# Yue Zhang - Peking University

## Contact Details

NameYue Zhang |
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AffiliationPeking University |
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CountryChina |
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## Pubs By Year |
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## Pub CategoriesHigh Energy Physics - Phenomenology (19) Cosmology and Nongalactic Astrophysics (12) High Energy Physics - Experiment (11) Computer Science - Computation and Language (7) Physics - Materials Science (6) Mathematics - Optimization and Control (5) High Energy Astrophysical Phenomena (4) Computer Science - Networking and Internet Architecture (3) Physics - Mesoscopic Systems and Quantum Hall Effect (3) Nuclear Theory (2) Nuclear Experiment (2) Solar and Stellar Astrophysics (2) Computer Science - Other (1) Astrophysics of Galaxies (1) Computer Science - Information Theory (1) Computer Science - Distributed; Parallel; and Cluster Computing (1) Mathematics - Information Theory (1) Computer Science - Numerical Analysis (1) Nonlinear Sciences - Chaotic Dynamics (1) Computer Science - Learning (1) Quantitative Biology - Quantitative Methods (1) General Relativity and Quantum Cosmology (1) Physics - Soft Condensed Matter (1) Statistics - Machine Learning (1) Quantitative Biology - Populations and Evolution (1) Computer Science - Computer Vision and Pattern Recognition (1) |

## Publications Authored By Yue Zhang

In earlier work, we addressed the problem of optimally controlling on line connected and automated vehicles crossing two adjacent intersections in an urban area to minimize fuel consumption without any explicit traffic signaling and without considering left and right turns. In this paper, we extend the solution of this problem to account for left and right turns under hard safety constraints. Furthermore, we formulate and solve another optimization problem to minimize a measure of passenger discomfort while the vehicle turns at the intersection, and we investigate the associated tradeoff between minimizing fuel consumption and passenger discomfort. Read More

We revisit the calculation of relic density of dark matter particles co-annihilating with a top or bottom partner, by properly including the QCD bound-states (onia) effects of the colored partners, as well as the relevant electroweak processes which become important in the low mass region. We carefully set up the complete framework that incorporates the relevant contributions and investigate their effects on the cosmologically preferred mass spectrum, which turn out to be comparable in size to those coming from the Sommerfeld enhancement. We apply the calculation to three scenarios: bino-stop and bino-sbottom co-annihilations in supersymmetry, and a vector dark matter co-annihilating with a fermionic top partner. Read More

In a multi-carrier phase ranging (MPR) system, the distance that radio signal travels is estimated through phase shift of multiple carrier frequencies. Due to phase ambiguity, a unique estimation can only be obtained within the unambiguous distance (UD), which depends on the carrier frequencies used for ranging. Without external information, the maximum measurable distance of an MPR system is defined by its UD. Read More

We present opinion recommendation, a novel task of jointly predicting a custom review with a rating score that a certain user would give to a certain product or service, given existing reviews and rating scores to the product or service by other users, and the reviews that the user has given to other products and services. A characteristic of opinion recommendation is the reliance of multiple data sources for multi-task joint learning, which is the strength of neural models. We use a single neural network to model users and products, capturing their correlation and generating customised product representations using a deep memory network, from which customised ratings and reviews are constructed jointly. Read More

This paper addresses the task of AMR-to-text generation by leveraging synchronous node replacement grammar. During training, graph-to-string rules are learned using a heuristic extraction algorithm. At test time, a graph transducer is applied to collapse input AMRs and generate output sentences. Read More

Transition-based models can be fast and accurate for constituent parsing. Compared with chart-based models, they leverage richer features by extracting history information from a parser stack, which spans over non-local constituents. On the other hand, during incremental parsing, constituent information on the right hand side of the current word is not utilized, which is a relative weakness of shift-reduce parsing. Read More

Sequential LSTM has been extended to model tree structures, giving competitive results for a number of tasks. Existing methods model constituent trees by bottom-up combinations of constituent nodes, making direct use of input word information only for leaf nodes. This is different from sequential LSTMs, which contain reference to input words for each node. Read More

We explore the self-interacting dark matter scenario in a simple dark sector model where the dark matter interacts through a dark photon. Splitting a Dirac fermion dark matter into two levels using a small Majorana mass can evade strong direct detection constraints on the kinetic mixing between the dark and normal photons, thus allowing the dark sector to be more visible at high intensity and/or high energy experiments. It is pointed out that such a mass splitting has a strong impact on the dark matter self-interaction strength. Read More

