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Gas-phase microresonator-based comb spectroscopy without an external pump laserJun 04 2018We present a novel approach to realize microresonator-comb-based high resolution spectroscopy that combines a fiber-laser cavity with a microresonator. Although the spectral resolution of a chip-based comb source is typically limited by the free spectral ... More

Counter-rotating cavity solitons in a silicon nitride microresonatorNov 13 2017We demonstrate the generation of counter-rotating cavity solitons in a silicon nitride microresonator using a fixed, single-frequency laser. We demonstrate a dual 3-soliton state with a difference in the repetition rates of the soliton trains that can ... More

Superradiant instabilities in a $D$-dimensional small Reissner-Nordström-Anti-de Sitter black holeMar 20 2014We investigate the superradiant instability for a charged scalar field in a $D$-dimensional small Reissner-Nordstr\"om-Anti-de Sitter (RN-AdS) black hole. Firstly, we solve the charged Klein-Gordon equation analytically by a matching method. We show that ... More

Visible Nonlinear PhotonicsJul 10 2019Over the past decade, remarkable advances have been realized in chip-based nonlinear photonic devices for classical and quantum applications in the near- and mid-infrared regimes. However, few demonstrations have been realized in the visible and near-visible ... More

Modelocked mid-infrared frequency combs in a silicon microresonatorApr 21 2016Mid-infrared (mid-IR) frequency combs have broad applications in molecular spectroscopy and chemical/biological sensing. Recently developed microresonator-based combs in this wavelength regime could enable portable and robust devices using a single-frequency ... More

Coherent, directional supercontinuum via cascaded dispersive wave generationAug 11 2017We demonstrate a novel approach to producing coherent, directional supercontinuum via cascaded dispersive wave generation. By pumping in the normal group-velocity dispersion regime, pulse compression of the first dispersive wave results in the generation ... More

Dynamics of mode-coupling-induced microresonator frequency combs in normal dispersionOct 04 2016We experimentally and theoretically investigate the dynamics of microresonator-based frequency comb generation assisted by mode coupling in the normal group-velocity dispersion (GVD) regime. We show that mode coupling can initiate intracavity modulation ... More

Microresonator-based high-resolution gas spectroscopyJul 12 2017In recent years, microresonator-based optical frequency combs have created up opportunities for developing a spectroscopy laboratory on a chip due to its broadband emission and high comb power. However, with mode spacings typically in the range of 10 ... More

Silicon-chip-based mid-infrared dual-comb spectroscopyOct 04 2016On-chip spectroscopy that could realize real-time fingerprinting with label-free and high-throughput detection of trace molecules is one of the 'holy grails" of sensing. Such miniaturized spectrometers would greatly enable applications in chemistry, bio-medicine, ... More

Coherent two-octave-spanning supercontinuum generation in lithium-niobate waveguidesJan 30 2019We demonstrate coherent supercontinuum generation (SCG) in a monolithically integrated lithium-niobate waveguide, under the presence of second- and third-order nonlinear effects. We achieve more than two octaves of optical bandwidth in a 0.5-cm-long waveguide ... More

Silicon-chip-based mid-infrared dual-comb spectroscopyOct 04 2016May 01 2017On-chip spectroscopy that could realize real-time fingerprinting with label-free and high-throughput detection of trace molecules is one of the 'holy grails" of sensing. Such miniaturized spectrometers would greatly enable applications in chemistry, bio-medicine, ... More

Raman-assisted coherent, mid-infrared frequency combs in silicon microresonatorsApr 21 2016We demonstrate the first low-noise mid-IR frequency comb source using a silicon microresonator. Our observation of strong Raman scattering lines in the generated comb suggests that Raman and four-wave mixing interactions play a role in assisting the transition ... More

Low-Loss Silicon Platform for Broadband Mid-Infrared PhotonicsMar 10 2017Broadband mid-infrared (mid-IR) spectroscopy applications could greatly benefit from today's well-developed, highly scalable silicon photonics technology; however, this platform lacks broadband transparency due to its reliance on absorptive silicon dioxide ... More

