W. Huang - Key Laboratory of Particle and Radiation Imaging of Ministry of Education, Tsinghua University

W. Huang
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Name
W. Huang
Affiliation
Key Laboratory of Particle and Radiation Imaging of Ministry of Education, Tsinghua University
City
Beijing
Country
China

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Physics - Instrumentation and Detectors (6)
 
Physics - Mesoscopic Systems and Quantum Hall Effect (6)
 
Physics - Optics (4)
 
Mathematics - Numerical Analysis (4)
 
Quantitative Biology - Neurons and Cognition (3)
 
Mathematics - Information Theory (3)
 
Physics - Accelerator Physics (3)
 
Mathematics - Dynamical Systems (3)
 
Mathematics - Operator Algebras (3)
 
Computer Science - Computer Vision and Pattern Recognition (3)
 
Computer Science - Information Theory (3)
 
Quantum Physics (3)
 
Physics - Materials Science (3)
 
Computer Science - Neural and Evolutionary Computing (2)
 
High Energy Physics - Phenomenology (2)
 
Computer Science - Learning (2)
 
Computer Science - Artificial Intelligence (2)
 
Nuclear Experiment (2)
 
Physics - Physics and Society (2)
 
High Energy Physics - Experiment (2)
 
Physics - Atomic Physics (1)
 
High Energy Astrophysical Phenomena (1)
 
Computer Science - Human-Computer Interaction (1)
 
Mathematics - Number Theory (1)
 
Mathematics - Rings and Algebras (1)
 
High Energy Physics - Theory (1)
 
Quantitative Biology - Quantitative Methods (1)
 
Physics - Strongly Correlated Electrons (1)
 
Physics - Superconductivity (1)
 
Nonlinear Sciences - Adaptation and Self-Organizing Systems (1)
 
Statistics - Applications (1)
 
Computer Science - Computation and Language (1)
 
Statistics - Computation (1)
 
Statistics - Machine Learning (1)

Publications Authored By W. Huang

2017May
Affiliations: 1Tsinghua University, china, 2Tsinghua University, china, 3Chinese Academy of Sciences, China, 4Chinese Academy of Sciences, China, 5Tsinghua University, china, 6Tsinghua University, china, 7Chinese Academy of Sciences, China, 8Tsinghua University, china, 9Chinese Academy of Sciences, China, 10Tsinghua University, china, 11Tsinghua University, china, 12Tsinghua University, china, 13Tsinghua University, china, 14Chinese Academy of Sciences, China, 15Chinese Academy of Sciences, China, 16Tsinghua University, china, 17Chinese Academy of Sciences, China, 18Chinese Academy of Sciences, China, 19Chinese Academy of Sciences, China, 20Chinese Academy of Sciences, China, 21Tsinghua University, china

Using a high energy electron beam for the imaging of high density matter with both high spatial-temporal and areal density resolution under extreme states of temperature and pressure is one of the critical challenges in high energy density physics . When a charged particle beam passes through an opaque target, the beam will be scattered with a distribution that depends on the thickness of the material. By collecting the scattered beam either near or off axis, so-called bright field or dark field images can be obtained. Read More

Heavily electron-doped and single-layer FeSe superconduct at much higher temperatures than bulk FeSe. There have been a number of proposals attempting to explain the origin of the enhanced transition temperature, including the proximity to magnetic, nematic and antiferro-orbital critical points, as well as possible strong interfacial phonon coupling in the case of single-layer FeSe. In this work, we examine the effect of the various mechanisms in an effective two-band model. Read More

To obtain precisely controllable, robust as well as reproduceable memristor for efficient neuromorphic computing still very challenging. Molecular tailoring aims at obtaining the much more flexibly tuning plasticity has recently generated significant interest as new paradigms toward the realization of novel memristor-based synapses. Herein, inspired by the deliberate oxygen transport carried by the hemoglobin in our blood circulation, we report a novel molecular-regulated electronic/ionic semiconducting (MEIS) platform ITO/MTPP/Al2O3-x/Al with a series of metallophorphyrins (MTPPs) to delicately regulate the ionic migration for robust molecular multimedia memristors. Read More

