotating Early-type Galaxies

We study the radial acceleration relation (RAR) for early-type galaxies (ETGs) in the SDSS MaNGA MPL5 dataset. The complete ETG sample show a slightly offset RAR from the relation reported by McGaugh et al. (2016) at the low-acceleration end; we find that the deviation is due to the fact that the slow rotators show a systematically higher acceleration relation than the McGaugh's RAR, while the fast rotators show a consistent acceleration relation to McGaugh's RAR. There is a 1σsignificant difference between the acceleration relations of the fast and slow rotators, suggesting that the acceleration relation correlates with the galactic spins, and that the slow rotators may have a different mass distribution compared with fast rotators and late-type galaxies. We suspect that the acceleration relation deviation of slow rotators may be attributed to more galaxy merger events, which would disrupt the original spins and correlated distributions of baryons and dark matter orbits in galaxies.

astro-ph.GA↗

arXiv2018

PHoToNs--A Parallel Heterogeneous & Threads oriented code for cosmological N-body simulation

We introduce a new code for cosmological simulations, PHoToNs, which has features on performing massive cosmological simulations on heterogeneous high performance Computer (HPC) and threads oriented programming. PHoToNs adopts a hybrid scheme to compute gravity force, with the conventional PM to compute the long-range force, the Tree algorithm to compute the short range force, and the direct summation PP to compute the gravity from very close particles. A self-similar space filling Peano-Hilbert curve is used to decompose computing domain. Threads programming is highly used to more flexibly manage the domain communication, PM calculation and synchronization, as well as Dual Tree Traversal on the CPU+MIC platform. The scalability of the PHoToNs performs well and the efficiency of PP kernel achieves 68.6% of peak performance on MIC and 74.4% on CPU platforms. We also test the accuracy of the code against the much used Gadget-2 in the community and found excellent agreement.

astro-ph.CO↗

arXiv2017

Probing satellite galaxies in the Local Group by using FAST

The abundance of neutral hydrogen (HI) in satellite galaxies in the Local Group is important for studying the formation history of our Local Group. In this work, we generated mock HI satellite galaxies in the Local Group using the high mass resolution hydrodynamic \textsc{apostle} simulation. The simulated HI mass function agrees with the ALFALFA survey very well above $10^6M_{\odot}$, although there is a discrepancy below this scale because of the observed flux limit. After carefully checking various systematic elements in the observations, including fitting of line width, sky coverage, integration time, and frequency drift due to uncertainty in a galaxy's distance, we predicted the abundance of HI in galaxies in a future survey that will be conducted by FAST. FAST has a larger aperture and higher sensitivity than the Arecibo telescope. We found that the HI mass function could be estimated well around $10^5 M_{\odot}$ if the integration time is 40 minutes. Our results indicate that there are 61 HI satellites in the Local Group, and 36 in the FAST field above $10^5 M_{\odot}$. This estimation is one order of magnitude better than the current data, and will put a strong constraint on the formation history of the Local Group. Also more high resolution simulated samples are needed to achieve this target.

astro-ph.GA↗

arXiv2017

Berry phase and model wavefunction in the half-filled Landau Level

We construct model wavefunctions for the half-filled Landau level parameterized by "composite fermion occupation-number configurations" in a two-dimensional momentum space which correspond to a Fermi sea with particle-hole excitations. When these correspond to a weakly-excited Fermi sea, they have large overlap with wavefunctions obtained by exact diagonalization of lowest-Landau-level electrons interacting with a Coulomb interaction, allowing exact states to be identified with quasiparticle configurations. We then formulate a many-body version of the single-particle Berry phase for adiabatic transport of a single quasiparticle around a path in momentum space, and evaluate it using a sequence of exact eigenstates in which a single quasiparticle moves incrementally. In this formulation the standard free-particle construction in terms of the overlap between "periodic parts of successive Bloch wavefunctions" is reinterpreted as the matrix element of a "momentum boost" operator between the full Bloch states, which becomes the matrix elements of a Girvin-MacDonald-Platzman density operator in the many-body context. This allows computation of the Berry phase for transport of a single composite fermion around the Fermi surface. In addition to a phase contributed by the density operator, we find a phase of exactly $π$ for this process.

cond-mat.str-el↗

arXiv2017

Lattice Monte Carlo for Quantum Hall States on a Torus

Monte Carlo is one of the most useful methods to study the quantum Hall problems. In this paper, we introduce a fast lattice Monte Carlo method based on a mathematically exact reformulation of the torus quantum Hall problems from continuum to lattice. We first apply this new technique to study the Berry phase of transporting composite fermions along different closed paths enclosing or not enclosing the Fermi surface center in the half filled Landau level problem. The Monte Carlo result agrees with the phase structure we found on small systems and confirms it on much larger sizes. Several other quantities including the Coulomb energy in different Landau levels, structure factor, particle-hole symmetry are computed and discussed for various model states. In the end, based on certain knowledge of structure factor, we introduce a algorithm by which the lattice Monte Carlo efficiency is further boosted by several orders.

cond-mat.str-el↗

arXiv2017

Efficient and Effective Single-Document Summarizations and A Word-Embedding Measurement of Quality