A hidden sector with pure non-abelian gauge symmetry is an elegant and just about the simplest model of dark matter. In this model the dark matter candidate is the lightest bound state made of the confined gauge fields, the dark glueball. In spite of its simplicity, the model has been shown to have several interesting non-standard implications in cosmology. Read More

In phylogenetic analysis, for non-molecular data, particularly morphology, parsimony optimization is the most commonly employed approach. In the past and present application of the parsimony principle, extra step numbers have been added across different characters without proper justification. This practice, however, has caused the impacts of characters to be inflated or deflated without a valid reason. Read More

Recently, these has been a surge on studying how to obtain partially annotated data for model supervision. However, there still lacks a systematic study on how to train statistical models with partial annotation (PA). Taking dependency parsing as our case study, this paper describes and compares two straightforward approaches for three mainstream dependency parsers. Read More

The task of AMR-to-text generation is to generate grammatical text that sustains the semantic meaning for a given AMR graph. We at- tack the task by first partitioning the AMR graph into smaller fragments, and then generating the translation for each fragment, before finally deciding the order by solving an asymmetric generalized traveling salesman problem (AGTSP). A Maximum Entropy classifier is trained to estimate the traveling costs, and a TSP solver is used to find the optimized solution. Read More

**Authors:**Jim Alexander, Marco Battaglieri, Bertrand Echenard, Rouven Essig, Matthew Graham, Eder Izaguirre, John Jaros, Gordan Krnjaic, Jeremy Mardon, David Morrissey, Tim Nelson, Maxim Perelstein, Matt Pyle, Adam Ritz, Philip Schuster, Brian Shuve, Natalia Toro, Richard G Van De Water, Daniel Akerib, Haipeng An, Konrad Aniol, Isaac J. Arnquist, David M. Asner, Henning O. Back, Keith Baker, Nathan Baltzell, Dipanwita Banerjee, Brian Batell, Daniel Bauer, James Beacham, Jay Benesch, James Bjorken, Nikita Blinov, Celine Boehm, Mariangela Bondí, Walter Bonivento, Fabio Bossi, Stanley J. Brodsky, Ran Budnik, Stephen Bueltmann, Masroor H. Bukhari, Raymond Bunker, Massimo Carpinelli, Concetta Cartaro, David Cassel, Gianluca Cavoto, Andrea Celentano, Animesh Chaterjee, Saptarshi Chaudhuri, Gabriele Chiodini, Hsiao-Mei Sherry Cho, Eric D. Church, D. A. Cooke, Jodi Cooley, Robert Cooper, Ross Corliss, Paolo Crivelli, Francesca Curciarello, Annalisa D'Angelo, Hooman Davoudiasl, Marzio De Napoli, Raffaella De Vita, Achim Denig, Patrick deNiverville, Abhay Deshpande, Ranjan Dharmapalan, Bogdan Dobrescu, Sergey Donskov, Raphael Dupre, Juan Estrada, Stuart Fegan, Torben Ferber, Clive Field, Enectali Figueroa-Feliciano, Alessandra Filippi, Bartosz Fornal, Arne Freyberger, Alexander Friedland, Iftach Galon, Susan Gardner, Francois-Xavier Girod, Sergei Gninenko, Andrey Golutvin, Stefania Gori, Christoph Grab, Enrico Graziani, Keith Griffioen, Andrew Haas, Keisuke Harigaya, Christopher Hearty, Scott Hertel, JoAnne Hewett, Andrew Hime, David Hitlin, Yonit Hochberg, Roy J. Holt, Maurik Holtrop, Eric W. Hoppe, Todd W. Hossbach, Lauren Hsu, Phil Ilten, Joe Incandela, Gianluca Inguglia, Kent Irwin, Igal Jaegle, Robert P. Johnson, Yonatan Kahn, Grzegorz Kalicy, Zhong-Bo Kang, Vardan Khachatryan, Venelin Kozhuharov, N. V. Krasnikov, Valery Kubarovsky, Eric Kuflik, Noah Kurinsky, Ranjan Laha, Gaia Lanfranchi, Dale Li, Tongyan Lin, Mariangela Lisanti, Kun Liu, Ming Liu, Ben Loer, Dinesh Loomba, Valery E. Lyubovitskij, Aaron Manalaysay, Giuseppe Mandaglio, Jeremiah Mans, W. J. Marciano, Thomas Markiewicz, Luca Marsicano, Takashi Maruyama, Victor A. Matveev, David McKeen, Bryan McKinnon, Dan McKinsey, Harald Merkel, Jeremy Mock, Maria Elena Monzani, Omar Moreno, Corina Nantais, Sebouh Paul, Michael Peskin, Vladimir Poliakov, Antonio D Polosa, Maxim Pospelov, Igor Rachek, Balint Radics, Mauro Raggi, Nunzio Randazzo, Blair Ratcliff, Alessandro Rizzo, Thomas Rizzo, Alan Robinson, Andre Rubbia, David Rubin, Dylan Rueter, Tarek Saab, Elena Santopinto, Richard Schnee, Jessie Shelton, Gabriele Simi, Ani Simonyan, Valeria Sipala, Oren Slone, Elton Smith, Daniel Snowden-Ifft, Matthew Solt, Peter Sorensen, Yotam Soreq, Stefania Spagnolo, James Spencer, Stepan Stepanyan, Jan Strube, Michael Sullivan, Arun S. Tadepalli, Tim Tait, Mauro Taiuti, Philip Tanedo, Rex Tayloe, Jesse Thaler, Nhan V. Tran, Sean Tulin, Christopher G. Tully, Sho Uemura, Maurizio Ungaro, Paolo Valente, Holly Vance, Jerry Vavra, Tomer Volansky, Belina von Krosigk, Andrew Whitbeck, Mike Williams, Peter Wittich, Bogdan Wojtsekhowski, Wei Xue, Jong Min Yoon, Hai-Bo Yu, Jaehoon Yu, Tien-Tien Yu, Yue Zhang, Yue Zhao, Yiming Zhong, Kathryn Zurek