The conditioning of implicit Runge-Kutta (RK) integration for linear finite element approximation of diffusion equations on general anisotropic meshes is investigated. Bounds are established for the condition number of the resulting linear system with and without diagonal preconditioning for the implicit Euler (the simplest implicit RK method) and general implicit RK methods. It is shown that the conditioning of an implicit RK method behaves like that of the implicit Euler method. Read More

This paper presents methods to compare networks where relationships between pairs of nodes in a given network are defined. We define such network distance by searching for the optimal method to embed one network into another network, prove that such distance is a valid metric in the space of networks modulo permutation isomorphisms, and examine its relationship with other network metrics. The network distance defined can be approximated via multi-dimensional scaling, however, the lack of structure in networks results in poor approximations. Read More

We report a post-growth aging mechanism of Bi$_2$Te$_3$(111) films with scanning tunneling microscopy in combination with density functional theory calculation. It is found that a monolayered structure with a squared lattice symmetry gradually aggregates from surface steps. Theoretical calculations indicate that the van der Waals (vdW) gap not only acts as a natural reservoir for self-intercalated Bi and Te atoms, but also provides them easy diffusion pathways. Read More

In this work, we study the dynamical robustness in a system consisting of both active and inactive oscillators. We analytically show that the dynamical robustness of such system is determined by the cross link density between active and inactive subpopulations, which depends on the specific process of inactivation. It is the multi-valued dependence of the cross link density on the control parameter, i. Read More

We propose a method based on the slice energy spread modulation to generate strong subpicoseond density bunching in high-intensity relativistic electron beams. A laser pulse with periodic intensity envelope is used to modulate the slice energy spread of the electron beam, which can then be converted into density modulation after a dispersive section. It is found that the double-horn slice energy distribution of the electron beam induced by the laser modulation is very effective to increase the density bunching. Read More

In classical sparse representation based classification and weighted SRC algorithms, the test samples are sparely represented by all training samples. They emphasize the sparsity of the coding coefficients but without considering the local structure of the input data. To overcome the shortcoming, aiming at the difficult problem of plant leaf recognition on the large-scale database, a two-stage local similarity based classification learning method is proposed by combining local mean-based classification method and local WSRC. Read More

We propose a novel ultrafast electronic switching device based on dual-graphene electron waveguides, in analogy to the optical dual-channel waveguide device. The design utilizes the principle of coherent quantum mechanical tunneling of Rabi oscillations between the two graphene electron waveguides. Based on a modified coupled mode theory, we construct a theoretical model to analyse the device characteristics, and predict that the swtiching speed is faster than 1 ps. Read More

Various physical structures exhibit a fundamentally probabilistic nature over diverse scales in space and time, to the point that the demarcation line between quantum and classic laws gets blurred. Here, we characterize the probability of intermittency in the laminar-turbulence transition of a partially mode-locked fibre laser system, whose degree of coherence is deteriorated by multiple mode mixing. Two competing processes, namely the proliferation and the decay of an optical turbulent puff, determine a critical behavior for the onset of turbulence in such a nonlinear dissipative system, where nondeterministic polarization rogue waves are introduced. Read More

Energies from alpha- and proton-decay experiments yield information of capital importance for deriving the atomic masses of superheavy and exotic nuclides. We present a procedure to correct the published decay energies in case the recoiling daughter nuclides were not considered properly in implantation experiments. A program has been developed based on Lindhard's integral theory, which can accurately predict the energy deposition of heavy atomic projectiles in matter. Read More

We have developed an efficient information-maximization method for computing the optimal shapes of tuning curves of sensory neurons by optimizing the parameters of the underlying feedforward network model. When applied to the problem of population coding of visual motion with multiple directions, our method yields several types of tuning curves with both symmetric and asymmetric shapes that resemble what have been found in the visual cortex. Our result suggests that the diversity or heterogeneity of tuning curve shapes as observed in neurophysiological experiment might actually constitute an optimal population representation of visual motions with multiple components. Read More

