arXiv subjects

Kai Zhang

Publications and source records attributed to Kai Zhang.

At least 667 records · Page 37Linked to original sources

arXiv2018

Efficient Test-based Variable Selection for High-dimensional Linear Models

Variable selection plays a fundamental role in high-dimensional data analysis. Various methods have been developed for variable selection in recent years. Well-known examples are forward stepwise regression (FSR) and least angle regression (LARS), among others. These methods typically add variables into the model one by one. For such selection procedures, it is crucial to find a stopping criterion that controls model complexity. One of the most commonly used techniques to this end is cross-validation (CV) which, in spite of its popularity, has two major drawbacks: expensive computational cost and lack of statistical interpretation. To overcome these drawbacks, we introduce a flexible and efficient test-based variable selection approach that can be incorporated into any sequential selection procedure. The test, which is on the overall signal in the remaining inactive variables, is based on the maximal absolute partial correlation between the inactive variables and the response given active variables. We develop the asymptotic null distribution of the proposed test statistic as the dimension tends to infinity uniformly in the sample size. We also show that the test is consistent. With this test, at each step of the selection, a new variable is included if and only if the $p$-value is below some pre-defined level. Numerical studies show that the proposed method delivers very competitive performance in terms of variable selection accuracy and computational complexity compared to CV.

stat.ME↗

arXiv2018

Chain length effects of $p$-oligophenyls with comparison of benzene by Raman scattering

Raman scattering measurements are performed on benzene and a number of $p$-oligophenyls including biphenyl, $p$-terphenyl, $p$-quaterphenyl, $p$-quinquephenyl, and $p$-sexiphenyl at ambient conditions. The vibrational modes of the intra- and intermolecular terms in these materials are analyzed and compared. Chain length effects on the vibrational properties are examined for the C-H in-plane bending mode and the inter-ring C-C stretching mode at around 1200 cm$^{-1}$ and 1280 cm$^{-1}$, respectively, and the C-C stretching modes at around 1600 cm$^{-1}$. The complex and fluctuating properties of these modes result in an imprecise estimation of the chain length of these molecules. Meanwhile, the obtained ratio of the intensities of the 1200 cm$^{-1}$ mode and 1280 cm$^{-1}$ mode is sensitive to the applied lasers. A librational motion mode with the lowest energy is found to have a monotonous change with the increase in the chain length. This mode is simply relevant to the $c$ axis of the unit cell. Such an obvious trend makes it a better indicator for determining the chain length effects on the physical and chemical properties in these molecules.

cond-mat.mtrl-sci↗

arXiv2018

Superconductivity in potassium-doped 2,2$'$-bipyridine

Organic compounds are always promising candidates of superconductors with high transition temperatures. We examine this proposal by choosing 2,2$'$-bipyridine solely composed by C, H, and N atoms. The presence of Meissner effect with a transition temperature of 7.2 K in this material upon potassium doping is demonstrated by the $dc$ magnetic susceptibility measurements. The real part of the $ac$ susceptibility exhibits the same transition temperature as that in $dc$ magnetization, and a sharp peak appeared in the imaginary part indicates the formation of the weakly linked superconducting vortex current. The occurence of superconductivity is further supported by the resistance drop at the transition together with its suppression by the applied magnetic fields. The superconducting phase is identified to be K$_3$-2,2$'$-bipyridine from the analysis of Raman scattering spectra. This work not only opens an encouraging window for finding superconductivity after optoelectronics in 2,2$'$-bipyridine-based materials but also offers an example to realize superconductivity from conducting polymers and their derivatives.

cond-mat.supr-con↗

arXiv2018

Observation of Meissner effect in potassium-doped $p$-quaterphenyl

Inspired by the discovery of high temperature superconductivity in potassium-doped $p$-terphenyl, we examine the possibility of superconductivity in $p$-quaterphenyl with one more phenyl ring than $p$-terphenyl. The Meissner effect with critical temperatures ranging from 3.5 K to 120 K is found by the magnetic susceptibility measurements in $p$-quaterphenyl upon doping potassium in the condition of annealing or just pestling. The primary superconducting phase with critical temperature of 7.2 K can be reduplicated in several superconducting samples. In both the annealed and pestled superconducting samples, the observation of bipolaronic character by the Raman scattering measurements reveals the close relationship between bipolarons and superconductivity. The occurrence of superconductivity in potassium-doped $p$-quaterphenyl provides an indication that chain link organic molecules are potential candidates for high temperature superconductors.

