arXiv subjects

Ping Li

Publications and source records attributed to Ping Li.

At least 343 records · Page 19Linked to original sources

arXiv2019

Thermodynamics of the Bardeen Black Hole in Anti-de Sitter Space

We first study the thermodynamics of Bardeen-AdS black hole by the $T$-$r_{h}$ diagram, where T is the Hawking temperature and $r_{h}$ is the radius of event horizon. The cut-off radius which is the minimal radius of the thermodynamical stable Bardeen black hole can be got, and the cut-off radius is the same with the result of the heat capacity analysis. Moreover, by studying the parameter $g$, which is interpreted as a gravitationally collapsed magnetic monopole arising in a specific form of non-linear electrodynamics, in the Bardeen black hole, we can get a critical value $g_{m}$ and different phenomenons with different values of parameter $g$. For $g>g_{m}$, there is no second order phase transition. We also research the thermodynamical stability of the Bardeen black hole by the Gibbs free energy and the heat capacity. In addition, the phase transition is discussed.

hep-th↗

arXiv2019

Randomized Learning of the Second-Moment Matrix of a Smooth Function

Consider an open set $\mathbb{D}\subseteq\mathbb{R}^n$, equipped with a probability measure $μ$. An important characteristic of a smooth function $f:\mathbb{D}\rightarrow\mathbb{R}$ is its \emph{second-moment matrix} $Σ_μ:=\int \nabla f(x) \nabla f(x)^* μ(dx) \in\mathbb{R}^{n\times n}$, where $\nabla f(x)\in\mathbb{R}^n$ is the gradient of $f(\cdot)$ at $x\in\mathbb{D}$ and $*$ stands for transpose. For instance, the span of the leading $r$ eigenvectors of $Σ_μ$ forms an \emph{active subspace} of $f(\cdot)$, which contains the directions along which $f(\cdot)$ changes the most and is of particular interest in \emph{ridge approximation}. In this work, we propose a simple algorithm for estimating $Σ_μ$ from random point evaluations of $f(\cdot)$ \emph{without} imposing any structural assumptions on $Σ_μ$. Theoretical guarantees for this algorithm are established with the aid of the same technical tools that have proved valuable in the context of covariance matrix estimation from partial measurements.

cs.IT↗

arXiv2019

The rigidity on the second fundamental form of projective manifolds

Let $M$ be a complex $n$-dimensional projective manifold in $\mathbb{P}^{n+r}$ endowed with the Fubini-Study metric of constant holomorphic sectional curvature $1$, $σ$ its second fundamental form, and $\underline{|σ|}^2$ the mean value of the squared length of $σ$ on $M$. We derive a formula for $\underline{|σ|}^2$ and classify them when $\underline{|σ|}^2\leq2n$. We present several applications to these results. The first application is to confirm a conjecture of Loi and Zedda, which characterizes the linear subspace and the quadric in terms of the $L^2$-norm of $σ$. The second application is to improve a result of Cheng solving an old conjecture of Oguie from pointwise case to mean case. The third application is to give an optimal second gap value on $\underline{|σ|}^2$, which can be viewed as a complex analog to those on minimal submanifolds in the unit spheres.

math.DG↗

arXiv2019

Photoacoustic Imaging of Lithium Metal Batteries

We demonstrate that photoacoustic microscopy (PAM) can be a potential novel imaging tool to investigate the Li metal dendrite growth, a critical issue leading to short circuit and even explosion of Li metal batteries. Our results suggest several advantages of PAM imaging of Li metal batteries: high resolution (micrometers), 3D imaging capability, deep penetration in a separator, and high contrast from bulk Li metal. Further, PAM has potential for in situ real-time imaging of Li metal batteries.

physics.app-ph↗

arXiv2019

Multi-Spectral Visual Odometry without Explicit Stereo Matching

Multi-spectral sensors consisting of a standard (visible-light) camera and a long-wave infrared camera can simultaneously provide both visible and thermal images. Since thermal images are independent from environmental illumination, they can help to overcome certain limitations of standard cameras under complicated illumination conditions. However, due to the difference in the information source of the two types of cameras, their images usually share very low texture similarity. Hence, traditional texture-based feature matching methods cannot be directly applied to obtain stereo correspondences. To tackle this problem, a multi-spectral visual odometry method without explicit stereo matching is proposed in this paper. Bundle adjustment of multi-view stereo is performed on the visible and the thermal images using direct image alignment. Scale drift can be avoided by additional temporal observations of map points with the fixed-baseline stereo. Experimental results indicate that the proposed method can provide accurate visual odometry results with recovered metric scale. Moreover, the proposed method can also provide a metric 3D reconstruction in semi-dense density with multi-spectral information, which is not available from existing multi-spectral methods.