We investigate the quantum phases of mixed-dimensional cold atom mixtures. In particular, we consider a mixture of a Fermi gas in a two-dimensional lattice, interacting with a bulk Fermi gas or a Bose-Einstein condensate in a three-dimensional lattice. The effective interaction of the two-dimensional system mediated by the bulk system is determined. Read More

Two-color multiphoton emission from polycrystalline tungsten nanotips has been demonstrated using two-color laser fields. The two-color photoemission is assisted by a three-photon multicolor quantum channel, which leads to a twofold increase in quantum efficiency. Weak-field control of two-color multiphoton emission was achieved by changing the efficiency of the quantum channel with pulse delay. Read More

The round trip time of the light pulse limits the maximum detectable frequency response range of vibration in phase-sensitive optical time domain reflectometry ({\phi}-OTDR). We propose a method to break the frequency response range restriction of {\phi}-OTDR system by modulating the light pulse interval randomly which enables a random sampling for every vibration point in a long sensing fiber. This sub-Nyquist randomized sampling method is suits for detecting sparse-wideband-frequency vibration signals. Read More

A third-order moving mesh cell-centered scheme without the remapping of physical variables is developed for the numerical solution of one-dimensional elastic-plastic flows with the Mie-Gr\"{u}neisen equation of state, the Wilkins constitutive model, and the von Mises yielding criterion. The scheme combines the Lagrangian method with the MMPDE moving mesh method and adaptively moves the mesh to better resolve shock and other types of waves while preventing the mesh from crossing and tangling. It treats the relative velocity of the flow with respect to the mesh as constant in time between time steps. Read More

In this paper, we investigate chaotic phenomena on quasi-periodic forced systems. We introduce the notion of random periodic orbits and random horseshoe for a quasi-periodic forced system $(M\times \Omega,\phi)$ by viewing $\phi$ as a random dynamical system over the metric dynamical system $(\Omega,\theta)$. When $\phi$ is transitive and Anosov on fibers, we prove that $\phi$ has an abundance of random periodic points, Spectral Decomposition Theorem and existence of random horseshoes. Read More

One of the major distinguishing features of the dynamic multiobjective optimization problems (DMOPs) is the optimization objectives will change over time, thus tracking the varying Pareto-optimal front becomes a challenge. One of the promising solutions is reusing the "experiences" to construct a prediction model via statistical machine learning approaches. However most of the existing methods ignore the non-independent and identically distributed nature of data used to construct the prediction model. Read More

A new functional is presented for variational mesh generation and adaptation. It is formulated based on combining the equidistribution and alignment conditions into a single condition without introducing any new parameters. The functional is shown to be coercive. Read More

Manifold optimization appears in a wide variety of computational problems in the applied sciences. In recent statistical methodologies such as sufficient dimension reduction and regression envelopes, estimation relies on the optimization of likelihood functions over spaces of matrices such as the Stiefel or Grassmann manifolds. Recently, Huang, Absil, Gallivan, and Hand (2016) have introduced the library ROPTLIB, which provides a framework and state of the art algorithms to optimize real-valued objective functions over commonly used matrix-valued Riemannian manifolds. Read More

The Plastic Scintillator Detector (PSD) is one of the main sub-detectors in the DArk Matter Particle Explorer (DAMPE) project. It will be operated over a large temperature range from -$10$ to $30^{\circ}$C, so the temperature effect of the whole detection system should be studied in detail. The temperature dependence of the PSD system is mainly contributed by the three parts: the plastic scintillator bar, the photomultiplier tube (PMT), and the Front End Electronics (FEE). Read More

The family of pairwise independently determined (PID) systems, i.e. those for which the independent joining is the only self joining with independent 2-marginals, is a class of systems for which the long standing open question by Rokhlin, of whether mixing implies mixing of all orders, has a positive answer. Read More

A sealed high gas pressure detector working in pure argon is assembled. It consists of a 5 cm $\times$ 5 cm PCB THGEM (THick Gaseous Electron Multipliers). The detector structure and experimental setup are described. Read More