cond-mat.supr-con↗

arXiv2017

Fundamental Limits of Coded Caching: From Uncoded Prefetching to Coded Prefetching

In order to characterize the fundamental limit of the tradeoff between the amount of cache memory and the delivery transmission rate of multiuser caching systems, various coding schemes have been proposed in the literature. These schemes can largely be categorized into two classes, namely uncoded prefetching schemes and coded prefetching schemes. While uncoded prefetching schemes in general offer order-wise optimal performance, coded prefetching schemes often have better performance at the low cache memory regime. The significant differences in the coding components between the two classes may leave the impression that they are largely unrelated. In this work, we provide a connection between the uncoded prefetching scheme proposed by Maddah Ali and Niesen (and its improved version by Yu et al) and the coded prefetching scheme proposed by Tian and Chen. A critical observation is first given where a coding component in the Tian-Chen scheme can be replaced by a binary .code, which enables us to view the two schemes as the extremes of a more general scheme. An explicit example is given to show that the intermediate operating points of this general scheme can in fact provide new memory-rate tradeoff points previously not known to be achievable in the literature. This new general coding scheme is then presented and analyzed rigorously, which yields a new inner bound to the memory-rate tradeoff for the caching problem.

cs.IT↗

arXiv2017

Single Image Super-resolution via a Lightweight Residual Convolutional Neural Network

Recent years have witnessed great success of convolutional neural network (CNN) for various problems both in low and high level visions. Especially noteworthy is the residual network which was originally proposed to handle high-level vision problems and enjoys several merits. This paper aims to extend the merits of residual network, such as skip connection induced fast training, for a typical low-level vision problem, i.e., single image super-resolution. In general, the two main challenges of existing deep CNN for supper-resolution lie in the gradient exploding/vanishing problem and large numbers of parameters or computational cost as CNN goes deeper. Correspondingly, the skip connections or identity mapping shortcuts are utilized to avoid gradient exploding/vanishing problem. In addition, the skip connections have naturally centered the activation which led to better performance. To tackle with the second problem, a lightweight CNN architecture which has carefully designed width, depth and skip connections was proposed. In particular, a strategy of gradually varying the shape of network has been proposed for residual network. Different residual architectures for image super-resolution have also been compared. Experimental results have demonstrated that the proposed CNN model can not only achieve state-of-the-art PSNR and SSIM results for single image super-resolution but also produce visually pleasant results. This paper has extended the mmm 2017 oral conference paper with a considerable new analyses and more experiments especially from the perspective of centering activations and ensemble behaviors of residual network.

cs.CV↗

arXiv2017

SDSS-IV MaNGA: Constraints on the Conditions for Star Formation in Galaxy Discs

Regions of disc galaxies with widespread star formation tend to be both gravitationally unstable and self-shielded against ionizing radiation, whereas extended outer discs with little or no star formation tend to be stable and unshielded on average. We explore what drives the transition between these two regimes, specifically whether discs first meet the conditions for self-shielding (parameterized by dust optical depth, $τ$) or gravitational instability (parameterized by a modified version of Toomre's instability parameters, $Q_{\rm thermal}$, which quantifies the stability of a gas disc that is thermally supported at $T=10^4$ K). We first introduce a new metric formed by the product of these quantities, $Q_{\rm thermal}τ$, which indicates whether the conditions for disk instability or self-shielding are easier to meet in a given region of a galaxy, and we discuss how $Q_{\rm thermal}τ$ can be constrained even in the absence of direct gas information. We then analyse a sample of 13 galaxies with resolved gas measurements and find that on average galaxies will reach the threshold for disk instabilities ($Q_{\rm thermal}<1$) before reaching the threshold for self-shielding ($τ>1$). Using integral field spectroscopic observations of a sample of 236 galaxies from the MaNGA survey, we find that the value of $Q_{\rm thermal}τ$ in star-forming discs is consistent with similar behavior. These results support a scenario where disc fragmentation and collapse occurs before self-shielding, suggesting that gravitational instabilities are the primary condition for widespread star formation in galaxy discs. Our results support similar conclusions based on recent galaxy simulations.

