Jian Li - Department of Astronomy, Nanjing University, China

Jian Li
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Name
Jian Li
Affiliation
Department of Astronomy, Nanjing University, China
City
Nanjing
Country
China

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Computer Science - Data Structures and Algorithms (10)
 
Computer Science - Learning (10)
 
Physics - Strongly Correlated Electrons (5)
 
High Energy Astrophysical Phenomena (4)
 
Physics - Materials Science (4)
 
Quantum Physics (4)
 
Computer Science - Artificial Intelligence (4)
 
Physics - Mesoscopic Systems and Quantum Hall Effect (4)
 
Computer Science - Computational Geometry (4)
 
Statistics - Machine Learning (4)
 
Mathematics - Dynamical Systems (3)
 
Mathematics - Information Theory (2)
 
Computer Science - Computer Vision and Pattern Recognition (2)
 
Computer Science - Information Theory (2)
 
Computer Science - Networking and Internet Architecture (2)
 
Physics - Superconductivity (2)
 
Mathematics - Statistics (1)
 
Earth and Planetary Astrophysics (1)
 
Statistics - Theory (1)
 
Computer Science - Information Retrieval (1)
 
Physics - Optics (1)
 
Computer Science - Neural and Evolutionary Computing (1)
 
Physics - Chemical Physics (1)
 
Mathematics - Numerical Analysis (1)
 
Physics - Plasma Physics (1)
 
Physics - Physics and Society (1)
 
Mathematics - Combinatorics (1)
 
Mathematics - Functional Analysis (1)
 
Physics - Data Analysis; Statistics and Probability (1)
 
Computer Science - Numerical Analysis (1)

Publications Authored By Jian Li

In the Best-$K$ identification problem (Best-$K$-Arm), we are given $N$ stochastic bandit arms with unknown reward distributions. Our goal is to identify the $K$ arms with the largest means with high confidence, by drawing samples from the arms adaptively. This problem is motivated by various practical applications and has attracted considerable attention in the past decade. Read More

Support Vector Machine is one of the most classical approaches for classification and regression. Despite being studied for decades, obtaining practical algorithms for SVM is still an active research problem in machine learning. In this paper, we propose a new perspective for SVM via saddle point optimization. Read More

Principal component analysis (PCA) is a fundamental dimension reduction tool in statistics and machine learning. For large and high-dimensional data, computing the PCA (i.e. Read More

It is a long standing open problem whether Yao-Yao graphs $\mathsf{YY}_{k}$ are all spanners. Bauer and Damian \cite{bauer2013infinite} showed that all $\mathsf{YY}_{6k}$ for $k \geq 6$ are spanners. Li and Zhan \cite{li2016almost} generalized their result and proved that all even Yao-Yao graphs $\mathsf{YY}_{2k}$ are spanners (for $k\geq 42$). Read More

To advance knowledge of K bonding in Cu(In,Ga)(Se,S)2 (CIGS) photovoltaic (PV) absorbers, recent Cu-K-In-Se phase growth studies have been extended to PV performance. First, the effect of distributing K throughout bulk Cu1-xKxInSe2 absorbers at low K/(K+Cu) compositions (0 <= x <= 0.30) was studied. Read More

Training deep neural networks is a highly nontrivial task, involving carefully selecting appropriate training algorithms, scheduling step sizes and tuning other hyperparameters. Trying different combinations can be quite labor-intensive and time consuming. Recently, researchers have tried to use deep learning algorithms to exploit the landscape of the loss function of the training problem of interest, and learn how to optimize over it in an automatic way. Read More

Internet or things (IoT) is changing our daily life rapidly. Although new technologies are emerging everyday and expanding their influence in this rapidly growing area, many classic theories can still find their places. In this paper, we study the important applications of the classic network coding theory in two important components of Internet of things, including the IoT core network, where data is sensed and transmitted, and the distributed cloud storage, where the data generated by the IoT core network is stored. Read More

In recent years, the capacitated center problems have attracted a lot of research interest. Given a set of vertices $V$, we want to find a subset of vertices $S$, called centers, such that the maximum cluster radius is minimized. Moreover, each center in $S$ should satisfy some capacity constraint, which could be an upper or lower bound on the number of vertices it can serve. Read More

