C. -H. Wu - The ARGO-YBJ Collaboration

C. -H. Wu
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C. -H. Wu
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The ARGO-YBJ Collaboration
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Computer Science - Distributed; Parallel; and Cluster Computing (5)
 
Mathematics - Optimization and Control (4)
 
Astrophysics of Galaxies (4)
 
High Energy Astrophysical Phenomena (4)
 
Statistics - Methodology (3)
 
Computer Science - Computer Vision and Pattern Recognition (3)
 
Quantum Physics (3)
 
Computer Science - Learning (3)
 
Computer Science - Networking and Internet Architecture (3)
 
Statistics - Machine Learning (3)
 
Physics - Mesoscopic Systems and Quantum Hall Effect (2)
 
Physics - Materials Science (2)
 
Mathematics - Geometric Topology (2)
 
Physics - Strongly Correlated Electrons (2)
 
Cosmology and Nongalactic Astrophysics (2)
 
Computer Science - Neural and Evolutionary Computing (2)
 
Mathematics - Dynamical Systems (2)
 
General Relativity and Quantum Cosmology (2)
 
Nuclear Experiment (2)
 
Physics - Instrumentation and Detectors (2)
 
Mathematics - Numerical Analysis (1)
 
Nuclear Theory (1)
 
Mathematical Physics (1)
 
Computer Science - Performance (1)
 
Mathematics - Mathematical Physics (1)
 
High Energy Physics - Theory (1)
 
Instrumentation and Methods for Astrophysics (1)
 
Physics - Space Physics (1)
 
Solar and Stellar Astrophysics (1)
 
Computer Science - Digital Libraries (1)
 
Physics - Physics and Society (1)
 
High Energy Physics - Phenomenology (1)
 
Computer Science - Computer Science and Game Theory (1)
 
High Energy Physics - Experiment (1)
 
Physics - Chemical Physics (1)
 
Physics - Optics (1)
 
Mathematics - Algebraic Topology (1)
 
Mathematics - Probability (1)
 
Computer Science - Artificial Intelligence (1)
 
Physics - Superconductivity (1)
 
Mathematics - Combinatorics (1)
 
Statistics - Theory (1)
 
Mathematics - Statistics (1)
 
Physics - Soft Condensed Matter (1)

Publications Authored By C. -H. Wu

High network communication cost for synchronizing gradients and parameters is the well-known bottleneck of distributed training. In this work, we propose TernGrad that uses ternary gradients to accelerate distributed deep learning in data parallelism. Our approach requires only three numerical levels {-1,0,1} which can aggressively reduce the communication time. Read More

Hexagonal boron nitride (h-BN) is a promising two-dimensional insulator with a large band gap and low density of charged impurities that is isostructural and isoelectronic with graphene. Here we report the chemical and atomic-scale structure of CVD-grown wafer-scale (~25 cm2) h-BN sheets ranging in thickness from 1-20 monolayers. Atomic-scale images of h-BN on Au and graphene/Au substrates obtained by scanning tunneling microscopy (STM) reveal high h-BN crystalline quality in monolayer samples. Read More

Let $F: \mathbb{L}^2(\Omega, \mathbb{R}) \to \mathbb{R}$ be a law invariant and continuously Fr\'echet differentiable mapping. Based on Lions \cite{Lions}, Cardaliaguet \cite{Cardaliaguet} (Theorem 6.2 and 6. Read More

Conventional analysis for computer experiments is based on Gaussian process (GP) models. Non-Gaussian observations such as binary responses are common in some computer experiments, but the extensions of GP models to these cases have received scant attention in the literature. Motivated by the analysis of a class of cell adhesion experiments, we introduce a generalized Gaussian process model for binary responses, which shares some common features with standard GP models. Read More

Hypergraph is a topological model for networks. In order to study the topology of hypergraphs, the homology of the associated simplicial complexes and the embedded homology have been invented. In this paper, we give some algorithms to compute the homology of the associated simplicial complexes and the embedded homology of hypergraphs as well as some heuristics for efficient computations. Read More