Competition between Raman and Kerr effects in microresonator comb generationMay 04 2017We investigate the effects of Raman and Kerr gain in crystalline microresonators and determine the conditions required to generate modelocked frequency combs. We show theoretically that strong, narrowband Raman gain determines a maximum microresonator ... More

Dual-pumped degenerate Kerr oscillator in a silicon nitride microresonatorSep 26 2015Oct 17 2015We demonstrate a degenerate parametric oscillator in a silicon-nitride microresonator. We use two frequency-detuned pump waves to perform parametric four-wave mixing and operate in the normal group-velocity dispersion regime to produce signal and idler ... More

Linear Quadratic Mean Field Games -- Part I: The Asymptotic Solvability ProblemNov 01 2018This paper investigates the so-called asymptotic solvability problem in linear quadratic (LQ) mean field games. The model has asymptotic solvability if for all sufficiently large population sizes, the corresponding game has a set of feedback Nash strategies ... More

Linear quadratic mean field games: Asymptotic solvability and relation to the fixed point approachMar 20 2019May 21 2019Mean field game theory has been developed largely following two routes. One of them, called the direct approach, starts by solving a large-scale game and next derives a set of limiting equations as the population size tends to infinity. The second route ... More

Maxwell perturbations on Kerr-anti-de Sitter: quasinormal modes, superradiant instabilities and vector cloudsDec 07 2015Scalar and gravitational perturbations on Kerr-anti-de Sitter (Kerr-AdS) black holes have been addressed in the literature and have been shown to exhibit a rich phenomenology. In this paper we complete the analysis of bosonic fields on this background ... More

Linear quadratic mean field games: Asymptotic solvability and relation to the fixed point approachMar 20 2019Mean field game theory has been developed largely following two routes. One of them, called the direct approach, starts by solving a large-scale game and next derives a set of limiting equations as the population size tends to infinity. The second route ... More

Breather soliton dynamics in microresonatorsSep 06 2016The generation of temporal cavity solitons in microresonators results in low-noise optical frequency combs which are critical for applications in spectroscopy, astronomy, navigation or telecommunications. Breather solitons also form an important part ... More

Supercontinuum generation in angle-etched diamond waveguidesJun 20 2019We experimentally demonstrate on-chip supercontinuum generation in the visible region in angle etched diamond waveguides. We measure an output spectrum spanning 670 nm to 920 nm in a 5mm long waveguide using 100 fs pulses with 187 pJ of incident pulse ... More

A General Decision Theory for Huber's $ε$-Contamination ModelNov 13 2015Today's data pose unprecedented challenges to statisticians. It may be incomplete, corrupted or exposed to some unknown source of contamination. We need new methods and theories to grapple with these challenges. Robust estimation is one of the revived ... More

Self-assembling two-dimensional quasicrystals in simple systems of monodisperse soft-core disksMar 26 2017In previous approaches to form quasicrystals, multiple competing length scales involved in particle size, shape or interaction potential are believed to be necessary. It is unexpected that quasicrystals can be self-assembled by monodisperse, isotropic ... More

Silicon-Chip Mid-Infrared Frequency Comb GenerationAug 05 2014Optical frequency combs represent a revolutionary technology for high precision spectroscopy due to their narrow linewidths and precise frequency spacing. Generation of such combs in the mid-infrared (IR) spectral region (2-20 um) is of great interest ... More

Domain Adaptive Neural Networks for Object RecognitionSep 21 2014We propose a simple neural network model to deal with the domain adaptation problem in object recognition. Our model incorporates the Maximum Mean Discrepancy (MMD) measure as a regularization in the supervised learning to reduce the distribution mismatch ... More

An Adaptive Clipping Approach for Proximal Policy OptimizationApr 17 2018Very recently proximal policy optimization (PPO) algorithms have been proposed as first-order optimization methods for effective reinforcement learning. While PPO is inspired by the same learning theory that justifies trust region policy optimization ... More