astro-ph.GA↗

arXiv2017

Biases in metallicity measurements from global galaxy spectra: the effects of flux-weighting and diffuse ionized gas contamination

Galaxy metallicity scaling relations provide a powerful tool for understanding galaxy evolution, but obtaining unbiased global galaxy gas-phase oxygen abundances requires proper treatment of the various line-emitting sources within spectroscopic apertures. We present a model framework that treats galaxies as ensembles of HII and diffuse ionized gas (DIG) regions of varying metallicities. These models are based upon empirical relations between line ratios and electron temperature for HII regions, and DIG strong-line ratio relations from SDSS-IV MaNGA IFU data. Flux-weighting effects and DIG contamination can significantly affect properties inferred from global galaxy spectra, biasing metallicity estimates by more than 0.3 dex in some cases. We use observationally-motivated inputs to construct a model matched to typical local star-forming galaxies, and quantify the biases in strong-line ratios, electron temperatures, and direct-method metallicities as inferred from global galaxy spectra relative to the median values of the HII region distributions in each galaxy. We also provide a generalized set of models that can be applied to individual galaxies or galaxy samples in atypical regions of parameter space. We use these models to correct for the effects of flux-weighting and DIG contamination in the local direct-method mass-metallicity and fundamental metallicity relations, and in the mass-metallicity relation based on strong-line metallicities. Future photoionization models of galaxy line emission need to include DIG emission and represent galaxies as ensembles of emitting regions with varying metallicity, instead of as single HII regions with effective properties, in order to obtain unbiased estimates of key underlying physical properties.

astro-ph.GA↗

arXiv2017

Particle rearrangement and softening contributions to the nonlinear mechanical response of glasses

Amorphous materials such as metallic, polymeric, and colloidal glasses, exhibit complex preparation-dependent mechanical response to applied shear. We perform numerical simulations to investigate the mechanical response of binary Lennard-Jones glasses undergoing athermal, quasistatic pure shear as a function of the cooling rate $R$ used to prepare them. The ensemble-averaged stress versus strain curve $\langleσ(γ)\rangle$ resembles the spatial average in the large size limit, which appears smooth and displays a putative elastic regime at small strains, a yielding-related peak at intermediate strain, and a plastic flow regime at large strains. In contrast, for each glass configuration in the ensemble, the stress-strain curve consists of many short nearly linear segments that are punctuated by particle-rearrangement-induced rapid stress drops. We quantify the shape of the small stress-strain segments, as well as the frequency and size of the stress drops in each glass configuration. We decompose the stress loss into the loss from particle rearrangements and from softening i.e., the reduction of the slopes of the linear segments in $σ(γ)$), and then compare the two contributions as a function of $R$ and $γ$. For the current studies, the rearrangement-induced stress loss is larger than the softening-induced stress loss, however, softening stress losses increase with decreasing cooling rate. We also characterize the structure of the potential energy landscape along the strain direction for glasses prepared with different $R$, and observe a dramatic change of the properties of the landscape near the yielding transition. We then show that the rearrangement-induced energy loss per strain can serve as an order parameter for the yielding transition, which sharpens for slow cooling rates and in the large system-size limit.

cond-mat.stat-mech↗

arXiv2017

Rank-Extreme Association of Gaussian Vectors and Low-Rank Detection

We study the spherical cap packing problem with a probabilistic approach. Such probabilistic considerations result in an asymptotic sharp universal uniform bound on the maximal inner product between any set of unit vectors and a stochastically independent uniformly distributed unit vector. When the set of unit vectors are themselves independently uniformly distributed, we further develop the extreme value distribution limit of the maximal inner product, which characterizes its uncertainty around the bound. As applications of the above asymptotic results, we derive (1) an asymptotic sharp universal uniform bound on the maximal spurious correlation, as well as its uniform convergence in distribution when the explanatory variables are independently Gaussian distributed; and (2) an asymptotic sharp universal bound on the maximum norm of a low-rank elliptically distributed vector, as well as related limiting distributions. With these results, we develop a fast detection method for a low-rank structure in high-dimensional Gaussian data without using the spectrum information.