The use of geometrical constraints opens many new perspectives in photonics and in fundamental studies of nonlinear waves. By implementing surface structures in vertical cavity surface emitting lasers as manifolds for curved space, we experimentally study the impacts of geometrical constraints on nonlinear wave localization. We observe localized waves pinned to the maximal curvature in an elliptical-ring, and confirm the reduction in the localization length of waves by measuring near and far field patterns, as well as the corresponding dispersion relation. Read More

Treated traditionally by the Ehrenfest approximation, dynamics of a one-dimensional molecular crystal model with off-diagonal exciton-phonon coupling is investigated in this work using the Dirac-Frenkel time-dependent variational principle with the multi-D$_2$ {\it Ansatz}. It is shown that the Ehrenfest method is equivalent to our variational method with the single D$_2$ {\it Ansatz}, and with the multi-D$_2$ {\it Ansatz}, the accuracy of our simulated dynamics is significantly enhanced in comparison with the semi-classical Ehrenfest dynamics. The multi-D$_2$ {\it Ansatz} is able to capture numerically accurate exciton momentum probability and help clarify the relation between the exciton momentum redistribution and the exciton energy relaxation. Read More

The so-called Boltzmann Tyranny (associated with the Boltzmann distribution of electrons) defines the fundamental thermionic limit of the subthreshold slope (SS) of a metal-oxide-semiconductor field-effect transistor (MOSFET) at 60 mV/dec at room temperature, which prohibits the decrease of the supply voltage and the power consumption. Adding a ferroelectric negative capacitor in the gate stack of a MOSFET is one of the promising solutions to break this thermionic limit. Meanwhile, 2-dimensional (2D) semiconductors, such as transition metal dichalcogenides (TMDs), due to its atomically thin layered channel, low dielectric constant, and ease of integration in a junctionless transistor topology, offer the best electrostatic control of the channel. Read More

Molybdenum ditelluride (MoTe$_2$) has attracted considerable interest for nanoelectronic, optoelectronic, spintronic, and valleytronic applications because of its modest band gap, high field-effect mobility, large spin-orbit-coupling splitting, and tunable 1T'/2H phases. However, synthesizing large-area, high-quality MoTe$_2$ remains challenging. The complicated design of gas-phase reactant transport and reaction for chemical vapor deposition or tellurization is nontrivial because of the weak bonding energy between Mo and Te. Read More

We study online resource allocation in a cloud computing platform, through a posted pricing mechanism: The cloud provider publishes a unit price for each resource type, which may vary over time; upon arrival at the cloud system, a cloud user either takes the current prices, renting resources to execute its job, or refuses the prices without running its job there. We design pricing functions based on the current resource utilization ratios, in a wide array of demand-supply relationships and resource occupation durations, and prove worst-case competitive ratios of the pricing functions in terms of social welfare. In the basic case of a single-type, non-recycled resource (i. Read More