Kitaev interactions underlying a quantum spin liquid have been long sought, but experimental data from which their strengths can be determined directly is still lacking. Here, by carrying out inelastic neutron scattering measurements on high-quality single crystals of $\alpha$-RuCl$_3$, we observe spin-wave spectra with a gap of $\sim$2 meV around the M point of the two-dimensional Brillouin zone. We derive an effective-spin model in the strong-coupling limit based on energy bands obtained from first-principle calculations, and find that the anisotropic Kitaev interaction $K$ term and the isotropic antiferromagentic off-diagonal exchange interaction $\Gamma$ term are significantly larger than the Heisenberg exchange coupling $J$ term. Read More

In the Best-$k$-Arm problem, we are given $n$ stochastic bandit arms, each associated with an unknown reward distribution. We are required to identify the $k$ arms with the largest means by taking as few samples as possible. In this paper, we make progress towards a complete characterization of the instance-wise sample complexity bounds for the Best-$k$-Arm problem. Read More

We study approximation algorithms for the following geometric version of the maximum coverage problem: Let $\mathcal{P}$ be a set of $n$ weighted points in the plane. Let $D$ represent a planar object, such as a rectangle, or a disk. We want to place $m$ copies of $D$ such that the sum of the weights of the points in $\mathcal{P}$ covered by these copies is maximized. Read More

Community structure is an important structural property that extensively exists in various complex networks. In the past decade, much attention has been paid to the design of community-detection methods, but analyzing the behaviors of the methods is also of interest in the theoretical research and real applications. Here, we focus on an important measure for community structure, significance [Sci. Read More

It is known that certain structures of the signal in addition to the standard notion of sparsity (called structured sparsity) can improve the sample complexity in several compressive sensing applications. Recently, Hegde et al. proposed a framework, called approximation-tolerant model-based compressive sensing, for recovering signals with structured sparsity. Read More

Testing quantum theory on macroscopic scales is a longstanding challenge that might help to revolutionise physics. For example, laboratory tests (such as those anticipated in nanomechanical or biological systems) may look to rule out macroscopic realism: the idea that the properties of macroscopic objects exist objectively and can be non-invasively measured. Such investigations are likely to suffer from i) stringent experimental requirements, ii) marginal statistical significance and iii) logical loopholes. Read More

The Leggett-Garg inequalities hold under the assumptions of macrorealism but can be violated by quantum mechanics. The degree to which quantum systems can violate these inequalities, however, is bounded. In particular, if the measurements on the system are genuinely dichotomic, the bound for these temporal inequalities is the same as Tsirelson bound for the relevant spatial Bell inequality. Read More

Typical analysis of content caching algorithms using the metric of hit probability under a stationary request process does not account for performance loss under a variable request arrival process. In this work, we consider adaptability of caching algorithms from two perspectives: (a) the accuracy of learning a fixed popularity distribution; and (b) the speed of learning items' popularity. In order to attain this goal, we compute the distance between the stationary distributions of several popular algorithms with that of a genie-aided algorithm that has knowledge of the true popularity ranking, which we use as a measure of learning accuracy. Read More

We study the spin-wave excitations in $\alpha$-RuCl$_3$ by the spin-wave theory. Starting from the five-orbital Hubbard model and the perturbation theory, we derive an effective isospin-$1/2$ model in the large Hubbard ($U$) limit. Based on the energy-band structure calculated from the first-principle method, we find that the effective model can be further reduced to the $K-\Gamma$ model containing a ferromagnetic nearest-neighbor (NN) Kitaev interaction ($K$) and a NN off-diagonal exchange interaction ($\Gamma$). Read More

Considering about seven years of Fermi-Large Area Telescope (LAT) data, we present a systematic search for variability possibly related to transitions between states in redbacks and black widow systems. Transitions are characterized by sudden and significant changes in the gamma-ray flux that persist on a timescale much larger than the orbital period. This phenomenology was already detected in the case of two redback systems, PSR J1023+0038 and PSR J1227-4853, for which we present here a dedicated study. Read More

Signatures of stochastic effects in the radiation of a relativistic electron beam interacting with a counterpropagating superstrong short focused laser pulse are investigated in a quantum regime when the electron's radiation dominates its dynamics. We consider the electron-laser interaction at near-reflection conditions when pronounced high-energy gamma-ray bursts arise in the backward-emission direction with respect to the initial motion of the electrons. The quantum stochastic nature of the gamma-photon emission is exhibited in the angular distributions of the radiation and explained in an intuitive picture. Read More