Cognitive flexibility describes the human ability to switch between modes of mental function to achieve goals. Mental switching is accompanied by transient changes in brain activity, which must occur atop an anatomical architecture that bridges disparate cortical and subcortical regions by underlying white matter tracts. However, an integrated perspective regarding how white matter networks might constrain brain dynamics during cognitive processes requiring flexibility has remained elusive. Read More

Physical library collections are valuable and long standing resources for knowledge and learning. However, managing books in a large bookshelf and finding books on it often leads to tedious manual work, especially for large book collections where books might be missing or misplaced. Recently, deep neural models, such as Convolutional Neural Networks (CNN) and Recurrent Neural Networks (RNN) have achieved great success for scene text detection and recognition. Read More

Let $\mathcal{U}=\left[ \begin{array}{cc} \mathcal{A} & \mathcal{M} \mathcal{N}& \mathcal{B} \end{array} \right]$ be a generalized matrix ring, where $\mathcal{A}$ and $\mathcal{B}$ are 2-torsion free. We prove that if $\phi :\mathcal{U}\rightarrow \mathcal{U}$ is an additive mapping such that $\phi(U)\circ V+U\circ \phi(V)=0$ whenever $UV=VU=0,$ then $\phi=\delta+\eta$, where $\delta$ is a Jordan derivation and $\eta$ is a multiplier. As its applications, we prove that the similar conclusion remains valid on full matrix algebras, unital prime rings with a nontrivial idempotent, unital standard operator algebras, CDCSL algebras and von Neumann algebras. Read More

This article provides an interesting exploration of character-level convolutional neural network solving Chinese corpus text classification problem. We constructed a large-scale Chinese language dataset, and the result shows that character-level convolutional neural network works better on Chinese corpus than its corresponding pinyin format dataset. This is the first time that character-level convolutional neural network applied to text classification problem. Read More

Enhanced visible light photocatalytic activity of transition metal-doped ceria (CeO2) nanomaterials have experimentally been demonstrated, whereas there are very few reports mentioning the mechanism of this behavior. Here we use first-principles calculations to explore the origin of enhanced photocatalytic performance of CeO2 doped with transition metal impurities (Fe, Cr and Co). When a transition metal atom substitutes a Ce atom into CeO2, t2g and eg levels of 3d orbits appear in the middle of band gap owing to the effect of cubic ligand field, and the former is higher than latter. Read More

Multilayer van der Waals (vdWs) heterostructures assembled by diverse atomically thin layers have demonstrated a wide range of fascinating phenomena and novel applications. Understanding the interlayer coupling and its correlation effect is paramount for designing novel vdWs heterostructures with desirable physical properties. Using a detailed theoretical study of 2D MoS2-graphene (GR)-based heterostructures based on state-of-the-art hybrid density functional theory, we reveal that for 2D few-layer heterostructures, vdWs forces between neighboring layers depend on the number of layers. Read More

We reveal a novel topological property of the exceptional points in a two-level parity-time symmetric system and then propose a scheme to detect the topological exceptional points in the system, which is embedded in a larger Hilbert space constructed by a four-level cold atomic system. We show that a tunable parameter in the presented system for simulating the non-Hermitian Hamiltonian can be tuned to swept the eigenstates through the exceptional points in parameter space. The non-trivial Berry phases of the eigenstates obtained in this loop from the exceptional points can be measured by the atomic interferometry. Read More

Two-dimensional transition metal dichalcogenides (MX2)/metal oxide heterostructures have shown unique physical properties, making them promising materials for various applications ranging from photocatalysis to solar energy conversion. Understanding the interfacial interactions is highly desirable for designing these heterostructures having excellent performance. Here we systematically study the interfacial interaction in monolayer MX2 (M=Mo, W; X=S, Se)/CeO2 heterostructures and its effects on electronic and optical properties by density functional theory. Read More