cs.CV↗

arXiv2019

Engineering Deep Representations for Modeling Aesthetic Perception

Many aesthetic models in computer vision suffer from two shortcomings: 1) the low descriptiveness and interpretability of those hand-crafted aesthetic criteria (i.e., nonindicative of region-level aesthetics), and 2) the difficulty of engineering aesthetic features adaptively and automatically toward different image sets. To remedy these problems, we develop a deep architecture to learn aesthetically-relevant visual attributes from Flickr1, which are localized by multiple textual attributes in a weakly-supervised setting. More specifically, using a bag-ofwords (BoW) representation of the frequent Flickr image tags, a sparsity-constrained subspace algorithm discovers a compact set of textual attributes (e.g., landscape and sunset) for each image. Then, a weakly-supervised learning algorithm projects the textual attributes at image-level to the highly-responsive image patches at pixel-level. These patches indicate where humans look at appealing regions with respect to each textual attribute, which are employed to learn the visual attributes. Psychological and anatomical studies have shown that humans perceive visual concepts hierarchically. Hence, we normalize these patches and feed them into a five-layer convolutional neural network (CNN) to mimick the hierarchy of human perceiving the visual attributes. We apply the learned deep features on image retargeting, aesthetics ranking, and retrieval. Both subjective and objective experimental results thoroughly demonstrate the competitiveness of our approach.

cs.CV↗

arXiv2019

On Convergence of Distributed Approximate Newton Methods: Globalization, Sharper Bounds and Beyond

The DANE algorithm is an approximate Newton method popularly used for communication-efficient distributed machine learning. Reasons for the interest in DANE include scalability and versatility. Convergence of DANE, however, can be tricky; its appealing convergence rate is only rigorous for quadratic objective, and for more general convex functions the known results are no stronger than those of the classic first-order methods. To remedy these drawbacks, we propose in this paper some new alternatives of DANE which are more suitable for analysis. We first introduce a simple variant of DANE equipped with backtracking line search, for which global asymptotic convergence and sharper local non-asymptotic convergence rate guarantees can be proved for both quadratic and non-quadratic strongly convex functions. Then we propose a heavy-ball method to accelerate the convergence of DANE, showing that nearly tight local rate of convergence can be established for strongly convex functions, and with proper modification of algorithm the same result applies globally to linear prediction models. Numerical evidence is provided to confirm the theoretical and practical advantages of our methods.

stat.ML↗

arXiv2019

Kähler hyperbolic manifolds and Chern number inequalities

We show in this article that Kähler hyperbolic manifolds satisfy a family of optimal Chern number inequalities and the equality cases can be attained by some compact ball quotients. These present restrictions to complex structures on negatively-curved compact Kähler manifolds, thus providing evidence to the rigidity conjecture of S.-T. Yau. The main ingredients in our proof are Gromov's results on the $L^2$-Hodge numbers, the $-1$-phenomenon of the $χ_y$-genus and Hirzebruch's proportionality principle. Similar methods can be applied to obtain parallel results on Kähler non-elliptic manifolds. In addition to these, we term a condition called ``Kähler exactness", which includes Kähler hyperbolic and non-elliptic manifolds and has been used by B.-L. Chen and X. Yang in their work, and show that the canonical bundle of a Kähler exact manifold of general type is ample. Some of its consequences and remarks are discussed as well.

math.DG↗

arXiv2019

First-principles prediction of a new family of layered topological insulators

Dozens of layered V$_2$IV$_2$VI$_6$ (V=P, As, Sb, Bi, IV=Si, Ge, Sn, Pb, VI=S, Se, Te) materials are investigated, several of which have been successfully synthesized in experiment. Among them, we predict nine strong topological insulators (TIs), two strong topological metals (TMs) and nearly twenty trivial insulators at their equilibrium structures. The TIs are in the (1;111) topological class, with energy gaps ranging from 0.04 to 0.2 eV. The strong TMs and the trivial insulators belong to the (1;111) and (0;000) topological classes, respectively. Small compressive strains easily turn some of the trivial insulators into strong TIs. This study enriches not only the family of topological materials but also the family of van der Waals layered materials, providing promising candidates for the future spintronic devices.