Inhomogeneous electron state and pseudogap have been widely observed in underdoped high temperature superconducting (HTSC) cuprates and some other strongly correlated materials. These phenomena are believed to be the characteristics of doped Mott insulators and have not yet been detected in other materials. Here, by using scanning tunneling microscopy (STM) and spectroscopy (STS), we demonstrate the electronic inhomogeneity at low energies and the pseudogap phenomenon in a conventional charge density wave (CDW) material 1T-TiSe2, with light doping by native defects. Read More

A {\em restraint} on a (finite undirected) graph $G = (V,E)$ is a function $r$ on $V$ such that $r(v)$ is a finite subset of ${\mathbb N}$; a proper vertex colouring $c$ of $G$ is {\em permitted} by $r$ if $c(v) \not\in r(v)$ for all vertices $v$ of $G$ (we think of $r(v)$ as the set of colours {\em forbidden} at $v$). Given a large number of colors, for restraints $r$ with exactly one colour forbidden at each vertex the smallest number of colorings is permitted when $r$ is a constant function, but the problem of what restraints permit the largest number of colourings is more difficult. We determine such extremal restraints for complete graphs and trees. Read More

Ordered assemblies of magnetic atoms on the surface of conventional superconductors can be used to engineer topological superconducting phases and realize Majorana fermion quasiparticles (MQPs) in a condensed matter setting. Recent experiments have shown that chains of Fe atoms on Pb generically have the required electronic characteristics to form a 1D topological superconductor and have revealed spatially resolved signatures of localized MQPs at the ends of such chains. Here we report higher resolution measurements of the same atomic chain system performed using a dilution refrigerator scanning tunneling microscope (STM). Read More

In this paper, we consider the non-spectral problem for the planar self-affine measures $\mu_{M,D}$ generated by an expanding integer matrix $M\in M_2(\mathbb{Z})$ and a finite digit set $D\subset\mathbb{Z}^2$. Let $p\geq2$ be a positive integer, $E_p^2:=\frac{1}{p}\{(i,j)^t:0\leq i,j\leq p-1\}$ and $\mathcal{Z}_{D}^2:=\{x\in[0, 1)^2:\sum_{d\in D}{e^{2\pi i\langle d,x\rangle}}=0\}$. We show that if $\emptyset\neq\mathcal{Z}_{D}^2\subset E_p^2\setminus\{0\}$ and $\gcd(\det(M),p)=1$, then there exist at most $p^2$ mutually orthogonal exponential functions in $L^2(\mu_{M,D})$. Read More

For dynamical systems with the shadowing property, we provide a method of approximation of invariant measures by ergodic measures supported on odometers and their almost 1-1 extensions. For a topologically transitive system with the shadowing property, we show that ergodic measures supported on odometers are dense in the space of invariant measures, and then ergodic measures are generic in the space of invariant measures. We also show that for every $c\geq 0$ and $\varepsilon>0$ the collection of ergodic measures (supported on almost 1-1 extensions of odometers) with entropy between $c$ and $c + \varepsilon$ is dense in the space of invariant measures with entropy at least $c$. Read More

Vision-based object detection is one of the fundamental functions in numerous traffic scene applications such as self-driving vehicle systems and advance driver assistance systems (ADAS). However, it is also a challenging task due to the diversity of traffic scene and the storage, power and computing source limitations of the platforms for traffic scene applications. This paper presents a generalized Haar filter based deep network which is suitable for the object detection tasks in traffic scene. Read More

The suffix array is a fundamental data structure for many applications that involve string searching and data compression. Designing time/space-efficient suffix array construction algorithms has attracted significant attentions and considerable advances have been made in the last 20 years. We obtain the suffix array construction algorithms that are optimal both in time and space for both integer and general alphabets. Read More

Following the intense studies on topological insulators, significant efforts have recently been devoted to the search for gapless topological systems. These materials not only broaden the topological classification of matter but also provide a condensed matter realization of various relativistic particles and phenomena previously discussed mainly in high energy physics. Weyl semimetals host massless, chiral, low-energy excitations in the bulk electronic band structure, whereas a symmetry protected pair of Weyl fermions gives rise to massless Dirac fermions. Read More