Posterior Contraction Rates of the Phylogenetic Indian Buffet ProcessesJul 31 2013May 19 2015By expressing prior distributions as general stochastic processes, nonparametric Bayesian methods provide a flexible way to incorporate prior knowledge and constrain the latent structure in statistical inference. The Indian buffet process (IBP) is such ... More

n-DBI gravity, maximal slicing and the Kerr geometryJan 06 2013Recently, in arXiv:1110.0832, we have established that solutions of Einstein's gravity admitting foliations with a certain geometric condition are also solutions of n-DBI gravity, arXiv:1109.1468. Here we observe that, in vacuum, the required geometric ... More

Evolving Deep Convolutional Neural Networks for Image ClassificationOct 30 2017Oct 31 2017Evolutionary computation methods have been successfully applied to neural networks since two decades ago, while those methods cannot scale well to the modern deep neural networks due to the complicated architectures and large quantities of connection ... More

Robust Covariance and Scatter Matrix Estimation under Huber's Contamination ModelJun 01 2015Jun 12 2017Covariance matrix estimation is one of the most important problems in statistics. To accommodate the complexity of modern datasets, it is desired to have estimation procedures that not only can incorporate the structural assumptions of covariance matrices, ... More

Second-order phase transition of Kehagias-Sfetsos black hole in deformed Hǒrava-Lifshitz gravityDec 03 2010Dec 14 2010We study the second-order phase transition (SOPT) for the spherically symmetric Kehagias-Sfetsos (KS) black hole in the deformed H\v{o}rava-Lifshitz gravity by applying the methods of equilibrium and non-equilibrium fluctuations. We find that, although ... More

Can Genetic Programming Do Manifold Learning Too?Feb 08 2019Exploratory data analysis is a fundamental aspect of knowledge discovery that aims to find the main characteristics of a dataset. Dimensionality reduction, such as manifold learning, is often used to reduce the number of features in a dataset to a manageable ... More

Automatically Evolving CNN Architectures Based on BlocksOct 28 2018The performance of Convolutional Neural Networks (CNNs) highly relies on their architectures. In order to design a CNN with promising performance, extended expertise in both CNNs and the investigated problem is required, which is not necessarily held ... More

Particle energy and Hawking temperatureApr 28 2009Some authors have recently found that the tunneling approach gives a different Hawking temperature for a Schwarzschild black hole in a different coordinate system. In this paper, we find that to work out the Hawking temperature in a different coordinate ... More

Dirac perturbations on Schwarzschild-Anti-de Sitter spacetimes: Generic boundary conditions and new quasinormal modesOct 28 2017Nov 23 2017We study Dirac quasinormal modes of Schwarzschild-Anti-de Sitter (Schwarzschild-AdS) black holes, following the generic principle for allowed boundary conditions proposed in \cite{PhysRevD.92.124006}. After deriving the equations of motion for Dirac fields ... More

Robust Covariance Matrix Estimation via Matrix DepthJun 01 2015Jul 30 2015Covariance matrix estimation is one of the most important problems in statistics. To accommodate the complexity of modern datasets, it is desired to have estimation procedures that not only can incorporate the structural assumptions of covariance matrices, ... More

A General Decision Theory for Huber's $ε$-Contamination ModelNov 13 2015Jan 16 2017Today's data pose unprecedented challenges to statisticians. It may be incomplete, corrupted or exposed to some unknown source of contamination. We need new methods and theories to grapple with these challenges. Robust estimation is one of the revived ... More

Effective Exploration for Deep Reinforcement Learning via Bootstrapped Q-Ensembles under Tsallis Entropy RegularizationSep 02 2018Sep 05 2018Recently deep reinforcement learning (DRL) has achieved outstanding success on solving many difficult and large-scale RL problems. However the high sample cost required for effective learning often makes DRL unaffordable in resource-limited applications. ... More