A framework is presented for unsupervised learning of representations based on infomax principle for large-scale neural populations. We use an asymptotic approximation to the Shannon's mutual information for a large neural population to demonstrate that a good initial approximation to the global information-theoretic optimum can be obtained by a hierarchical infomax method. Starting from the initial solution, an efficient algorithm based on gradient descent of the final objective function is proposed to learn representations from the input datasets, and the method works for complete, overcomplete, and undercomplete bases. Read More

We prove that every 2-local derivation from the algebra $M_n(\mathcal{A})(n>2)$ into its bimodule $M_n(\mathcal{M})$ is a derivation, where $\mathcal{A}$ is a unital Banach algebra and $\mathcal{M}$ is a unital $\mathcal{A}$-bimodule such that each Jordan derivation from $\mathcal{A}$ into $\mathcal{M}$ is an inner derivation, and that every 2-local derivation on a C*-algebra with a faithful traceable representation is a derivation. We also characterize local and 2-local Lie derivations on some algebras such as von Neumann algebras, nest algebras, Jiang-Su algebra and UHF algebras. Read More

Information theory is a powerful tool for neuroscience and other disciplines. Efficient calculation of Shannon's mutual information (MI) is a key computational step that often presents the biggest difficulty for practical applications. In this paper, we propose effective approximation methods for evaluating MI in the context of neural population coding, especially for high-dimensional inputs. Read More

We characterize derivations and 2-local derivations from $M_{n}(\mathcal{A})$ into $M_{n}(\mathcal{M})$, $n \ge 2$, where $\mathcal{A}$ is a unital algebra over $\mathbb{C}$ and $\mathcal{M}$ is a unital $\mathcal{A}$-bimodule. We show that every derivation $D: M_{n}(\mathcal{A}) \to M_{n}(\mathcal{M})$, $n \ge 2,$ is the sum of an inner derivation and a derivation induced by a derivation from $\mathcal{A}$ to $\mathcal{M}$. We say that $\mathcal{A}$ commutes with $\mathcal{M}$ if $am=ma$ for every $a\in\mathcal{A}$ and $m\in\mathcal{M}$. Read More

Supersolidity is an intriguing concept. It combines the property of superfluid flow with the long-range spatial periodicity of solids, two properties which are often mutually exclusive. The original discussion of quantum crystals and supersolidity focuses on solid Helium-4 where it was predicted that vacancies could form dilute weakly interacting Bose-Einstein condensates. Read More

This paper considers metric spaces where distances between a pair of nodes are represented by distance intervals. The goal is to study methods for the determination of hierarchical clusters, i.e. Read More

Preservation of nonnengativity and boundedness in the finite element solution of Nagumo-type equations with general anisotropic diffusion is studied. Linear finite elements and the backward Euler scheme are used for the spatial and temporal discretization, respectively. An explicit, an implicit, and two hybrid explicit-implicit treatments for the nonlinear reaction term are considered. Read More

Knowledge base completion aims to infer new relations from existing information. In this paper, we propose path-augmented TransR (PTransR) model to improve the accuracy of link prediction. In our approach, we base PTransR model on TransR, which is the best one-hop model at present. Read More

Convolutional Neural Networks (CNNs) have made remarkable progress on scene recognition, partially due to these recent large-scale scene datasets, such as the Places and Places2. Scene categories are often defined by multi-level information, including local objects, global layout, and background environment, thus leading to large intra-class variations. In addition, with the increasing number of scene categories, label ambiguity has become another crucial issue in large-scale classification. Read More

We apply the transformation of mixing azimuthal and internal coordinate or mixing time and internal coordinate to a stack of N black M-branes to find the Melvin spacetime of a stack of N black D-branes with magnetic or electric flux in string theory, after the Kaluza-Klein reduction. We slightly extend previous formulas to investigate the external magnetic and electric effects on the butterfly effect and holographic mutual information. It shows that the Melvin fields do not modify the scrambling time and will enhance the mutual information. Read More

Drawing principles, or aesthetics, are important in graph drawing. They are used as criteria for algorithm design and for quality evaluation. Current aesthetics are described as visual properties that a drawing is required to have to be visually pleasing. Read More