This report, based on the Dark Sectors workshop at SLAC in April 2016, summarizes the scientific importance of searches for dark sector dark matter and forces at masses beneath the weak-scale, the status of this broad international field, the important milestones motivating future exploration, and promising experimental opportunities to reach these milestones over the next 5-10 years. Read More

Spintronics, which utilizes spin as information carrier, is a promising solution for nonvolatile memory and low-power computing in the post-Moore era. An important challenge is to realize long distance spin transport, together with efficient manipulation of spin current for novel logic-processing applications. Here, we describe a gate-variable spin current demultiplexer (GSDM) based on graphene, serving as a fundamental building block of reconfigurable spin current logic circuits. Read More

Earlier work has established a decentralized optimal control framework for coordinating online a continuous flow of connected automated vehicles (CAVs) entering a control zone and crossing two adjacent intersections in an urban area. A solution, when it exists, allows the vehicles to cross the intersections without the use of traffic lights, without creating congestion on the connecting road, and under the hard safety constraint of collision avoidance. We establish the conditions under which such solutions exist and show that they can be enforced through an appropriately designed feasibility enforcement zone that precedes the control zone. Read More

We consider a dark sector consisting of dark matter that is a Dirac fermion and a scalar mediator. This model has been extensively studied in the past. If the scalar couples to the dark matter in a parity conserving manner then dark matter annihilation to two mediators is dominated by the P-wave channel and hence is suppressed at very low momentum. Read More

**Authors:**Ruirui Xu

^{1}, Zhongyu Ma

^{2}, Yue Zhang

^{3}, Yuan Tian

^{4}, E. N. E. van Dalen

^{5}, H. Müther

^{6}

**Affiliations:**

^{1}China Institute of Atomic Energy, Beijing 102413,

^{2}China Institute of Atomic Energy, Beijing 102413,

^{3}China Institute of Atomic Energy, Beijing 102413,

^{4}China Institute of Atomic Energy, Beijing 102413,

^{5}Institut für Theoretische Physik, Universität Tübingen, Germany,

^{6}Institut für Theoretische Physik, Universität Tübingen, Germany

**Category:**Nuclear Theory

The Microscopic Otical Model Potential is evaluated within a relativistic scheme which provides a natural and consistent relation between the spin-orbit part and the central part of the potential. The Dirac-Brueckner-Hartree-Fock (DBHF) approach provides such a microscopic relativistic scheme, which is based on a realistic nucleon-nucleon interaction and reproduce the saturation properties of symmetric nuclear matter without any adjustable parameter. Its solution using the projection technique within the subtracted T-matrix (STM) representation provides a reliable extension to asymmetric nuclear matter, which is important to describe the features of the isospin asymmetric nuclei. Read More