Generating Redundant Features with Unsupervised Multi-Tree Genetic ProgrammingFeb 02 2018Mar 20 2018Recently, feature selection has become an increasingly important area of research due to the surge in high-dimensional datasets in all areas of modern life. A plethora of feature selection algorithms have been proposed, but it is difficult to truly analyse ... More

Change Point Analysis of Histone Modifications Reveals Epigenetic Blocks Linking to Physical DomainsSep 20 2013May 09 2014Histone modification is a vital epigenetic mechanism for transcriptional control in eukaryotes. High-throughput techniques have enabled whole-genome analysis of histone modifications in recent years. However, most studies assume one combination of histone ... More

Scatter Component Analysis: A Unified Framework for Domain Adaptation and Domain GeneralizationOct 15 2015Jul 26 2016This paper addresses classification tasks on a particular target domain in which labeled training data are only available from source domains different from (but related to) the target. Two closely related frameworks, domain adaptation and domain generalization, ... More

Embedding Learning Through Multilingual Concept InductionJan 21 2018Jun 27 2018We present a new method for estimating vector space representations of words: embedding learning by concept induction. We test this method on a highly parallel corpus and learn semantic representations of words in 1259 different languages in a single ... More

Using Aggregated Relational Data to feasibly identify network structure without network dataMar 12 2017Aug 02 2018Social network data is often prohibitively expensive to collect, limiting empirical network research. Typical economic network mapping requires (1) enumerating a census, (2) eliciting the names of all network links for each individual, (3) matching the ... More

Automatically Evolving CNN Architectures Based on BlocksOct 28 2018Mar 10 2019The performance of Convolutional Neural Networks (CNNs) highly relies on their architectures. In order to design a CNN with promising performance, extended expertise in both CNNs and the investigated problem is required, which is not necessarily held ... More

Spin Seebeck Effect in Asymmetric Four-Terminal Systems with Rashba Spin-Orbit CouplingAug 11 2014We propose a new type of the spin Seebeck effect (SSE) emerging from the Rashba spin-orbit coupling in asymmetric four-terminal electron systems. This system generates spin currents or spin voltages along the longitudinal direction parallel to the temperature ... More

Domain Generalization for Object Recognition with Multi-task AutoencodersAug 31 2015The problem of domain generalization is to take knowledge acquired from a number of related domains where training data is available, and to then successfully apply it to previously unseen domains. We propose a new feature learning algorithm, Multi-Task ... More

Role of disorder in determining the vibrational properties of mass-spring networksMar 01 2017By introducing four fundamental types of disorders into a two-dimensional triangular lattice separately, we determine the role of each type of disorder in the vibration of the resulting mass-spring networks. We are concerned mainly with the origin of ... More

Towards Accurate Deceptive Opinion Spam Detection based on Word Order-preserving CNNNov 25 2017Mar 19 2018Nowadays, deep learning has been widely used. In natural language learning, the analysis of complex semantics has been achieved because of its high degree of flexibility. The deceptive opinions detection is an important application area in deep learning ... More

A Particle Swarm Optimization-based Flexible Convolutional Auto-Encoder for Image ClassificationDec 13 2017Nov 11 2018Convolutional auto-encoders have shown their remarkable performance in stacking to deep convolutional neural networks for classifying image data during past several years. However, they are unable to construct the state-of-the-art convolutional neural ... More

A Hybrid Differential Evolution Approach to Designing Deep Convolutional Neural Networks for Image ClassificationAug 20 2018Aug 22 2018Convolutional Neural Networks (CNNs) have demonstrated their superiority in image classification, and evolutionary computation (EC) methods have recently been surging to automatically design the architectures of CNNs to save the tedious work of manually ... More

Marginal scalar and Proca clouds around Reissner-Nordström black holesJun 13 2014Massive scalar test fields around Kerr black holes can form quasi-bound states with complex frequencies. Some of these states decay in time, but some others -- in the superradiant regime -- grow, causing a superradiant instability. Precisely at the threshold ... More

