arXiv subjects

Yi Yang

Publications and source records attributed to Yi Yang.

At least 1,099 records · Page 61Linked to original sources

arXiv2016

Interstellar-Medium Mapping in M82 Through Light Echoes Around Supernova 2014J

We present multiple-epoch measurements of the size and surface brightness of the light echoes from supernova (SN) 2014J in the nearby starburst galaxy M82. Hubble Space Telescope (HST) ACS/WFC images were taken ~277 and ~416 days after B-band maximum in the filters F475W, F606W, and F775W. Observations with HST WFC3/UVIS images at epochs ~216 and ~365 days (Crotts 2015) are included for a more complete analysis. The images reveal the temporal evolution of at least two major light-echo components. The first one exhibits a filled ring structure with position-angle-dependent intensity. This radially extended, diffuse echo indicates the presence of an inhomogeneous interstellar dust cloud ranging from ~100 pc to ~500 pc in the foreground of the SN. The second echo component appears as an unresolved luminous quarter-circle arc centered on the SN. The wavelength dependence of scattering measured in different dust components suggests that the dust producing the luminous arc favors smaller grain sizes, while that causing the diffuse light echo may have sizes similar to those of the Milky Way dust. Smaller grains can produce an optical depth consistent with that along the supernova-Earth line of sight measured by previous studies around maximum light. Therefore, it is possible that the dust slab, from which the luminous arc arises, is also responsible for most of the extinction towards SN 2014J. The optical depths determined from the Milky Way-like dust in the scattering matters are lower than that produced by the dust slab.

astro-ph.HE↗

arXiv2016

A Resolved Near-Infrared Image of The Inner Cavity in The GM Aur Transitional Disk

We present high-contrast H-band polarized intensity (PI) images of the transitional disk around the young solar-like star GM Aur. The near-infrared direct imaging of the disk was derived by polarimetric differential imaging using the Subaru 8.2-m Telescope and HiCIAO. An angular resolution and an inner working angle of 0."07 and r~0."05, respectively, were obtained. We clearly resolved a large inner cavity, with a measured radius of 18+/-2 au, which is smaller than that of a submillimeter interferometric image (28 au). This discrepancy in the cavity radii at near-infrared and submillimeter wavelengths may be caused by a 3-4M_Jup planet about 20 au away from the star, near the edge of the cavity. The presence of a near-infrared inner is a strong constraint on hypotheses for inner cavity formation in a transitional disk. A dust filtration mechanism has been proposed to explain the large cavity in the submillimeter image, but our results suggest that this mechanism must be combined with an additional process. We found that the PI slope of the outer disk is significantly different from the intensity slope obtained from HST/NICMOS, and this difference may indicate the grain growth process in the disk.

astro-ph.SR↗

arXiv2016

Optimizing Memory Efficiency for Deep Convolutional Neural Networks on GPUs

Leveraging large data sets, deep Convolutional Neural Networks (CNNs) achieve state-of-the-art recognition accuracy. Due to the substantial compute and memory operations, however, they require significant execution time. The massive parallel computing capability of GPUs make them as one of the ideal platforms to accelerate CNNs and a number of GPU-based CNN libraries have been developed. While existing works mainly focus on the computational efficiency of CNNs, the memory efficiency of CNNs have been largely overlooked. Yet CNNs have intricate data structures and their memory behavior can have significant impact on the performance. In this work, we study the memory efficiency of various CNN layers and reveal the performance implication from both data layouts and memory access patterns. Experiments show the universal effect of our proposed optimizations on both single layers and various networks, with up to 27.9x for a single layer and up to 5.6x on the whole networks.

cs.DC↗

arXiv2016

Person Re-identification: Past, Present and Future

Person re-identification (re-ID) has become increasingly popular in the community due to its application and research significance. It aims at spotting a person of interest in other cameras. In the early days, hand-crafted algorithms and small-scale evaluation were predominantly reported. Recent years have witnessed the emergence of large-scale datasets and deep learning systems which make use of large data volumes. Considering different tasks, we classify most current re-ID methods into two classes, i.e., image-based and video-based; in both tasks, hand-crafted and deep learning systems will be reviewed. Moreover, two new re-ID tasks which are much closer to real-world applications are described and discussed, i.e., end-to-end re-ID and fast re-ID in very large galleries. This paper: 1) introduces the history of person re-ID and its relationship with image classification and instance retrieval; 2) surveys a broad selection of the hand-crafted systems and the large-scale methods in both image- and video-based re-ID; 3) describes critical future directions in end-to-end re-ID and fast retrieval in large galleries; and 4) finally briefs some important yet under-developed issues.