We propose a novel Connectionist Text Proposal Network (CTPN) that accurately localizes text lines in natural image. The CTPN detects a text line in a sequence of fine-scale text proposals directly in convolutional feature maps. We develop a vertical anchor mechanism that jointly predicts location and text/non-text score of each fixed-width proposal, considerably improving localization accuracy. Read More

We demonstrate a hybrid distributed fiber sensing system for multi-parameter detection. The integration of phase-sensitive optical time domain reflectometry ({\Phi}-OTDR) and Brillouin optical time domain reflectometry (B-OTDR) enables measurement of vibration, temperature and strain. Exploiting the fast changing property of vibration and the static property of temperature and strain, the laser pulse width and intensity are modulated and then injected into the single-mode sensing fiber proportionally, so that the three concerned parameters can be extracted simultaneously by only one photo-detector and data acquisition channel. Read More

We provide a criterion for a point satisfying the required disjointness condition in Sarnak's M\"obius Disjointness Conjecture. As a direct application, we have that the conjecture holds for any topological model of an ergodic system with discrete spectrum. Read More

We define single electron spin qubits in a silicon MOS double quantum dot system. By mapping the qubit resonance frequency as a function of gate-induced electric field, the spectrum reveals an anticrossing that is consistent with an inter-valley spin-orbit coupling. We fit the data from which we extract an inter-valley coupling strength of 43 MHz. Read More