Automatically Designing CNN Architectures Using Genetic Algorithm for Image ClassificationAug 11 2018Convolutional Neural Networks (CNNs) have gained a remarkable success on many real-world problems in recent years. However, the performance of CNNs is highly relied on their architectures. For some state-of-the-art CNNs, their architectures are hand-crafted ... More

A direct approach to false discovery rates by decoy permutationsApr 23 2018The current approaches to false discovery rates (FDRs) in multiple hypothesis testing are usually based on the null distribution of a test statistic. However, all types of null distributions, including the theoretical, permutation-based and empirical ... More

Sparse CCA via Precision Adjusted Iterative ThresholdingNov 24 2013Sparse Canonical Correlation Analysis (CCA) has received considerable attention in high-dimensional data analysis to study the relationship between two sets of random variables. However, there has been remarkably little theoretical statistical foundation ... More

Automatically Designing CNN Architectures Using Genetic Algorithm for Image ClassificationAug 11 2018Apr 04 2019Convolutional Neural Networks (CNNs) have gained a remarkable success on many real-world problems in recent years. However, the performance of CNNs is highly relied on their architectures. For some state-of-the-art CNNs, their architectures are hand-crafted ... More

Hawking radiation for a Proca field in D dimensions II: charged field in a brane charged black holeDec 10 2012Feb 26 2013We generalise our first analysis of the wave equation for a massive vector boson in the background of a D-dimensional Schwarzschild black hole, by adding charge both to the field and the black hole, on the 3+1 dimensional Standard Model brane. A detailed ... More

Hawking radiation for a Proca field in D-dimensionsOct 11 2011We study the wave equation of a massive vector boson in the background of a D-dimensional Schwarzschild black hole. The mass term introduces a coupling between two physical degrees of freedom of the field, and we solve the resulting system of ODEs numerically, ... More

Maxwell perturbations on asymptotically anti-de Sitter spacetimes: Generic boundary conditions and a new branch of quasinormal modesOct 15 2015Dec 02 2015Perturbations of asymptotically Anti-de-Sitter (AdS) spacetimes are often considered by imposing field vanishing boundary conditions (BCs) at the AdS boundary. Such BCs, of Dirichlet-type, imply a vanishing energy flux at the boundary, but the converse ... More

Density affects the nature of the hexatic-liquid transition in two-dimensional melting of core-softened systemsMay 03 2016Aug 18 2016We find that both continuous and discontinuous hexatic-liquid transitions can happen in the melting of two-dimensional solids of soft-core disks. For three typical model systems, Hertzian, harmonic, and Gaussian-core models, we observe the same scenarios. ... More

First laws of thermodynamics in IR Modified Hǒrava-Lifshitz gravityDec 24 2009Apr 23 2010We study the first law of thermodynamics in IR modified H\v{o}rava-Lifshitz spacetime. Based on the Bekenstein-Hawking entropy, we obtain the integral formula and the differential formula of the first law of thermodynamics for the Kehagias-Sfetsos black ... More

A Hybrid GA-PSO Method for Evolving Architecture and Short Connections of Deep Convolutional Neural NetworksMar 10 2019Image classification is a difficult machine learning task, where Convolutional Neural Networks (CNNs) have been applied for over 20 years in order to solve the problem. In recent years, instead of the traditional way of only connecting the current layer ... More

Evolving Deep Neural Networks by Multi-objective Particle Swarm Optimization for Image ClassificationMar 21 2019Apr 22 2019In recent years, convolutional neural networks (CNNs) have become deeper in order to achieve better classification accuracy in image classification. However, it is difficult to deploy the state-of-the-art deep CNNs for industrial use due to the difficulty ... More

Evolving Deep Convolutional Neural Networks by Variable-length Particle Swarm Optimization for Image ClassificationMar 17 2018Convolutional neural networks (CNNs) are one of the most effective deep learning methods to solve image classification problems, but the best architecture of a CNN to solve a specific problem can be extremely complicated and hard to design. This paper ... More