cond-mat.mtrl-sci↗

arXiv2019

Joule-Thomson expansion of the Bardeen-AdS black holes

The Joule-Thomson expansion process is studied for Bardeen-AdS black holes in the extended phase space. Firstly, we get Joule-Thomson coefficient and find that the divergent point of Joule-Thomson coefficient coincides with the zero point of temperature. The inversion curves are also obtained from the zero point of Joule-Thomson coefficient. Then the minimum inversion temperature and the corresponding mass are obtained. In addition, the ratio between minimum inversion and critical temperature for Bardeen-AdS black holes is also calculated. We obtain the isenthalpic curve in $T$-$P$ graph and demonstrate the cooling-heating region by the inversion curve. An interesting phenomenon we get is that black hole is always in heating process. The same phenomenon can be also obtained from the charged AdS black holes.

gr-qc↗

arXiv2019

Logician: A Unified End-to-End Neural Approach for Open-Domain Information Extraction

In this paper, we consider the problem of open information extraction (OIE) for extracting entity and relation level intermediate structures from sentences in open-domain. We focus on four types of valuable intermediate structures (Relation, Attribute, Description, and Concept), and propose a unified knowledge expression form, SAOKE, to express them. We publicly release a data set which contains more than forty thousand sentences and the corresponding facts in the SAOKE format labeled by crowd-sourcing. To our knowledge, this is the largest publicly available human labeled data set for open information extraction tasks. Using this labeled SAOKE data set, we train an end-to-end neural model using the sequenceto-sequence paradigm, called Logician, to transform sentences into facts. For each sentence, different to existing algorithms which generally focus on extracting each single fact without concerning other possible facts, Logician performs a global optimization over all possible involved facts, in which facts not only compete with each other to attract the attention of words, but also cooperate to share words. An experimental study on various types of open domain relation extraction tasks reveals the consistent superiority of Logician to other states-of-the-art algorithms. The experiments verify the reasonableness of SAOKE format, the valuableness of SAOKE data set, the effectiveness of the proposed Logician model, and the feasibility of the methodology to apply end-to-end learning paradigm on supervised data sets for the challenging tasks of open information extraction.

cs.CL↗

arXiv2019

Cycle-SUM: Cycle-consistent Adversarial LSTM Networks for Unsupervised Video Summarization

In this paper, we present a novel unsupervised video summarization model that requires no manual annotation. The proposed model termed Cycle-SUM adopts a new cycle-consistent adversarial LSTM architecture that can effectively maximize the information preserving and compactness of the summary video. It consists of a frame selector and a cycle-consistent learning based evaluator. The selector is a bi-direction LSTM network that learns video representations that embed the long-range relationships among video frames. The evaluator defines a learnable information preserving metric between original video and summary video and "supervises" the selector to identify the most informative frames to form the summary video. In particular, the evaluator is composed of two generative adversarial networks (GANs), in which the forward GAN is learned to reconstruct original video from summary video while the backward GAN learns to invert the processing. The consistency between the output of such cycle learning is adopted as the information preserving metric for video summarization. We demonstrate the close relation between mutual information maximization and such cycle learning procedure. Experiments on two video summarization benchmark datasets validate the state-of-the-art performance and superiority of the Cycle-SUM model over previous baselines.

cs.CV↗

arXiv2019

Thermodynamics of charged AdS black holes in rainbow gravity

In this paper, the thermodynamic property of charged AdS black holes is studied in rainbow gravity. By the Heisenberg Uncertainty Principle and the modified dispersion relation, we obtain deformed temperature. Moreover, in rainbow gravity we calculate the heat capacity in a fixed charge and discuss the thermal stability. We also obtain a similar behaviour with the liquid-gas system in extending phase space (including $P$ and $r$) and study its critical behavior with the pressure given by the cosmological constant and with a fixed black hole charge $Q$. Furthermore, we study the Gibbs function and find its characteristic swallow tail behavior, which indicates the phase transition. We also find there is a special value about the mass of test particle which would lead the black hole to zero temperature and a diverging heat capacity with a fixed charge.

gr-qc↗

arXiv2019

Apparent horizon and gravitational thermodynamics of Universe in the Eddington-Born-Infeld theory