2017Apr
Authors: F. P. An, A. B. Balantekin, H. R. Band, M. Bishai, S. Blyth, D. Cao, G. F. Cao, J. Cao, Y. L. Chan, J. F. Chang, Y. Chang, H. S. Chen, Q. Y. Chen, S. M. Chen, Y. X. Chen, Y. Chen, J. Cheng, Z. K. Cheng, J. J. Cherwinka, M. C. Chu, A. Chukanov, J. P. Cummings, Y. Y. Ding, M. V. Diwan, M. Dolgareva, J. Dove, D. A. Dwyer, W. R. Edwards, R. Gill, M. Gonchar, G. H. Gong, H. Gong, M. Grassi, W. Q. Gu, L. Guo, X. H. Guo, Y. H. Guo, Z. Guo, R. W. Hackenburg, S. Hans, M. He, K. M. Heeger, Y. K. Heng, A. Higuera, Y. B. Hsiung, B. Z. Hu, T. Hu, E. C. Huang, H. X. Huang, X. T. Huang, Y. B. Huang, P. Huber, W. Huo, G. Hussain, D. E. Jaffe, K. L. Jen, X. P. Ji, X. L. Ji, J. B. Jiao, R. A. Johnson, D. Jones, L. Kang, S. H. Kettell, A. Khan, S. Kohn, M. Kramer, K. K. Kwan, M. W. Kwok, T. J. Langford, K. Lau, L. Lebanowski, J. Lee, J. H. C. Lee, R. T. Lei, R. Leitner, J. K. C. Leung, C. Li, D. J. Li, F. Li, G. S. Li, Q. J. Li, S. Li, S. C. Li, W. D. Li, X. N. Li, X. Q. Li, Y. F. Li, Z. B. Li, H. Liang, C. J. Lin, G. L. Lin, S. Lin, S. K. Lin, Y. -C. Lin, J. J. Ling, J. M. Link, L. Littenberg, B. R. Littlejohn, J. L. Liu, J. C. Liu, C. W. Loh, C. Lu, H. Q. Lu, J. S. Lu, K. B. Luk, X. Y. Ma, X. B. Ma, Y. Q. Ma, Y. Malyshkin, D. A. Martinez Caicedo, K. T. McDonald, R. D. McKeown, I. Mitchell, Y. Nakajima, J. Napolitano, D. Naumov, E. Naumova, H. Y. Ngai, J. P. Ochoa-Ricoux, A. Olshevskiy, H. -R. Pan, J. Park, S. Patton, V. Pec, J. C. Peng, L. Pinsky, C. S. J. Pun, F. Z. Qi, M. Qi, X. Qian, R. M. Qiu, N. Raper, J. Ren, R. Rosero, B. Roskovec, X. C. Ruan, H. Steiner, P. Stoler, J. L. Sun, W. Tang, D. Taychenachev, K. Treskov, K. V. Tsang, C. E. Tull, N. Viaux, B. Viren, V. Vorobel, C. H. Wang, M. Wang, N. Y. Wang, R. G. Wang, W. Wang, X. Wang, Y. F. Wang, Z. Wang, Z. Wang, Z. M. Wang, H. Y. Wei, L. J. Wen, K. Whisnant, C. G. White, L. Whitehead, T. Wise, H. L. H. Wong, S. C. F. Wong, E. Worcester, C. -H. Wu, Q. Wu, W. J. Wu, D. M. Xia, J. K. Xia, Z. Z. Xing, J. L. Xu, Y. Xu, T. Xue, C. G. Yang, H. Yang, L. Yang, M. S. Yang, M. T. Yang, Y. Z. Yang, M. Ye, Z. Ye, M. Yeh, B. L. Young, Z. Y. Yu, S. Zeng, L. Zhan, C. Zhang, C. C. Zhang, H. H. Zhang, J. W. Zhang, Q. M. Zhang, R. Zhang, X. T. Zhang, Y. M. Zhang, Y. X. Zhang, Y. M. Zhang, Z. J. Zhang, Z. Y. Zhang, Z. P. Zhang, J. Zhao, L. Zhou, H. L. Zhuang, J. H. Zou

The Daya Bay experiment has observed correlations between reactor core fuel evolution and changes in the reactor antineutrino flux and energy spectrum. Four antineutrino detectors in two experimental halls were used to identify 2.2 million inverse beta decays (IBDs) over 1230 days spanning multiple fuel cycles for each of six 2. Read More

We present low-frequency spectral energy distributions of 60 known radio pulsars observed with the Murchison Widefield Array (MWA) telescope. We searched the GaLactic and Extragalactic All-sky MWA (GLEAM) survey images for 200-MHz continuum radio emission at the position of all pulsars in the ATNF pulsar catalogue. For the 60 confirmed detections we have measured flux densities in 20 x 8 MHz bands between 72 and 231 MHz. Read More

Nonparametric models are versatile, albeit computationally expensive, tool for modeling mixture models. In this paper, we introduce spectral methods for the two most popular nonparametric models: the Indian Buffet Process (IBP) and the Hierarchical Dirichlet Process (HDP). We show that using spectral methods for the inference of nonparametric models are computationally and statistically efficient. Read More

Very large-scale Deep Neural Networks (DNNs) have achieved remarkable successes in a large variety of computer vision tasks. However, the high computation intensity of DNNs makes it challenging to deploy these models on resource-limited systems. Some studies used low-rank approaches that approximate the filters by low-rank basis to accelerate the testing. Read More

In [2], the authors constructed closed oriented hyperbolic surfaces with pseudo-Anosov diffeomorphisms from certain class of integral matrices. In this paper, we present a very simple algorithm to compute the Teichmueller polynomial corresponding to those surface diffeomorphisms. Read More