cs.CV↗

arXiv2016

The expanding light echoes from supernova 2014J in M82

We present the measurement of the size and surface brightness of the expanding light echoes from supernova (SN) 2014J in the nearby starburst galaxy M82. Hubble Space Telescope (HST) ACS/WFC images were taken ~277 and ~416 days (after the time of B-band maximum light) in the filters F475W, F606W, and F775W, each combined with the three polarizing filters: POL0V, POL60V, and POL120V. The two epochs' imaging reveals the time evolution of at least two major echoes. Three concentric bright regions between position angles (PA, 0^{\circ} from North, counterclockwise). 80^{\circ} ~ 170^{\circ} have projected radius of 0.60" on the sky on ~277 days and expanding to 0.75" on ~416 days, corresponding to scattering materials at a foreground distance of 222\pm37 pc. Another fainter but evident light echo extending over a wide range of PA has radii of 0.75" and 0.96" on ~277 and ~416 days. This corresponds to scattering material at a foreground distance of 367\pm61 pc. Multiple light echoes with S/N > 2.5 reside at smaller radii on ~277 days but become less significant on ~416 days indicating a complex structure of foreground interstellar medium (ISM). The light echo shows bluer color than predicted under a Rayleigh scattering case. We also found the light echo brightened from V_{echo}=21.68\pm0.07 on 2014 September 5, to V_{echo}=21.05\pm0.08 on 2014 November 6, suggesting an enhancement of echoing materials at different distances projected on to the plane of the sky.

astro-ph.SR↗

arXiv2016

Inverse Magnetic Catalysis in the Soft-Wall Model of AdS/QCD

Magnetic effects on chiral phase transition have been investigated in a modified soft-wall AdS/QCD model, in which the dilaton field is taken to be negative at the ultraviolet region and positive at the infrared region as in Phys.Rev.D93(2016),101901 and JHEP1604(2016)036. The magnetic field is introduced into the background geometry by solving the Einstein-Maxwell system. After embedding the magnetized background geometry into the modified soft-wall model, the magnetic field dependent behavior of chiral condensate is worked out numerically. It is found that, in the chiral limit, the chiral phase transition remains as a second order at finite magnetic field $B$, while the symmetry restoration temperature and chiral condensate decrease with the increasing of magnetic field in small $B$ region. When including finite quark mass effect, the phase transition turns to be a crossover one, and the transition temperature still decreases with increasing magnetic field $B$ when $B$ is not very large. In this sense, inverse magnetic catalysis effect is observed in this modified soft-wall AdS/QCD model.

hep-th↗

arXiv2016

S-MART: Novel Tree-based Structured Learning Algorithms Applied to Tweet Entity Linking

Non-linear models recently receive a lot of attention as people are starting to discover the power of statistical and embedding features. However, tree-based models are seldom studied in the context of structured learning despite their recent success on various classification and ranking tasks. In this paper, we propose S-MART, a tree-based structured learning framework based on multiple additive regression trees. S-MART is especially suitable for handling tasks with dense features, and can be used to learn many different structures under various loss functions. We apply S-MART to the task of tweet entity linking --- a core component of tweet information extraction, which aims to identify and link name mentions to entities in a knowledge base. A novel inference algorithm is proposed to handle the special structure of the task. The experimental results show that S-MART significantly outperforms state-of-the-art tweet entity linking systems.

cs.CL↗

arXiv2016

Toward Socially-Infused Information Extraction: Embedding Authors, Mentions, and Entities

Entity linking is the task of identifying mentions of entities in text, and linking them to entries in a knowledge base. This task is especially difficult in microblogs, as there is little additional text to provide disambiguating context; rather, authors rely on an implicit common ground of shared knowledge with their readers. In this paper, we attempt to capture some of this implicit context by exploiting the social network structure in microblogs. We build on the theory of homophily, which implies that socially linked individuals share interests, and are therefore likely to mention the same sorts of entities. We implement this idea by encoding authors, mentions, and entities in a continuous vector space, which is constructed so that socially-connected authors have similar vector representations. These vectors are incorporated into a neural structured prediction model, which captures structural constraints that are inherent in the entity linking task. Together, these design decisions yield F1 improvements of 1%-5% on benchmark datasets, as compared to the previous state-of-the-art.

cs.CL↗

arXiv2016

The Lauricella Functions and Exact String Scattering Amplitudes

We discover that the 26D open bosonic string scattering amplitudes (SSA) of three tachyons and one arbitrary string state can be expressed in terms of the D-type Lauricella functions with associated SL(K+3,C) symmetry. As a result, SSA and symmetries or relations among SSA of different string states at various limits calculated previously can be rederived. These include the linear relations first conjectured by Gross [1-3] and later corrected and proved in [4-9] in the hard scattering limit, the recurrence relations in the Regge scattering limit with associated SL(5,C) symmetry [19-21] and the extended recurrence relations in the nonrelativistic scattering limit with associated SL(4,C) symmetry [24] discovered recently. Finally, as an application, we calculate a new recurrence relation of SSA which is valid for all energies.