Our task is to generate an effective summary for a given document with specific realtime requirements. We use the softplus function to enhance keyword rankings to favor important sentences, based on which we present a number of summarization algorithms using various keyword extraction and topic clustering methods. We show that our algorithms meet the realtime requirements and yield the best ROUGE recall scores on DUC-02 over all previously-known algorithms. We show that our algorithms meet the realtime requirements and yield the best ROUGE recall scores on DUC-02 over all previously-known algorithms. To evaluate the quality of summaries without human-generated benchmarks, we define a measure called WESM based on word-embedding using Word Mover's Distance. We show that the orderings of the ROUGE and WESM scores of our algorithms are highly comparable, suggesting that WESM may serve as a viable alternative for measuring the quality of a summary.

cs.IR↗

arXiv2017

DTATG: An Automatic Title Generator based on Dependency Trees

We study automatic title generation for a given block of text and present a method called DTATG to generate titles. DTATG first extracts a small number of central sentences that convey the main meanings of the text and are in a suitable structure for conversion into a title. DTATG then constructs a dependency tree for each of these sentences and removes certain branches using a Dependency Tree Compression Model we devise. We also devise a title test to determine if a sentence can be used as a title. If a trimmed sentence passes the title test, then it becomes a title candidate. DTATG selects the title candidate with the highest ranking score as the final title. Our experiments showed that DTATG can generate adequate titles. We also showed that DTATG-generated titles have higher F1 scores than those generated by the previous methods.

cs.IR↗

arXiv2017

How biased is your model? Concentration Inequalities, Information and Model Bias

We derive tight and computable bounds on the bias of statistical estimators, or more generally of quantities of interest, when evaluated on a baseline model P rather than on the typically unknown true model Q. Our proposed method combines the scalable information inequality derived by P. Dupuis, K.Chowdhary, the authors and their collaborators together with classical concentration inequalities (such as Bennett's and Hoeffding-Azuma inequalities). Our bounds are expressed in terms of the Kullback-Leibler divergence R(Q||P) of model Q with respect to P and the moment generating function for the statistical estimator under P. Furthermore, concentration inequalities, i.e. bounds on moment generating functions, provide tight and computationally inexpensive model bias bounds for quantities of interest. Finally, they allow us to derive rigorous confidence bands for statistical estimators that account for model bias and are valid for an arbitrary amount of data.

cs.IT↗

arXiv2017

Massive Quiescent Galaxies at z>3 in The Millennium Simulation Populated by A Semi-analytic Galaxy Formation Model

We take advantage of the statistical power of the large-volume dark-matter-only Millennium simulation, combined with a sophisticated semi-analytic galaxy formation model, to explore whether the recently reported $z=3.7$ quiescent galaxy ZF-COSMOS-20115 (ZF; Glazebrook et al. 2017) can be accommodated in current galaxy formation models. In our model, a population of quiescent galaxies (QGs) with stellar masses and star formation rates comparable to those of ZF naturally emerges at redshifts $z<4$. There are two and five ZF analogues at the redshift $3.86$ and $3.58$ in the Millennium simulation volume, respectively. We demonstrate that, while the $z>3.5$ massive QGs are rare (about 2\% of the galaxies with the similar stellar masses), the existing AGN feedback model implemented in the semi-analytic galaxy formation model can successfully explain the formation of the high-redshift QGs as it does on their lower redshift counterparts.

astro-ph.GA↗

arXiv2017

The segregation of baryons and dark matter during halo assembly

The standard galaxy formation theory assumes that baryons and dark matter are initially well-mixed before becoming segregated due to radiative cooling. We use non-radiative hydrodynamical simulations to explicitly examine this assumption and find that baryons and dark matter can also be segregated because of different physics obeyed by gas and dark matter during the build-up of the halo. As a result, baryons in many haloes do not originate from the same Lagrangian region as the dark matter. When using the fraction of corresponding dark matter and gas particles in the initial conditions (the "paired fraction") as a proxy of the dark matter and gas segregation strength of a halo, on average about $25$ percent of the baryonic and dark matter of the final halo are segregated in the initial conditions. This is at odds with the assumption of the standard galaxy formation model. A consequence of this effect is that the baryons and dark matter of the same halo initially experience different tidal torques and thus their angular momentum vectors are often misaligned. The degree of the misalignment is largely preserved during later halo assembly and can be understood with the tidal torque theory. The result challenges the precision of some semi-analytical approaches which utilize dark matter halo merger trees to infer properties of gas associated to dark matter haloes.

astro-ph.GA↗

arXiv2017

Large-scale Feature Selection of Risk Genetic Factors for Alzheimer's Disease via Distributed Group Lasso Regression

Genome-wide association studies (GWAS) have achieved great success in the genetic study of Alzheimer's disease (AD). Collaborative imaging genetics studies across different research institutions show the effectiveness of detecting genetic risk factors. However, the high dimensionality of GWAS data poses significant challenges in detecting risk SNPs for AD. Selecting relevant features is crucial in predicting the response variable. In this study, we propose a novel Distributed Feature Selection Framework (DFSF) to conduct the large-scale imaging genetics studies across multiple institutions. To speed up the learning process, we propose a family of distributed group Lasso screening rules to identify irrelevant features and remove them from the optimization. Then we select the relevant group features by performing the group Lasso feature selection process in a sequence of parameters. Finally, we employ the stability selection to rank the top risk SNPs that might help detect the early stage of AD. To the best of our knowledge, this is the first distributed feature selection model integrated with group Lasso feature selection as well as detecting the risk genetic factors across multiple research institutions system. Empirical studies are conducted on 809 subjects with 5.9 million SNPs which are distributed across several individual institutions, demonstrating the efficiency and effectiveness of the proposed method.

cs.LG↗