This paper studies problems on locally stopping distributed consensus algorithms over networks where each node updates its state by interacting with its neighbors and decides by itself whether certain level of agreement has been achieved among nodes. Since an individual node is unable to access the states of those beyond its neighbors, this problem becomes challenging. In this work, we first define the stopping problem for generic distributed algorithms. Read More

Despite the more than one order of magnitude difference between the measured dipole moments in $^{144}$Ba and $^{146}$Ba, the strength of the octupole correlations in $^{146}$Ba are found to be as strong as those in $^{144}$Ba with a similarly large value of $B(E3;3^- \rightarrow 0^+)$ determined as 48($^{+21}_{-29}$) W.u. The new results not only establish unambiguously the presence of a region of octupole deformation centered on these neutron-rich Ba isotopes, but also manifest the dependence of the electric dipole moments on the occupancy of different neutron orbitals in nuclei with enhanced octupole strength, as revealed by fully microscopic calculations. Read More

Objective: The present study proposes a deep learn- ing model, named DeepSleepNet, for automatic sleep stage scoring based on raw single-channel EEG, and a two-step training algorithm used to effectively train such model. Methods: Most of the existing methods rely on hand-engineered features which require prior knowledge about sleep stage scoring. Only a few of them encode the temporal information such as stage transition rules, which is important to correctly identify the next possible sleep stages, into the extracted features. Read More

Crystal structures and the Bloch theorem play a fundamental role in condensed matter physics. We propose "space-time" crystals exhibiting the general intertwined space-time periodicities in $D+1$ dimensions, which include the Floquet lattice systems as a special case. Their crystal symmetry structures are described by "space-time" groups. Read More

Interactions and effect aliasing are among the fundamental concepts in experimental design. In this paper, some new insights and approaches are provided on these subjects. In the literature, the "de-aliasing" of aliased effects is deemed to be impossible. Read More

Kennedy and O'Hagan (2001) propose a model for calibrating some unknown parameters in a computer model and estimating the discrepancy between the computer output and physical response. This model is known to have certain identifiability issues. Tuo and Wu (2016) show that there are examples for which the Kennedy-O'Hagan method renders unreasonable results in calibration. Read More

The Data Activated Liu Graph Engine - DALiuGE - is an execution framework for processing large astronomical datasets at a scale required by the Square Kilometre Array Phase 1 (SKA1). It includes an interface for expressing complex data reduction pipelines consisting of both data sets and algorithmic components and an implementation run-time to execute such pipelines on distributed resources. By mapping the logical view of a pipeline to its physical realisation, DALiuGE separates the concerns of multiple stakeholders, allowing them to collectively optimise large-scale data processing solutions in a coherent manner. Read More

James' effective Hamiltonian method has been extensively adopted to investigate largely detuned interacting quantum systems. This method is just corresponding to the second-order perturbation theory, and cannot be exploited to treat the problems which should be solved by using the third or higher-order perturbation theory. In this paper, we generalize James' effective Hamiltonian method to the higher-order case. Read More

We consider the optimal allocation of generic resources among multiple generic entities of interest over a finite planning horizon, where each entity generates stochastic returns as a function of its resource allocation during each period. The main objective is to maximize the expected return while at the same time managing risk to an acceptable level for each period. We devise a general solution framework and establish how to obtain the optimal dynamic resource allocation. Read More

A graph is said to be symmetric if its automorphism group is transitive on its arcs. Guo et al. (Electronic J. Read More

In this paper we demonstrate the necessity of including the generally omitted collective mode contributions in calculations of the Meissner effect for non-uniform superconductors. We consider superconducting pairing with non-zero center of mass momentum, as is relevant to high transition temperature cuprates, cold atoms, and quantum chromodynamic superconductors. For the concrete example of the Fulde-Ferrell phase we present a quantitative calculation of the superfluid density, showing the collective mode contributions are not only appreciable but that they derive from the amplitude mode of the order parameter. Read More