The thermodynamics of Universe in the Eddington-Born-Infeld (EBI) theory was restudied by utilizing the holographic-style gravitational equations that dominate the dynamics of the cosmical apparent horizon $Υ_{A}$ and the evolution of Universe. We started in rewriting the EBI action of the Palatini approach into the Bigravity-type action with an extra metric $q_{μν}$. With the help of the holographic-style dynamical equations, we discussed the property of the cosmical apparent horizon $Υ_{A}$ including timelike, spacelike and null characters, which depends on the value of the parameter of state $w_{m}$ in EBI Universe. The unified first law for the gravitational thermodynamics and the total energy differential for the open system enveloped by $Υ_{A}$ in EBI Universe were obtained. Finally, applying the positive-heat-out sign convention, we derived the generalized second law of gravitational thermodynamics in EBI universe.

gr-qc↗

arXiv2018

Non-Asymptotic Chernoff Lower Bound and Its Application to Community Detection in Stochastic Block Model

Chernoff coefficient is an upper bound of Bayes error probability in classification problem. In this paper, we will develop sharp Chernoff type bound on Bayes error probability. The new bound is not only an upper bound but also a lower bound of Bayes error probability up to a constant in a non-asymptotic setting. Moreover, we will apply this result to community detection in stochastic block model. As a clustering problem, the optimal error rate of community detection can be characterized by our Chernoff type bound. This can be formalized by deriving a minimax error rate over certain class of parameter space, then achieving such error rate by a feasible algorithm employ multiple steps of EM type updates.

math.ST↗

arXiv2018

Monochromatic $k$-edge-connection colorings of graphs

A path in an edge-colored graph $G$ is called monochromatic if any two edges on the path have the same color. For $k\geq 2$, an edge-colored graph $G$ is said to be monochromatic $k$-edge-connected if every two distinct vertices of $G$ are connected by at least $k$ edge-disjoint monochromatic paths, and $G$ is said to be uniformly monochromatic $k$-edge-connected if every two distinct vertices are connected by at least $k$ edge-disjoint monochromatic paths such that all edges of these $k$ paths colored with a same color. We use $mc_k(G)$ and $umc_k(G)$ to denote the maximum number of colors that ensures $G$ to be monochromatic $k$-edge-connected and, respectively, $G$ to be uniformly monochromatic $k$-edge-connected. In this paper, we first conjecture that for any $k$-edge-connected graph $G$, $mc_k(G)=e(G)-e(H)+\lfloor\frac{k}{2}\rfloor$, where $H$ is a minimum $k$-edge-connected spanning subgraph of $G$. We verify the conjecture for $k=2$. We also prove the conjecture for $G=K_{k+1}$ when $k\geq4$ is even, and for $G=K_{k,n}$ when $k\geq4$ is even, or when $k=3$ and $n\geq k$. When $G$ is a minimal $k$-edge-connected graph, we give an upper bound of $mc_k(G)$, i.e., $mc_k(G)\leq k-1$, and $mc_k(G)\leq \lfloor\frac{k}{2}\rfloor$ when $G=K_{k,n}$. For the uniformly monochromatic $k$-edge-connectivity, we prove that for all $k$, $umc_k(G)=e(G)-e(H)+1$, where $H$ is a minimum $k$-edge-connected spanning subgraph of $G$.

math.CO↗

arXiv2018

On cyclic codes of length $2^e$ over finite fields

Professor Cunsheng Ding gave cyclotomic constructions of cyclic codes with length being the product of two primes. In this paper, we study the cyclic codes of length $n=2^e$ and dimension $k=2^{e-1}$. Clearly, Ding's construction is not hold in this place. We describe two new types of generalized cyclotomy of order two, which are different from Ding's. Furthermore, we study two classes of cyclic codes of length $n$ and dimension $k$. We get the enumeration of these cyclic codes. What's more, all of the codes from our construction are among the best cyclic codes. Furthermore, we study the hull of cyclic codes of length $n$ over $\mathbb{F}_q$. We obtain the range of $\ell=\dim({\rm Hull}(C))$. We construct and enumerate cyclic codes of length $n$ having hull of given dimension.

cs.IT↗

arXiv2018

The evolution of universe in the two-scalar theory

We generalize f(R,T) gravity into the two-scalar theory that includes two independent scalar fields by the variational method, and we derive its field equations in Einstein frame using conformal transformation. Based on Friedmann equations and Raychaudhuri equation, with a consideration of the cosmic content as its perfect-fluid form, a further discussion leads us to an accelerated expanding condition of universe. In the two-scalar theory, universe has two states which are the accelerated expansion and decelerated contraction, and it has three stages during its evolution. The first and third stages are in the accelerated expanding state, and the second stage is in the decelerated contracting state. The third stage represents the present universe and it tends to become a dust universe.

gr-qc↗