hep-th↗

arXiv2016

ASASSN-15lh: A Superluminous Ultraviolet Rebrightening Observed by Swift and Hubble

We present and discuss ultraviolet and optical photometry from the Ultraviolet/Optical Telescope and X-ray limits from the X-Ray Telescope on Swift and imaging polarimetry and ultraviolet/optical spectroscopy with the Hubble Space Telescope of ASASSN-15lh. It has been classified as a hydrogen-poor superluminous supernova (SLSN I) more luminous than any other supernova observed. ASASSN-15lh is not detected in the X-rays in individual or coadded observations. From the polarimetry we determine that the explosion was only mildly asymmetric. We find the flux of ASASSN-15lh to increase strongly into the ultraviolet, with a ultraviolet luminosity a hundred times greater than the hydrogen-rich, ultraviolet-bright SLSN II SN 2008es. We find objects as bright as ASASSN-15lh are easily detectable beyond redshifts of ~4 with the single-visit depths planned for the Large Synoptic Survey Telescope. Deep near-infrared surveys could detect such objects past a redshift of ~20 enabling a probe of the earliest star formation. A late rebrightening -- most prominent at shorter wavelengths -- is seen about two months after the peak brightness, which is itself as bright as a superluminous supernova. The ultraviolet spectra during the rebrightening are dominated by the continuum without the broad absorption or emission lines seen in SLSNe or tidal disruption events and the early optical spectra of ASASSN-15lh. Our spectra show no strong hydrogen emission, showing only LyA absorption near the redshift previously found by optical absorption lines of the presumed host. The properties of ASASSN-15lh are extreme when compared to either SLSNe or tidal disruption events.

astro-ph.HE↗

arXiv2016

Sparsity Oriented Importance Learning for High-dimensional Linear Regression

With now well-recognized non-negligible model selection uncertainty, data analysts should no longer be satisfied with the output of a single final model from a model selection process, regardless of its sophistication. To improve reliability and reproducibility in model choice, one constructive approach is to make good use of a sound variable importance measure. Although interesting importance measures are available and increasingly used in data analysis, little theoretical justification has been done. In this paper, we propose a new variable importance measure, sparsity oriented importance learning (SOIL), for high-dimensional regression from a sparse linear modeling perspective by taking into account the variable selection uncertainty via the use of a sensible model weighting. The SOIL method is theoretically shown to have the inclusion/exclusion property: When the model weights are properly around the true model, the SOIL importance can well separate the variables in the true model from the rest. In particular, even if the signal is weak, SOIL rarely gives variables not in the true model significantly higher important values than those in the true model. Extensive simulations in several illustrative settings and real data examples with guided simulations show desirable properties of the SOIL importance in contrast to other importance measures.

stat.ME↗

arXiv2016

Strategies for Searching Video Content with Text Queries or Video Examples

The large number of user-generated videos uploaded on to the Internet everyday has led to many commercial video search engines, which mainly rely on text metadata for search. However, metadata is often lacking for user-generated videos, thus these videos are unsearchable by current search engines. Therefore, content-based video retrieval (CBVR) tackles this metadata-scarcity problem by directly analyzing the visual and audio streams of each video. CBVR encompasses multiple research topics, including low-level feature design, feature fusion, semantic detector training and video search/reranking. We present novel strategies in these topics to enhance CBVR in both accuracy and speed under different query inputs, including pure textual queries and query by video examples. Our proposed strategies have been incorporated into our submission for the TRECVID 2014 Multimedia Event Detection evaluation, where our system outperformed other submissions in both text queries and video example queries, thus demonstrating the effectiveness of our proposed approaches.

cs.IR↗

arXiv2016

Optically Thin Metallic Films for High-radiative-efficiency Plasmonics

Plasmonics enables deep-subwavelength concentration of light and has become important for fundamental studies as well as real-life applications. Two major existing platforms of plasmonics are metallic nanoparticles and metallic films. Metallic nanoparticles allow efficient coupling to far field radiation, yet their synthesis typically leads to poor material quality. Metallic films offer substantially higher quality materials, but their coupling to radiation is typically jeopardized due to the large momentum mismatch with free space. Here, we propose and theoretically investigate optically thin metallic films as an ideal platform for high-radiative-efficiency plasmonics. For far-field scattering, adding a thin high-quality metallic substrate enables a higher quality factor while maintaining the localization and tunability that the nanoparticle provides. For near-field spontaneous emission, a thin metallic substrate, of high quality or not, greatly improves the field overlap between the emitter environment and propagating surface plasmons, enabling high-Purcell (total enhancement > $10^4$), high-quantum-yield (> 50 %) spontaneous emission, even as the gap size vanishes (3$\sim$5 nm). The enhancement has almost spatially independent efficiency and does not suffer from quenching effects that commonly exist in previous structures.