The theoretical study of grain boundaries (GBs) in polycrystalline semiconductors is currently stalemated by their complicated nature, which is difficult to extract from any direct experimental characterization. Usually, coincidence-site-lattice (CSL) models are constructed simply by aligning two symmetric planes, ignoring various possible reconstructions. Here, we propose a general self-passivation rule to determine the low-energy GB reconstruction, and find new configurations for the CdTe sigma3 (112) GBs. Read More

Aspect phrase grouping is an important task in aspect-level sentiment analysis. It is a challenging problem due to polysemy and context dependency. We propose an Attention-based Deep Distance Metric Learning (ADDML) method, by considering aspect phrase representation as well as context representation. Read More

We study the impact of bound state formation on dark matter annihilation rates in models where dark matter interacts via a light mediator, the dark photon. We derive the general cross section for radiative capture into all possible bound states, and point out its non-trivial dependence on the dark matter velocity and the dark photon mass. For indirect detection, our result shows that dark matter annihilation inside bound states can play an important role in enhancing signal rates over the rate for direct dark matter annihilation with Sommerfeld enhancement. Read More

Physical vapor deposition (PVD) is widely used in manufacturing ultra-thin layers of amorphous organic solids. Here, we demonstrate that these films exhibit a sharp transition from glassy solid to liquid-like behavior with thickness below 30 nm. This liquid-like behavior persists even at temperatures well below the glass transition temperature, T$_{\mathrm{g}}$. Read More

We address the problem of optimally controlling connected automated vehicles (CAVs) crossing an urban inter- section without any explicit traffic signaling. We first formulate a centralized problem with the objective of controlling CAV acceler- ation/deceleration to maximize traffic throughput subject to hard safety constraints and minimal energy cost. We show that the solution of this problem provides the times required for individual CAVs to cross the intersection and that the centralized problem becomes, under certain conditions, equivalent to a decentralized framework whereby each CAV minimizes its energy consumption subject to the throughput-maximizing timing constraints. Read More

Current-induced domain wall motion (CIDWM) is regarded as a promising way towards achieving emerging high-density, high-speed and low-power non-volatile devices. Racetrack memory is an attractive spintronic memory based on this phenomenon, which can store and transfer a series of data along a magnetic nanowire. However, storage capacity issue is always one of the most serious bottlenecks hindering its application for practical systems. Read More

We investigate the possibility that the dark matter candidate is from a pure non-abelian gauge theory of the hidden sector, motivated in large part by its elegance and simplicity. The dark matter is the lightest bound state made of the confined gauge fields, the hidden glueball. We point out this simple setup is capable of providing rich and novel phenomena in the dark sector, especially in the parameter space of large N. Read More

ATLAS and CMS have each reported a modest diphoton excess consistent with the decay of a broad resonance at ~ 750 GeV. We show how this signal can arise in a weakly coupled theory comprised solely of narrow width particles. In particular, if the decaying particle is produced off-shell, then the associated diphoton resonance will have a broad, adjustable width. Read More

In order to obtain a reasonable and reliable forecast method for crude oil price volatility, this paper evaluates the forecast performance of single-regime GARCH models (including the standard linear GARCH model and the nonlinear GJR-GARCH and EGARCH models) and the two-regime Markov Regime Switching GARCH (MRS-GARCH) model for crude oil price volatility at different data frequencies and time horizons. The results indicate that, first, the two-regime MRS-GARCH model beats other three single-regime GARCH type models in in-sample data estimation under most evaluation criteria, although it appears inferior under a few of other evaluation criteria. Second, the two-regime MRS-GARCH model overall provides more accurate volatility forecast for daily data but this superiority dies way for weekly and monthly data. Read More

A model of dark sector where $O({\rm few~GeV})$ mass dark matter particles $\chi$ couple to a lighter dark force mediator $V$, $m_V \ll m_\chi$, is motivated by the recently discovered mismatch between simulated and observed shapes of galactic haloes. Such models, in general, provide a challenge for direct detection efforts and collider searches. We show that for a large range of coupling constants and masses, the production and decay of the bound states of $\chi$, such as $0^{-+}$ and $1^{--}$ states, $\eta_D$ and $ \Upsilon_D$, is an important search channel. Read More

Despite the recent progress on two-dimensional multilayer materials (2DMM) with weak interlayer interactions, the investigation on 2DMM with strong interlayer interactions is far from its sufficiency. Here we report on first-principles calculations that clarify the structural evolution and optoelectronic properties of such a 2DMM, multilayer silicene. With our newly developed global optimization algorithm, we discover the existence of rich dynamically stable multilayer silicene phases, the stability of which is closely related to the extent of sp3 hybridization that can be evaluated by the average bonds and effective bond angles. Read More