math.ST↗

arXiv2017

Spherical Cap Packing Asymptotics and Rank-Extreme Detection

math.ST↗

arXiv2017

Learning Deep CNN Denoiser Prior for Image Restoration

Model-based optimization methods and discriminative learning methods have been the two dominant strategies for solving various inverse problems in low-level vision. Typically, those two kinds of methods have their respective merits and drawbacks, e.g., model-based optimization methods are flexible for handling different inverse problems but are usually time-consuming with sophisticated priors for the purpose of good performance; in the meanwhile, discriminative learning methods have fast testing speed but their application range is greatly restricted by the specialized task. Recent works have revealed that, with the aid of variable splitting techniques, denoiser prior can be plugged in as a modular part of model-based optimization methods to solve other inverse problems (e.g., deblurring). Such an integration induces considerable advantage when the denoiser is obtained via discriminative learning. However, the study of integration with fast discriminative denoiser prior is still lacking. To this end, this paper aims to train a set of fast and effective CNN (convolutional neural network) denoisers and integrate them into model-based optimization method to solve other inverse problems. Experimental results demonstrate that the learned set of denoisers not only achieve promising Gaussian denoising results but also can be used as prior to deliver good performance for various low-level vision applications.

cs.CV↗

arXiv2017

SDSS-IV MaNGA: The Impact of Diffuse Ionized Gas on Emission-line Ratios, Interpretation of Diagnostic Diagrams, and Gas Metallicity Measurements

Diffuse Ionized Gas (DIG) is prevalent in star-forming galaxies. Using a sample of 365 nearly face-on star-forming galaxies observed by MaNGA, we demonstrate how DIG in star-forming galaxies impacts the measurements of emission line ratios, hence the interpretation of diagnostic diagrams and gas-phase metallicity measurements. At fixed metallicity, DIG-dominated low Hα surface brightness regions display enhanced [SII]/Hα, [NII]/Hα, [OII]/Hβ, and [OI]/Hα. The gradients in these line ratios are determined by metallicity gradients and Hα surface brightness. In line ratio diagnostic diagrams, contamination by DIG moves HII regions towards composite or LI(N)ER-like regions. A harder ionizing spectrum is needed to explain DIG line ratios. Leaky HII region models can only shift line ratios slightly relative to HII region models, and thus fail to explain the composite/LI(N)ER line ratios displayed by DIG. Our result favors ionization by evolved stars as a major ionization source for DIG with LI(N)ER-like emission. DIG can significantly bias the measurement of gas metallicity and metallicity gradients derived using strong-line methods. Metallicities derived using N2O2 are optimal because they exhibit the smallest bias and error. Using O3N2, R23, N2=[NII]/Hα, and N2S2Hα (Dopita et al. 2016) to derive metallicities introduces bias in the derived metallicity gradients as large as the gradient itself. The strong-line method of Blanc et al. (2015; IZI hereafter) cannot be applied to DIG to get an accurate metallicity because it currently contains only HII region models which fail to describe the DIG.

astro-ph.GA↗

arXiv2017

Calibrated Percentile Double Bootstrap For Robust Linear Regression Inference

We consider inference for the parameters of a linear model when the covariates are random and the relationship between response and covariates is possibly non-linear. Conventional inference methods such as z-intervals perform poorly in these cases. We propose a double bootstrap-based calibrated percentile method, perc-cal, as a general-purpose CI method which performs very well relative to alternative methods in challenging situations such as these. The superior performance of perc-cal is demonstrated by a thorough, full-factorial design synthetic data study as well as a real data example involving the length of criminal sentences. We also provide theoretical justification for the perc-cal method under mild conditions. The method is implemented in the R package `perccal', available through CRAN and coded primarily in C++, to make it easier for practitioners to use.