We provide experimental results to show that self-propulsion of Janus particles made by coating platinum on the hemisphere of dielectric particles in hydrogen peroxide solution is similar to selfelectrophoresis. By different surface treatments and measuring the motion of particles and their {\zeta}-potentials, we find that the speed and direction of motion are determined by the {\zeta}-potential in a given concentration of hydrogen peroxide solution. When sign of {\zeta}-potential is changed from negative to positive, the direction of motion reverses from toward non-catalytic side to catalytic side. Read More

In this paper, the quasinormal modes of gravitational perturbation around some well-known regular black holes were evaluated by using the WKB approximation as well as the asymptotic iteration method. Through numerical calculation, we make a detailed analysis of the gravitational QNM frequencies by varying the characteristic parameters of the gravitational perturbation and the spacetime charge parameters of the regular black holes. It is found that the imaginary part of quasinormal modes as a function of the charge parameter has different monotonic behaviors for different black hole spacetimes. Read More

The emerging paradigm of network function virtualization advocates deploying virtualized network functions (VNF) on standard virtualization platforms for significant cost reduction and management flexibility. There have been system designs for managing dynamic deployment and scaling of VNF service chains within one cloud data center. Many real-world network services involve geo-distributed service chains, with prominent examples of mobile core networks and IMSs (IP Multimedia Subsystems). Read More

Although the low energy fractional excitations of one dimensional integrable models are often well-understood, exploring quantum dynamics in these systems remains challenging in the gapless regime, especially at intermediate and high energies. Based on the algebraic Bethe ansatz formalism, we study spin dynamics in the antiferromagnetic spin-$\frac{1}{2}$ XXZ chain with the Ising anisotropy via the form-factor formulae. Various excitations at different energy scales are identified crucial to the dynamic spin structure factors under the guidance of sum rules. Read More

Statistical Archetypal Analysis (SAA) is introduced for the dimensional reduction of a collection of probability distributions known via samples. Applications include medical diagnosis from clinical data in the form of distributions (such as distributions of blood pressure or heart rates from different patients), the analysis of climate data such as temperature or wind speed at different locations, and the study of bifurcations in stochastic dynamical systems. Distributions can be embedded into a Hilbert space with a suitable metric, and then analyzed similarly to feature vectors in Euclidean space. Read More

We have studied radio haloes and relics in nine merging galaxy clusters using the Murchison Widefield Array (MWA). The images used for this study were obtained from the GaLactic and Extragalactic All-sky MWA (GLEAM) Survey which was carried out at 5 frequencies, viz. 88, 118, 154, 188 and 215 MHz. Read More

This paper is concerned with a constrained optimization problem over a directed graph (digraph) of nodes, in which the cost function is a sum of local objectives, and each node only knows its local objective and constraints. To collaboratively solve the optimization, most of the existing works require the interaction graph to be balanced or "doubly-stochastic", which is quite restrictive and not necessary as shown in this paper. We focus on an epigraph form of the original optimization to resolve the "unbalanced" problem, and design a novel two-step recursive algorithm with a simple structure. Read More

This paper presents a novel method for selecting main effects and a set of reparametrized predictors called conditional main effects (CMEs), which capture the conditional effect of a factor at a fixed level of another factor. CMEs represent highly interpretable phenomena for a wide range of applications in engineering, social sciences and genomics. The challenge in model selection lies in the grouped collinearity structure of CMEs, which can cause poor selection and prediction performance for existing methods. Read More

We explore signatures of the non-Markovianity in the time-resolved energy transfer processes for quantum open systems. Focusing on typical systems such as the exact solvable damped Jaynes-Cummings model and the general spin-boson model, we establish quantitative links between the time-resolved energy current and the symmetric logarithmic derivative quantum Fisher information (SLD-QFI) flow, one of measures quantifying the non-Markovianity, within the framework of non-Markovian master equations in time-local forms. From the relationships, we find in the damped Jaynes-Cummings model that the SLD-QFI backflow from the reservoir to the system always correlates with an energy backflow, thus we can directly witness the non-Markovianity from the dynamics of the energy current. Read More

The growing demand in mobile Internet access calls for high capacity and energy efficient cellular access with better cell coverage. The in-band relaying solution, proposed in LTE-Advanced, improves coverage without requiring additional spectrum for backhauling, making its deployment more economical and practical. However, in-band relay without careful management incurs low spectrum utilization and reduces the system capacity. Read More