In this paper, we study the stochastic combinatorial multi-armed bandit (CMAB) framework that allows a general nonlinear reward function, whose expected value may not depend only on the means of the input random variables but possibly on the entire distributions of these variables. Our framework enables a much larger class of reward functions such as the $\max()$ function and nonlinear utility functions. Existing techniques relying on accurate estimations of the means of random variables, such as the upper confidence bound (UCB) technique, do not work directly on these functions. Read More

Direction-of-arrival (DOA) estimation refers to the process of retrieving the direction information of several electromagnetic waves/sources from the outputs of a number of receiving antennas that form a sensor array. DOA estimation is a major problem in array signal processing and has wide applications in radar, sonar, wireless communications, etc. With the development of sparse representation and compressed sensing, the last decade has witnessed a tremendous advance in this research topic. Read More

We propose to utilize the sub-system fidelity (SSF), defined by comparing a pair of reduced density matrices derived from the degenerate ground states, to identify and/or characterize symmetry protected topological (SPT) states in one-dimensional interacting many-body systems. The SSF tells whether two states are locally indistinguishable (LI) by measurements within a given sub-system. Starting from two polar states (states that could be distinguished on either edge), the other combinations of these states can be mapped onto a Bloch sphere. Read More

Recent observations have suggested that there is water ice present on the surfaces of 24 Themis and 1 Ceres. We present upper limits on the H$_2$O production rate on these bodies derived using a search for [OI]6300 Angstrom emission. For Themis, the water production is less than 4. Read More

We explore connections among the regional proximal relation, the asymptotic relation and the distal relation for a topological dynamical system with the shadowing property, and show that if a Devaney chaotic system has the shadowing property then it is distributionally chaotic. Read More

We study the possible superconducting pairing symmetry mediated by spin and charge fluctuations on the honeycomb lattice using the extended Hubbard model and the random-phase-approximation method. From $2\%$ to $20\%$ doping levels, a spin-singlet $d_{x^{2}-y^{2}}+id_{xy}$-wave is shown to be the leading superconducting pairing symmetry when only the on-site Coulomb interaction $U$ is considered, with the gap function being a mixture of the nearest-neighbor and next-nearest-neighbor pairings. When the offset of the energy level between the two sublattices exceeds a critical value, the most favorable pairing is a spin-triplet $f$-wave which is mainly composed of the next-nearest-neighbor pairing. Read More

AE Aquarii (AE Aqr) is a cataclysmic binary hosting one of the fastest rotating (P$_{\rm spin}$ = 33.08 s) white dwarfs known. Based on seven years of Fermi Large Area Telescope (LAT) Pass 8 data, we report on a deep search for gamma-ray emission from AE Aqr. Read More

Fundamental insight into the nature of the quantum phase transition from a superconductor to an insulator in two dimensions, or from one plateau to the next or to an insulator in quantum Hall effect, has been revealed through the study of its scaling behavior. Here, we report on the experimental observation of a quantum phase transition from a quantum-anomalous-Hall (QAH) insulator to an Anderson insulator in a magnetic topological insulator by tuning the chemical potential. Our experiment demonstrates the existence of scaling behavior from which we extract the critical exponent for this quantum phase transition. Read More

In the classical best arm identification (Best-$1$-Arm) problem, we are given $n$ stochastic bandit arms, each associated with a reward distribution with an unknown mean. We would like to identify the arm with the largest mean with probability at least $1-\delta$, using as few samples as possible. Understanding the sample complexity of Best-$1$-Arm has attracted significant attention since the last decade. Read More

To segment a sequence of independent random variables at an unknown number of change-points, we introduce new procedures that are based on thresholding the likelihood ratio statistic. We also study confidence regions based on the likelihood ratio statistic for the changepoints and joint confidence regions for the change-points and the parameter values. Applications to segment an array CGH analysis of the BT474 cell line are discussed. Read More

Based on more than seven years of Fermi Large Area Telescope (LAT) Pass 8 data, we report on a detailed analysis of the bright gamma-ray pulsar (PSR) J0007+7303. We confirm that PSR J0007+7303 is significantly detected as a point source also during the off-peak phases with a TS value of 262 ($\sim$ 16 $\sigma$). In the description of PSR J0007+7303 off-peak spectrum, a power law with an exponential cutoff at 2. Read More

The humidity sensitivity of n-type strontium-hexaferrite semiconductors, X-type (Sr2Co2Fe28O46) and Z-type (Sr3Co2Fe24O41), are investigated at room temperature. The contact and reactions between water and material surface are demonstrated considering the formation of oxide ion vacancy, singly-ionized / fully-ionized oxide ion vacancy, and the chemisorbed / physisorbed / condensed water. An impedance spectra model is proposed considering the material-electrode interface, interior material, grain boundary, absorbed water and Warburg response. Read More