2016Aug
Authors: The CLIC, CLICdp collaborations, :, M. J. Boland, U. Felzmann, P. J. Giansiracusa, T. G. Lucas, R. P. Rassool, C. Balazs, T. K. Charles, K. Afanaciev, I. Emeliantchik, A. Ignatenko, V. Makarenko, N. Shumeiko, A. Patapenka, I. Zhuk, A. C. Abusleme Hoffman, M. A. Diaz Gutierrez, M. Vogel Gonzalez, Y. Chi, X. He, G. Pei, S. Pei, G. Shu, X. Wang, J. Zhang, F. Zhao, Z. Zhou, H. Chen, Y. Gao, W. Huang, Y. P. Kuang, B. Li, Y. Li, J. Shao, J. Shi, C. Tang, X. Wu, L. Ma, Y. Han, W. Fang, Q. Gu, D. Huang, X. Huang, J. Tan, Z. Wang, Z. Zhao, T. Laštovička, U. Uggerhoj, T. N. Wistisen, A. Aabloo, K. Eimre, K. Kuppart, S. Vigonski, V. Zadin, M. Aicheler, E. Baibuz, E. Brücken, F. Djurabekova, P. Eerola, F. Garcia, E. Haeggström, K. Huitu, V. Jansson, V. Karimaki, I. Kassamakov, A. Kyritsakis, S. Lehti, A. Meriläinen, R. Montonen, T. Niinikoski, K. Nordlund, K. Österberg, M. Parekh, N. A. Törnqvist, J. Väinölä, M. Veske, W. Farabolini, A. Mollard, O. Napoly, F. Peauger, J. Plouin, P. Bambade, I. Chaikovska, R. Chehab, M. Davier, W. Kaabi, E. Kou, F. LeDiberder, R. Pöschl, D. Zerwas, B. Aimard, G. Balik, J. -P. Baud, J. -J. Blaising, L. Brunetti, M. Chefdeville, C. Drancourt, N. Geoffroy, J. Jacquemier, A. Jeremie, Y. Karyotakis, J. M. Nappa, S. Vilalte, G. Vouters, A. Bernard, I. Peric, M. Gabriel, F. Simon, M. Szalay, N. van der Kolk, T. Alexopoulos, E. N. Gazis, N. Gazis, E. Ikarios, V. Kostopoulos, S. Kourkoulis, P. D. Gupta, P. Shrivastava, H. Arfaei, M. K. Dayyani, H. Ghasem, S. S. Hajari, H. Shaker, Y. Ashkenazy, H. Abramowicz, Y. Benhammou, O. Borysov, S. Kananov, A. Levy, I. Levy, O. Rosenblat, G. D'Auria, S. Di Mitri, T. Abe, A. Aryshev, T. Higo, Y. Makida, S. Matsumoto, T. Shidara, T. Takatomi, Y. Takubo, T. Tauchi, N. Toge, K. Ueno, J. Urakawa, A. Yamamoto, M. Yamanaka, R. Raboanary, R. Hart, H. van der Graaf, G. Eigen, J. Zalieckas, E. Adli, R. Lillestøl, L. Malina, J. Pfingstner, K. N. Sjobak, W. Ahmed, M. I. Asghar, H. Hoorani, S. Bugiel, R. Dasgupta, M. Firlej, T. A. Fiutowski, M. Idzik, M. Kopec, M. Kuczynska, J. Moron, K. P. Swientek, W. Daniluk, B. Krupa, M. Kucharczyk, T. Lesiak, A. Moszczynski, B. Pawlik, P. Sopicki, T. Wojtoń, L. Zawiejski, J. Kalinowski, M. Krawczyk, A. F. Żarnecki, E. Firu, V. Ghenescu, A. T. Neagu, T. Preda, I-S. Zgura, A. Aloev, N. Azaryan, J. Budagov, M. Chizhov, M. Filippova, V. Glagolev, A. Gongadze, S. Grigoryan, D. Gudkov, V. Karjavine, M. Lyablin, A. Olyunin, A. Samochkine, A. Sapronov, G. Shirkov, V. Soldatov, A. Solodko, E. Solodko, G. Trubnikov, I. Tyapkin, V. Uzhinsky, A. Vorozhtov, E. Levichev, N. Mezentsev, P. Piminov, D. Shatilov, P. Vobly, K. Zolotarev, I. Bozovic Jelisavcic, G. Kacarevic, S. Lukic, G. Milutinovic-Dumbelovic, M. Pandurovic, U. Iriso, F. Perez, M. Pont, J. Trenado, M. Aguilar-Benitez, J. Calero, L. Garcia-Tabares, D. Gavela, J. L. Gutierrez, D. Lopez, F. Toral, D. Moya, A. Ruiz Jimeno, I. Vila, T. Argyropoulos, C. Blanch Gutierrez, M. Boronat, D. Esperante, A. Faus-Golfe, J. Fuster, N. Fuster Martinez, N. Galindo Muñoz, I. García, J. Giner Navarro, E. Ros, M. Vos, R. Brenner, T. Ekelöf, M. Jacewicz, J. Ögren, M. Olvegård, R. Ruber, V. Ziemann, D. Aguglia, N. Alipour Tehrani, A. Andersson, F. Andrianala, F. Antoniou, K. Artoos, S. Atieh, R. Ballabriga Sune, M. J. Barnes, J. Barranco Garcia, H. Bartosik, C. Belver-Aguilar, A. Benot Morell, D. R. Bett, S. Bettoni, G. Blanchot, O. Blanco Garcia, X. A. Bonnin, O. Brunner, H. Burkhardt, S. Calatroni, M. Campbell, N. Catalan Lasheras, M. Cerqueira Bastos, A. Cherif, E. Chevallay, B. Constance, R. Corsini, B. Cure, S. Curt, B. Dalena, D. Dannheim, G. De Michele, L. De Oliveira, N. Deelen, J. P. Delahaye, T. Dobers, S. Doebert, M. Draper, F. Duarte