It's useful to automatically transform an image from its original form to some synthetic form (style, partial contents, etc.), while keeping the original structure or semantics. We define this requirement as the "image-to-image translation" problem, and propose a general approach to achieve it, based on deep convolutional and conditional generative adversarial networks (GANs), which has gained a phenomenal success to learn mapping images from noise input since 2014. Read More

Allometric scaling can reflect underlying mechanisms, dynamics and structures in complex systems; examples include typical scaling laws in biology, ecology and urban development. In this work, we study allometric scaling in scientific fields. By performing an analysis of the outputs/inputs of various scientific fields, including the numbers of publications, citations, and references, with respect to the number of authors, we find that in all fields that we have studied thus far, including physics, mathematics and economics, there are allometric scaling laws relating the outputs/inputs and the sizes of scientific fields. Read More

We present a sample of 1,483 sources that display spectral peaks between 72 MHz and 1.4 GHz, selected from the GaLactic and Extragalactic All-sky Murchison Widefield Array (GLEAM) survey. The GLEAM survey is the widest fractional bandwidth all-sky survey to date, ideal for identifying peaked-spectrum sources at low radio frequencies. Read More

We identify coronal mass ejections (CMEs) associated with magnetic clouds (MCs) observed near Earth by the Wind spacecraft from 2008 to mid-2012, a time period when the two STEREO spacecraft were well positioned to study Earth-directed CMEs. We find 31 out of 48 Wind MCs during this period can be clearly connected with a CME that is trackable in STEREO imagery all the way from the Sun to near 1 AU. For these events, we perform full 3-D reconstructions of the CME structure and kinematics, assuming a flux rope morphology for the CME shape, considering the full complement of STEREO and SOHO imaging constraints. Read More

We examine the effect of the stress tensor of a quantum matter field, such as the electromagnetic field, on the spectrum of primordial gravity waves expected in inflationary cosmology. We find that the net effect is a small reduction in the power spectrum, especially at higher frequencies, but which has a different form from that described by the usual spectral index. Thus this effect has a characteristic signature, and is in principle observable. Read More

This paper considers a distributed convex optimization problem with inequality constraints over time-varying unbalanced digraphs, where the cost function is a sum of local objectives, and each node of the graph only knows its local objective and inequality constraints. Although there is a vast literature on distributed optimization, most of them require the graph to be balanced, which is quite restrictive and not necessary. Very recently, the unbalanced problem has been resolved only for either time-invariant graphs or unconstrained optimization. Read More

In this work the relativistic mean field (RMF) FSUGold model extended to include hyperons is employed to study the properties of neutron stars with strong magnetic fields. The chaotic magnetic field approximation is utilized. The effect of the anomalous magnetic moments (AMMs) is also investigated. Read More

In this note, we deduce a partial answer to the question in the title. In particular, we show that asymptotically almost all bi-Perron algebraic unit whose characteristic polynomial has degree at most $2n$ do not correspond to dilatations of pseudo-Anosov maps on a closed orientable surface of genus $n$ for $n\geq 10$. As an application of the argument, we also obtain a statement on the number of closed geodesics of the same length in the moduli space of area one abelian differentials for low genus cases. Read More

We study the problem of recovering the underlining sparse signals from clean or noisy phaseless measurements. Due to the sparse prior of signals, we adopt an L0regularized variational model to ensure only a small number of nonzero elements being recovered in the signal and two different formulations are established in the modeling based on the choices of data fidelity, i.e. Read More

We present a modular framework, the Workload Characterisation Framework (WCF), that is developed to reproducibly obtain, store and compare key characteristics of radio astronomy processing software. As a demonstration, we discuss the experiences using the framework to characterise a LOFAR calibration and imaging pipeline. Read More

Variational methods have become an important kind of methods in signal and image restoration - a typical inverse problem. One important minimization model consists of the squared $\ell_2$ data fidelity (corresponding to Gaussian noise) and a regularization term constructed by a regularization function (potential function) composed of first order difference operators. As contrasts are important features in signals and images, we study, in this paper, the possibility of contrast-preserving restoration by variational methods. Read More