We address the problem of coordinating online a continuous flow of connected and automated vehicles (CAVs) crossing two adjacent intersections in an urban area. We present a decentralized optimal control framework whose solution yields for each vehicle the optimal acceleration/deceleration at any time in the sense of minimizing fuel consumption. The solution, when it exists, allows the vehicles to cross the intersections without the use of traffic lights, without creating congestion on the connecting road, and under the hard safety constraint of collision avoidance. Read More

We explore CP violating aspects in the Higgs sector of models where new vectorlike quarks carry Yukawa couplings mainly to the third generation quarks of the Standard Model. We point out that in the simplest model, Higgs CP violating interactions only exist in the hWW channel. At low energy, we find that rare B decays can place similarly strong constraints as those from electric dipole moments on the source of CP violation. Read More

Two decades ago, a phenomenon resembling Landau damping was described in the synchronization of globally coupled oscillators: the evidence of a regime where the order parameter decays when linear theory predicts neutral stability for the incoherent state. We here show that such an effect is far more generic, as soon as phase oscillators couple to their mean field according to their natural frequencies, being then grouped into two distinct populations of conformists and contrarians. We report the analytical solution of this latter situation, which allows determining the critical coupling strength and the stability of the incoherent state, together with extensive numerical simulations that fully support all theoretical predictions. Read More

All-spin logic device (ASLD) has attracted increasing interests as one of the most promising post-CMOS device candidates, thanks to its low power, non-volatility and logic-in-memory structure. Here we investigate the key current-limiting factors and develop a physics-based model of ASLD through nano-magnet switching, the spin transport properties and the breakdown characteristic of channel. First, ASLD with perpendicular magnetic anisotropy (PMA) nano-magnet is proposed to reduce the critical current (Ic0). Read More

The organic-inorganic hybrid perovskite CH3NH3PbI3 has attracted significant interest for its high performance in converting solar light into electrical power with an efficiency exceeding 20%. Unfortunately, chemical stability is one major challenge in the development of the CH3NH3PbI3 solar cells. It was commonly assumed that moisture or oxygen in the environment causes the poor stability of hybrid halide perovskites, however, here we show from the first-principles calculations that the room-temperature tetragonal phase of CH3NH3PbI3 is thermodynamically unstable with respect to the phase separation into CH3NH3I + PbI2, i. Read More

We propose and investigate a novel, minimal, and experimentally testable framework for baryogenesis, dubbed dexiogenesis, using baryon number violating effective interactions of right-handed Majorana neutrinos responsible for the seesaw mechanism. The distinct LHC signature of our framework is same-sign top quark final states, possibly originating from displaced vertices. The region of parameters relevant for LHC phenomenology can also yield concomitant signals in nucleon decay experiments. Read More

The advent of software defined networking enables flexible, reliable and feature-rich control planes for data center networks. However, the tight coupling of centralized control and complete visibility leads to a wide range of issues among which scalability has risen to prominence. To address this, we present LazyCtrl, a novel hybrid control plane design for data center networks where network control is carried out by distributed control mechanisms inside independent groups of switches while complemented with a global controller. Read More

We analyze the constraints on a CP-violating, flavor conserving, two Higgs doublet model from the measurements of Higgs properties and from the search for heavy Higgs bosons at LHC, and show that the stronger limits typically come from the heavy Higgs search channels. The limits on CP violation arising from the Higgs sector measurements are complementary to those from EDM measurements. Combining all current constraints from low energy to colliders, we set generic upper bounds on the CP violating angle which parametrizes the CP odd component in the 126 GeV Higgs boson. Read More

We calculate the early universe evolution of perturbations in the dark matter energy density in the context of simple dark sector models containing a GeV scale light mediator. We consider the case that the mediator is long lived, with lifetime up to a second, and before decaying it temporarily dominates the energy density of the universe. We show that for primordial perturbations that enter the horizon around this period, the interplay between linear growth during matter domination and collisional damping can generically lead to a sharp peak in the spectrum of dark matter density perturbation. Read More

In this paper, we present GASG21 (Grassmannian Adaptive Stochastic Gradient for $L_{2,1}$ norm minimization), an adaptive stochastic gradient algorithm to robustly recover the low-rank subspace from a large matrix. In the presence of column outliers, we reformulate the batch mode matrix $L_{2,1}$ norm minimization with rank constraint problem as a stochastic optimization approach constrained on Grassmann manifold. For each observed data vector, the low-rank subspace $\mathcal{S}$ is updated by taking a gradient step along the geodesic of Grassmannian. Read More