Thermal Boundary Conductance Across Metal-Nonmetal Interfaces: Effects of Electron-Phonon Coupling both in Metal and at InterfaceDec 08 2014We theoretically investigate the thermal boundary conductance across metal-nonmetal interfaces in the presence of the electron-phonon coupling not only in metal but also at interface. The thermal energy can be transferred from metal to nonmetal via three ... More

Null-free False Discovery Rate Control Using Decoy Permutations for Multiple TestingApr 23 2018Jun 12 2019The current approaches to false discovery rate (FDR) control in multiple hypothesis testing are usually based on the null distribution of a test statistic. However, all types of null distributions, including the theoretical, permutation-based and empirical ... More

Evolving Deep Convolutional Neural Networks for Image ClassificationOct 30 2017Mar 10 2019Evolutionary computation methods have been successfully applied to neural networks since two decades ago, while those methods cannot scale well to the modern deep neural networks due to the complicated architectures and large quantities of connection ... More

GA-Novo: De Novo Peptide Sequencing via Tandem Mass Spectrometry using Genetic AlgorithmFeb 03 2019Proteomics is the large-scale analysis of the proteins. The common method for identifying proteins and characterising their amino acid sequences is to digest the proteins into peptides, analyse the peptides using mass spectrometry and assign the resulting ... More

Hierarchically porous Ni monolith@branch-structured NiCo2O4 for high energy density supercapacitorsApr 03 2016NiCo2O4 of varying nanostrucutures ranging from nanowires, nanoplates to nano-plates@nanowires were successfully grown on microporous (MP) Ni foams via one-step hydrothermal process. The investigation of electrochemical capacitance favors Ni-Co2O4 of ... More

Asymptotically Normal and Efficient Estimation of Covariate-Adjusted Gaussian Graphical ModelSep 23 2013A tuning-free procedure is proposed to estimate the covariate-adjusted Gaussian graphical model. For each finite subgraph, this estimator is asymptotically normal and efficient. As a consequence, a confidence interval can be obtained for each edge. The ... More

Decorated marked surfaces II: Intersection numbers and dimensions of HomsNov 14 2014May 28 2015We study the 3-Calabi-Yau categories $\mathcal{D}$ arising from quivers with potential associated to a decorated marked surface $\mathbf{S}_\bigtriangleup$ introduced by the first author. We prove two conjectures in the prequel, that under a bijection ... More

Finite presentations for spherical/braid twist groups from decorated marked surfacesMar 29 2017Oct 29 2018We give a finite presentation for the braid twist group of a decorated surface. If the decorated surface arises from a triangulated marked surface without punctures, we obtain a finite presentation for the spherical twist group of the associated 3-Calabi-Yau ... More

Surgery on links with unknotted components and three-manifoldsJan 22 2008It is shown that any closed three-manifold M obtained by integral surgery on a knot in the three-sphere can always be constructed from integral surgeries on a 3-component link L with each component being an unknot in the three-sphere. It is also interesting ... More

Cluster categories for marked surfaces: punctured caseOct 31 2013May 24 2015We study the cluster categories arising from marked surfaces (with punctures and non-empty boundaries). By constructing skewed-gentle algebras, we show that there is a bijection between tagged curves and string objects. Applications include interpreting ... More

On the existence of natural self-oscillation of a free electronJan 11 2012Jan 27 2013The possibility of the existence of natural self-oscillation of a free electron is suggested. This oscillation depends on the interaction of the electron with its own electromagnetic fields. Suitable standing wave solutions of the electromagnetic fields ... More

Weil asymptotic formula for the Laplacian on domains with rough boundariesOct 07 2003We study asymptotic distribution of eigenvalues of the Laplacian on a bounded domain in $ \R^n$. Our main results include an explicit remainder estimate in the Weyl formula for the Dirichlet Laplacian on an arbitrary bounded domain, sufficient conditions ... More