Solving geometric optimization problems over uncertain data have become increasingly important in many applications and have attracted a lot of attentions in recent years. In this paper, we study two important geometric optimization problems, the $k$-center problem and the $j$-flat-center problem, over stochastic/uncertain data points in Euclidean spaces. For the stochastic $k$-center problem, we would like to find $k$ points in a fixed dimensional Euclidean space, such that the expected value of the $k$-center objective is minimized. Read More

Characterizing driving styles of human drivers using vehicle sensor data, e.g., GPS, is an interesting research problem and an important real-world requirement from automotive industries. Read More

We report on the search for gamma-ray emission from 20 magnetars using 6 years of Fermi, Large Area Telescope (LAT) observations. No significant evidence for gamma-ray emission from any of the currently-known magnetars is found. We derived the most stringent upper limits to date on the 0. Read More

For every positive integer $n\geq 2$, we introduce the concept of measure-theoretic $n$-sensitivity for measure-theoretic dynamical systems via finite measurable partitions, and show that an ergodic system is measure-theoretically $n$-sensitive but not $(n+1)$-sensitive if and only if its maximal pattern entropy is $\log n$. Read More

Choosing a good location when opening a new store is crucial for the future success of a business. Traditional methods include offline manual survey, which is very time consuming, and analytic models based on census data, which are un- able to adapt to the dynamic market. The rapid increase of the availability of big data from various types of mobile devices, such as online query data and offline positioning data, provides us with the possibility to develop automatic and accurate data-driven prediction models for business store placement. Read More

The best arm identification problem (BEST-1-ARM) is the most basic pure exploration problem in stochastic multi-armed bandits. The problem has a long history and attracted significant attention for the last decade. However, we do not yet have a complete understanding of the optimal sample complexity of the problem: The state-of-the-art algorithms achieve a sample complexity of $O(\sum_{i=2}^{n} \Delta_{i}^{-2}(\ln\delta^{-1} + \ln\ln\Delta_i^{-1}))$ ($\Delta_{i}$ is the difference between the largest mean and the $i^{th}$ mean), while the best known lower bound is $\Omega(\sum_{i=2}^{n} \Delta_{i}^{-2}\ln\delta^{-1})$ for general instances and $\Omega(\Delta^{-2} \ln\ln \Delta^{-1})$ for the two-arm instances. Read More

We study the pure exploration problem subject to a matroid constraint (Best-Basis) in a stochastic multi-armed bandit game. In a Best-Basis instance, we are given $n$ stochastic arms with unknown reward distributions, as well as a matroid $\mathcal{M}$ over the arms. Let the weight of an arm be the mean of its reward distribution. Read More

We address the issue of visual saliency from three perspectives. First, we consider saliency detection as a frequency domain analysis problem. Second, we achieve this by employing the concept of {\it non-saliency}. Read More

It is an open problem whether Yao-Yao graphs $\mathsf{YY}_k$ (also known as sparse-Yao graphs) are all spanners when the integer parameter $k$ is large enough. In this paper we show that, for any integer $k\geq 42$, the Yao-Yao graph $\mathsf{YY}_{2k}$ is a $t_k$-spanner, with stretch factor $t_k=6.03+O(k^{-1})$ when $k$ tends to infinity. Read More

The Heisenberg-Robertson uncertainty relation quantitatively expresses the impossibility of jointly sharp preparation of incompatible observables. However it does not capture the concept of incompatible observables because it can be trivial even for two incompatible observables. We experimentally demonstrate the new stronger uncertainty relations proposed by Maccone and Pati [Phys. Read More

We investigated theoretically the exciton-plasmon coupling effects on the population dynamics and the absorption properties of a hybrid nanosystem composed of a metal nanoparticle (MNP) and a V-type three level semiconductor quantum dot (SQD), which are created by the interaction with the induced dipole moments in the SQD and the MNP, respectively. Excitons of the SQD and the plasmons of the MNP in such a hybrid nanosystem could be coupled strongly or weakly to demonstrate novel properties of the hybrid system. Our results show that the nonlinear optical response of the hybrid nanosystem can be greatly enhanced or depressed due to the exciton-plasmon couplings. Read More