We consider the bound state problem for a field theory that contains a Dirac fermion $\chi$ that Yukawa couples to a (light) scalar field $\phi$. We are interested in bound states with a large number $N$ of $\chi$ particles. A Fermi gas model is used to numerically determine the dependence of the radius $R$ of these bound states on $N$ and also the dependence of the binding energy on $N$. Read More

The simplest renormalizable effective field theories with asymmetric dark matter bound states contain two additional gauge singlet fields one being the dark matter and the other a mediator particle that the dark matter annihilates into. We examine the physics of one such model with a Dirac fermion as the dark matter and a real scalar mediator. For a range of parameters the Yukawa coupling of the dark matter to the mediator gives rise to stable asymmetric dark matter bound states. Read More

A light hidden gauge boson with kinetic mixing with the usual photon is a popular setup in theories of dark matter. The supernova cooling via radiating the hidden boson is known to put an important constraint on the mixing. I consider the possible role dark matter, which under reasonable assumptions naturally exists inside supernova, can play in the cooling picture. Read More

We present a support vector machine classifier to identify the K giant stars from the LAMOST survey directly using their spectral line features. The completeness of the identification is about 75% for tests based on LAMOST stellar parameters. The contamination in the identified K giant sample is lower than 2. Read More

We consider all the dimension 6 operators as well as some simple extensions of the standard model that give new contributions to neutrino interactions with matter. Such interactions are usually parametrized by $\epsilon_{\alpha \beta}$, where $\alpha$ and $\beta$ are neutrino flavor indices taking the values $e$, $\mu$ and $\tau$. In the simple models we consider the $\epsilon_{\alpha \beta}$'s are much more constrained than in the operator-based model-independent approach. Read More

We analyze the constraints on CP-violating, flavor conserving Two Higgs Doublet Models (2HDMs) implied by measurements of Higgs boson properties at the Large Hadron Collider (LHC) and by the non-observation of permanent electric dipole moments (EDMs) of molecules, atoms and the neutron. We find that the LHC and EDM constraints are largely complementary, with the LHC studies constraining the mixing between the neutral CP-even states and EDMs probing the effect of mixing between the CP-even and CP-odd scalars. The presently most stringent constraints are implied by the non-observation of the ThO molecule EDM signal. Read More

It is a challenge to specify unambiguous distance (UD) in a phase-based ranging system with hopping frequencies (PRSHF). In this letter, we propose to characterize the UD in a PRSHF by the probability that it takes on its maximum value. We obtain a very simple and elegant expression of the probability with growth estimation techniques from analytic number theory. Read More

The radio interferometric positioning system (RIPS) is a novel positioning solution used in wireless sensor networks. This letter explores the ranging accuracy of RIPS in two configurations. In the linear step-frequency (LSF) configuration, we derive the mean square error (MSE) of the maximum likelihood (ML) estimator. Read More

Traditional gazetteers are built and maintained by authoritative mapping agencies. In the age of Big Data, it is possible to construct gazetteers in a data-driven approach by mining rich volunteered geographic information (VGI) from the Web. In this research, we build a scalable distributed platform and a high-performance geoprocessing workflow based on the Hadoop ecosystem to harvest crowd-sourced gazetteer entries. Read More

We investigate the feasibility of directly detecting a generation mechanism of the cosmic baryon asymmetry, by repeating the same particle physics process inside the LHC. We propose a framework with R-parity and CP violating squark decays responsible for baryogenesis, which can be embedded in supersymmetric models and is partly motivated by naturalness. We argue that the baryon number generation here is closely related to lepton charge asymmetry on the resonance. Read More

We have developed a new global optimization method for the determination of interface structure based on the differential evolution algorithm. Here, we applied this method to search for the ground state atomic structures of the grain boundary between the armchair and zigzag oriented graphene. We find two new grain boundary structures with considerably lower formation energy of about 1 eV/nm than that of the previously widely used structural models. Read More

A total of $\sim640,000$ objects from LAMOST pilot survey have been publicly released. In this work, we present a catalog of DA white dwarfs from the entire pilot survey. We outline a new algorithm for the selection of white dwarfs by fitting S\'ersic profiles to the Balmer H$\beta$, H$\gamma$ and H$\delta$ lines of the spectra, and calculating the equivalent width of the CaII K line. Read More