Ramos, A. Dubrovskiy, K. Elsener, J. Esberg, M. Esposito, V. Fedosseev, P. Ferracin, A. Fiergolski, K. Foraz, A. Fowler, F. Friebel, J-F. Fuchs, C. A. Fuentes Rojas, A. Gaddi, L. Garcia Fajardo, H. Garcia Morales, C. Garion, L. Gatignon, J-C. Gayde, H. Gerwig, A. N. Goldblatt, C. Grefe, A. Grudiev, F. G. Guillot-Vignot, M. L. Gutt-Mostowy, M. Hauschild, C. Hessler, J. K. Holma, E. Holzer, M. Hourican, D. Hynds, Y. Inntjore Levinsen, B. Jeanneret, E. Jensen, M. Jonker, M. Kastriotou, J. M. K. Kemppinen, R. B. Kieffer, W. Klempt, O. Kononenko, A. Korsback, E. Koukovini Platia, J. W. Kovermann, C-I. Kozsar, I. Kremastiotis, S. Kulis, A. Latina, F. Leaux, P. Lebrun, T. Lefevre, L. Linssen, X. Llopart Cudie, A. A. Maier, H. Mainaud Durand, E. Manosperti, C. Marelli, E. Marin Lacoma, R. Martin, S. Mazzoni, G. Mcmonagle, O. Mete, L. M. Mether, M. Modena, R. M. Münker, T. Muranaka, E. Nebot Del Busto, N. Nikiforou, D. Nisbet, J-M. Nonglaton, F. X. Nuiry, A. Nürnberg, M. Olvegard, J. Osborne, S. Papadopoulou, Y. Papaphilippou, A. Passarelli, M. Patecki, L. Pazdera, D. Pellegrini, K. Pepitone, E. Perez Codina, A. Perez Fontenla, T. H. B. Persson, M. Petrič, F. Pitters, S. Pittet, F. Plassard, R. Rajamak, S. Redford, Y. Renier, S. F. Rey, G. Riddone, L. Rinolfi, E. Rodriguez Castro, P. Roloff, C. Rossi, V. Rude, G. Rumolo, A. Sailer, E. Santin, D. Schlatter, H. Schmickler, D. Schulte, N. Shipman, E. Sicking, R. Simoniello, P. K. Skowronski, P. Sobrino Mompean, L. Soby, M. P. Sosin, S. Sroka, S. Stapnes, G. Sterbini, R. Ström, I. Syratchev, F. Tecker, P. A. Thonet, L. Timeo, H. Timko, R. Tomas Garcia, P. Valerio, A. L. Vamvakas, A. Vivoli, M. A. Weber, R. Wegner, M. Wendt, B. Woolley, W. Wuensch, J. Uythoven, H. Zha, P. Zisopoulos, M. Benoit, M. Vicente Barreto Pinto, M. Bopp, H. H. Braun, M. Csatari Divall, M. Dehler, T. Garvey, J. Y. Raguin, L. Rivkin, R. Zennaro, A. Aksoy, Z. Nergiz, E. Pilicer, I. Tapan, O. Yavas, V. Baturin, R. Kholodov, S. Lebedynskyi, V. Miroshnichenko, S. Mordyk, I. Profatilova, V. Storizhko, N. Watson, A. Winter, J. Goldstein, S. Green, J. S. Marshall, M. A. Thomson, B. Xu, W. A. Gillespie, R. Pan, M. A Tyrk, D. Protopopescu, A. Robson, R. Apsimon, I. Bailey, G. Burt, D. Constable, A. Dexter, S. 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The Compact Linear Collider (CLIC) is a multi-TeV high-luminosity linear e+e- collider under development. For an optimal exploitation of its physics potential, CLIC is foreseen to be built and operated in a staged approach with three centre-of-mass energy stages ranging from a few hundred GeV up to 3 TeV. The first stage will focus on precision Standard Model physics, in particular Higgs and top-quark measurements. Read More

We consider indirect detection of meta-stable dark matter particles decaying into a stable neutral particle and a pair of standard model fermions. Due to the softer energy spectra from the three-body decay, such models could potentially explain the AMS-02 positron excess without being constrained by the Fermi-LAT gamma-ray data and the cosmic ray anti-proton measurements. We scrutinize over different final state fermions, paying special attention to handling of the cosmic ray background and including various contributions from cosmic ray propagation with the help of the \textsc{LikeDM} package. Read More

We propose a novel and simple mechanism where sizable effects of non-standard interactions (NSI) in neutrino propagation are induced from the mixing between an electrophilic second Higgs doublet and a charged singlet. The mixing arises from a dimensionful coupling of the scalar doublet and singlet to the standard model Higgs boson. In light of the small mass, the light mass eigenstate from the doublet-singlet mixing can generate much larger NSI than those induced by the heavy eigenstate. Read More