Asymptotic properties of one-step weighted $M$-estimators and applications to some regression problemsMay 11 2015Jul 04 2015We study asymptotic behavior of one-step weighted $M$-estimators based on samples from arrays of not necessarily identically distributed random variables and representing explicit approximations to the corresponding consistent weighted $M$-estimators. ... More

Asymptotic properties of one-step $M$-estimators based on nonidentically distributed observations with applications to nonlinear regression problemsMar 11 2015Apr 11 2016We study asymptotic behavior of one-step $M$-estimators based on samples from arrays of not necessarily identically distributed random variables and representing explicit approximations to the corresponding consistent $M$-estimators. These estimators ... More

Cluster categories for marked surfaces: punctured caseOct 31 2013Jan 08 2017We study the cluster categories arising from marked surfaces (with punctures and non-empty boundaries). By constructing skewed-gentle algebras, we show that there is a bijection between tagged curves and string objects. Applications include interpreting ... More

Decorated marked surfaces II: Intersection numbers and dimensions of HomsNov 14 2014Jun 02 2017We study the 3-Calabi-Yau categories $\mathcal{D}$ arising from quivers with potential associated to a decorated marked surface $\mathbf{S}_\bigtriangleup$ introduced by the first author. We prove two conjectures in the prequel, that under a bijection ... More

Turbulent Flame Speeds of G-equation Models in Unsteady Cellular FlowsOct 05 2012We perform a computationl study of front speeds of G-equation models in time dependent cellular flows. The G-equations arise in premixed turbulent combustion, and are Hamilton-Jacobi type level set partial differential equations (PDEs). The curvature-strain ... More

A Numerical Study of Turbulent Flame Speeds of Curvature and Strain G-equations in Cellular FlowsFeb 28 2012We study front speeds of curvature and strain G-equations arising in turbulent combustion. These G-equations are Hamilton-Jacobi type level set partial differential equations (PDEs) with non-coercive Hamiltonians and degenerate nonlinear second order ... More

Asymptotics for turbulent flame speeds of the viscous G-equation enhanced by cellular and shear flowsJul 20 2010Aug 03 2010G-equations are well-known front propagation models in turbulent combustion and describe the front motion law in the form of local normal velocity equal to a constant (laminar speed) plus the normal projection of fluid velocity. In level set formulation, ... More

Thread Batching for High-performance Energy-efficient GPU Memory DesignJun 13 2019Massive multi-threading in GPU imposes tremendous pressure on memory subsystems. Due to rapid growth in thread-level parallelism of GPU and slowly improved peak memory bandwidth, the memory becomes a bottleneck of GPU's performance and energy efficiency. ... More

High-speed Railway Fastener Detection and Localization SystemJul 02 2019Railway transportation is the artery of China's national economy and plays an important role in the development of today's society. Due to the late start of China's railway security inspection technology, the current railway security inspection tasks ... More

Communication: Words and Conceptual SystemsJul 29 2015Dec 04 2015Words (phrases or symbols) play a key role in human life. Word (phrase or symbol) representation is the fundamental problem for knowledge representation and understanding. A word (phrase or symbol) usually represents a name of a category. However, it ... More

Ising antiferromagnet on the 2-uniform latticesJun 27 2016The antiferromagnetic Ising model is investigated on the 20 2-uniform lattices using the Monte-Carlo method based on the Wang-Landau algorithm and the Metropolis algorithm to study the geometric frustration effect systematically. Based on the specific ... More

The Discord-like Correlation of Bipartite CoherenceNov 01 2016Nov 08 2016Quantum discord is a measure of quantum correlation by the the mutual information difference between the state and the output state after the local von Neumann measurement, where the mutual information contained in a bipartite state is defined as the ... More

An optimization problem in heat conduction with minimal temperature constraint, interior heating and exterior insulationApr 28 2016We show the existence and optimal regularity of the optimal temperature configuration in a problem in heat conduction with minimal temperature constraint, interior heating and exterior insulation. Regularity of the two free boundaries is also studied. ... More