stat.ME↗

arXiv2016

SDSS-IV MaNGA: environmental dependence of stellar age and metallicity gradients in nearby galaxies

We present a study on the stellar age and metallicity distributions for 1105 galaxies using the STARLIGHT software on MaNGA integral field spectra. We derive age and metallicity gradients by fitting straight lines to the radial profiles, and explore their correlations with total stellar mass M*, NUV-r colour and environments, as identified by both the large scale structure (LSS) type and the local density. We find that the mean age and metallicity gradients are close to zero but slightly negative, which is consistent with the inside-out formation scenario. Within our sample, we find that both the age and metallicity gradients show weak or no correlation with either the LSS type or local density environment. In addition, we also study the environmental dependence of age and metallicity values at the effective radii. The age and metallicity values are highly correlated with M* and NUV-r and are also dependent on LSS type as well as local density. Low-mass galaxies tend to be younger and have lower metallicity in low-density environments while high-mass galaxies are less affected by environment.

astro-ph.GA↗

arXiv2016

Principle of detailed balance and a dilute gas in gravitational field

We study in this paper a dilute gas in a gravitational field and present a relation of the molecular distribution function with respect to position and velocity. The relation is obtained from the principle of detailed balance and can be used to study temperature distribution and density distribution.

cond-mat.stat-mech↗

arXiv2016

A New Diagnostic Diagram of Ionization Source for High Redshift Emission Line Galaxies

We propose a new diagram, the Kinematic-Excitation diagram (KEx diagram), which uses the [OIII]/Hβ line ratio and the [OIII]5007 emission line width (σ_{[OIII]}) to diagnose the ionization source and physical properties of the Active Galactic Nuclei (AGNs) and the star-forming galaxies (SFGs). The KEx diagram is a suitable tool to classify emission-line galaxies (ELGs) at intermediate redshift because it uses only the [OIII]5007 and Hβ emission lines. We use the SDSS DR7 main galaxy sample and the Baldwin-Phillips-Terlevich (BPT) diagnostic to calibrate the diagram at low redshift. We find that the diagram can be divided into 3 regions: one occupied mainly by the pure AGNs (KEx-AGN region), one dominated by composite galaxies (KEx-composite region), and one contains mostly SFGs (KEx-SFG region). AGNs are separated from SFGs in this diagram mainly because they preferentially reside in luminous and massive galaxies and have high [OIII]/Hβ. The separation of AGN from star-forming galaxies is even cleaner thanks to the additional 0.15/0.12 dex offset in [OIII] line width at fixed luminosity/stellar mass. We apply the KEx diagram to 7,866 galaxies at 0.3 < z < 1 in the DEEP2 Galaxy Redshift Survey, and compare it to an independent X-ray classification scheme using Chandra observation. X-ray AGNs are mostly located in the KEx-AGN region while X-ray SFGs are mostly located in the KEx-SFG region. Almost all of Type1 AGNs lie in the KEx-AGN region. These confirm the reliability of this classification diagram for emission line galaxies at intermediate redshift. At z~2, the demarcation line between star-forming galaxies and AGNs should shift 0.3 dex higher in σ_{[OIII]} to account for evolution.

astro-ph.GA↗

arXiv2016

SDSS-IV MaNGA: A serendipitous observation of a potential gas accretion event

The nature of warm, ionized gas outside of galaxies may illuminate several key galaxy evolutionary processes. A serendipitous observation by the MaNGA survey has revealed a large, asymmetric H$α$ complex with no optical counterpart that extends $\approx8"$ ($\approx6.3$ kpc) beyond the effective radius of a dusty, starbursting galaxy. This H$α$ extension is approximately three times the effective radius of the host galaxy and displays a tail-like morphology. We analyze its gas-phase metallicities, gaseous kinematics, and emission-line ratios, and discuss whether this H$α$ extension could be diffuse ionized gas, a gas accretion event, or something else. We find that this warm, ionized gas structure is most consistent with gas accretion through recycled wind material, which could be an important process that regulates the low-mass end of the galaxy stellar mass function.

astro-ph.GA↗