physics.optics↗

arXiv2016

Probing Neutrino Mass Hierarchy by Comparing the Charged-Current and Neutral-Current Interaction Rates of Supernova Neutrinos

The neutrino mass hierarchy is one of the neutrino fundamental properties yet to be determined. We introduce a method to determine neutrino mass hierarchy by comparing the interaction rate of neutral current (NC) interactions, $ν(\hatν) + p\rightarrowν(\hatν) + p$, and inverse beta decays (IBD), $\barν_e + p\rightarrow n + e^+$, of supernova neutrinos in scintillation detectors. Neutrino flavor conversions inside the supernova are sensitive to neutrino mass hierarchy. Due to Mikheyev-Smirnov-Wolfenstein effects, the full swapping of $\barν_e$ flux with the $\barν_x$ ($x=μ,~τ$) one occurs in the inverted hierarchy, while such a swapping does not occur in the normal hierarchy. As a result, more high energy IBD events occur in the detector for the inverted hierarchy than the high energy IBD events in the normal hierarchy. By comparing IBD interaction rate with the mass hierarchy independent NC interaction rate, one can determine the neutrino mass hierarchy.

hep-ph↗

arXiv2016

Attention to Scale: Scale-aware Semantic Image Segmentation

Incorporating multi-scale features in fully convolutional neural networks (FCNs) has been a key element to achieving state-of-the-art performance on semantic image segmentation. One common way to extract multi-scale features is to feed multiple resized input images to a shared deep network and then merge the resulting features for pixelwise classification. In this work, we propose an attention mechanism that learns to softly weight the multi-scale features at each pixel location. We adapt a state-of-the-art semantic image segmentation model, which we jointly train with multi-scale input images and the attention model. The proposed attention model not only outperforms average- and max-pooling, but allows us to diagnostically visualize the importance of features at different positions and scales. Moreover, we show that adding extra supervision to the output at each scale is essential to achieving excellent performance when merging multi-scale features. We demonstrate the effectiveness of our model with extensive experiments on three challenging datasets, including PASCAL-Person-Part, PASCAL VOC 2012 and a subset of MS-COCO 2014.

cs.CV↗

arXiv2016

Fluid/Gravity Correspondence with Scalar Field and Electromagnetic Field

We consider fluid/gravity correspondence in a general rotating black hole background with scalar and electromagnetic fields. Using the method of Petrov-like boundary condition, we show that the scalar and the electromagnetic fields contribute external forces to the dual Navier-Stokes equation and the rotation of black hole induces the Coriolis force.

hep-th↗

arXiv2016

The String BCJ Relations Revisited and Extended Recurrence relations of Nonrelativistic String Scattering Amplitudes

We review and extend high energy string BCJ relations in both the fixed angle and Regge regimes. We then give an explicit proof of four point string BCJ relations for all energy. This calculation provides an alternative proof of the one based on monodromy of integration in string amplitude calculation. In addition, we calculate both s-t and t-u channel nonrelativistic low energy string scattering amplitudes of three tachyons and one leading trojectory string state at arbitrary mass levels. We discover that the mass and spin dependent nonrelativistic string BCJ relations can be expressed in terms of Gauss hypergeometry functions. As an application, for each fixed mass level N, we derive extended recurrence relations among nonrelativistic low energy string scattering amplitudes of string states with different spins and different channels.

hep-th↗

arXiv2016

Insurance Premium Prediction via Gradient Tree-Boosted Tweedie Compound Poisson Models

The Tweedie GLM is a widely used method for predicting insurance premiums. However, the structure of the logarithmic mean is restricted to a linear form in the Tweedie GLM, which can be too rigid for many applications. As a better alternative, we propose a gradient tree-boosting algorithm and apply it to Tweedie compound Poisson models for pure premiums. We use a profile likelihood approach to estimate the index and dispersion parameters. Our method is capable of fitting a flexible nonlinear Tweedie model and capturing complex interactions among predictors. A simulation study confirms the excellent prediction performance of our method. As an application, we apply our method to an auto insurance claim data and show that the new method is superior to the existing methods in the sense that it generates more accurate premium predictions, thus helping solve the adverse selection issue. We have implemented our method in a user-friendly R package that also includes a nice visualization tool for interpreting the fitted model.

stat.ME↗