Unique continuation for fractional orders of elliptic equationsSep 06 2016Sep 07 2016We establish the strong unique continuation property of fractional orders of linear elliptic equations with $C^{1,\alpha}$-coefficients by establishing monotonicity of some Almgren-type frequency functional via an extension procedure of Stinga and Stinga-Torrea. ... More

A Bishop type inequality on metric measure spaces with Ricci curvature bounded belowMar 14 2016We define a Bishop-type inequality on metric measure spaces with Riemannian curvature-dimension condition. The main result in this short article is that any RCD spaces with the Bishop-type inequalities possess only one regular set in not only the measure ... More

On convex hull of Gaussian samplesApr 27 2010Let $X_i = {X_i(t), t \in T}$ be i.i.d. copies of a centered Gaussian process $X = {X(t), t \in T}$ with values in $\mathbb{R}^d$ defined on a separable metric space $T.$ It is supposed that $X$ is bounded. We consider the asymptotic behaviour of convex ... More

The Importance of being OddDec 04 2000Jan 03 2001In this letter I consider mainly a finite XXZ spin chain with periodic boundary conditions and \bf{odd} \rm number of sites. This system is described by the Hamiltonian $H_{xxz}=-\sum_{j=1}^{N}\{\sigma_j^{x}\sigma_{j+1}^{x} +\sigma_j^{y}\sigma_{j+1}^{y} ... More

Global weak solutions to the Navier-Stokes-Vlasov equationsApr 30 2012Nov 27 2012In this paper, the system of particles coupled with fluid is considered. The particles are described by a Vlasov equation, and the fluid is governed by a forced Navier-Stokes equations. The interaction with fluid phase governed by Navier-Stokes equations ... More

A High-Order WENO-based Staggered Godunov-type Scheme with Constrained Transport for Force-free ElectrodynamicsOct 18 2010The force-free (or low inertia) limit of magnetohydrodynamics (MHD) can be applied to many astrophysical objects, including black holes, neutron stars, and accretion disks, where the electromagnetic field is so strong that the inertia and pressure of ... More

Analysis of Massive Heterogeneous Temporal-Spatial Data with 3D Self-Organizing Map and Time VectorSep 27 2016Self-organizing map(SOM) have been widely applied in clustering, this paper focused on centroids of clusters and what they reveal. When the input vectors consists of time, latitude and longitude, the map can be strongly linked to physical world, providing ... More

An ExpTime Procedure for Description Logic $\mathcal{ALCQI}$ (Draft)Mar 12 2007Mar 18 2007A worst-case ExpTime tableau-based decision procedure is outlined for the satisfiability problem in $\mathcal{ALCQI}$ w.r.t. general axioms.

Conformal equations that are not Virasoro or Weyl invariantFeb 14 2019While the argument by Zamolodchikov and Polchinski suggests global conformal invariance implies Virasoro invariance in two-dimensional unitary conformal field theories with discrete dilatation spectrum, it is not the case in more general situations without ... More

The Templates of Nonsingular Smale Flows on Three ManifoldsMar 11 2011In this paper, we first discuss some connections between template theory and the description of basic sets of Smale flows on 3-manifolds due to F. B\'eguin and C. Bonatti. The main tools we use are symbolic dynamics, template moves and some combinatorial ... More

Affine Hirsch foliations on 3-manifoldsApr 13 2016Apr 14 2016This paper is devoted to discussing affine Hirsch foliations on $3$-manifolds. First, we prove that up to isotopic leaf-conjugacy, every closed orientable $3$-manifold $M$ admits $0$, $1$ or $2$ affine Hirsch foliations. Then, we analysis the $3$-manifolds ... More

Cloud Computing framework for Computer Vision Research:An IntroductionFeb 06 2013Cloud computing offers the potential to help scientists to process massive number of computing resources often required in machine learning application such as computer vision problems. This proposal would like to show that which benefits can be obtained ... More