Y. F. Wang - Department of Astronomy, University of Geneva, Switzerland

Y. F. Wang
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Name
Y. F. Wang
Affiliation
Department of Astronomy, University of Geneva, Switzerland
City
Geneva
Country
Switzerland

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Computer Science - Learning (6)
 
Computer Science - Artificial Intelligence (5)
 
Statistics - Machine Learning (5)
 
Computer Science - Computer Vision and Pattern Recognition (4)
 
Physics - Materials Science (4)
 
Physics - Mesoscopic Systems and Quantum Hall Effect (4)
 
Computer Science - Computation and Language (3)
 
High Energy Physics - Experiment (3)
 
Statistics - Applications (3)
 
Statistics - Methodology (3)
 
Mathematics - Numerical Analysis (3)
 
Physics - Instrumentation and Detectors (2)
 
Physics - Plasma Physics (2)
 
Mathematics - Dynamical Systems (2)
 
Mathematics - Spectral Theory (2)
 
Mathematics - Functional Analysis (2)
 
Physics - Optics (2)
 
Computer Science - Computational Engineering; Finance; and Science (2)
 
Quantum Physics (2)
 
Computer Science - Logic in Computer Science (1)
 
Physics - Computational Physics (1)
 
Statistics - Theory (1)
 
Instrumentation and Methods for Astrophysics (1)
 
Quantitative Biology - Quantitative Methods (1)
 
Mathematics - Algebraic Topology (1)
 
Mathematics - Statistics (1)
 
Mathematics - K-Theory and Homology (1)
 
Physics - Fluid Dynamics (1)
 
Computer Science - Distributed; Parallel; and Cluster Computing (1)
 
Quantitative Biology - Neurons and Cognition (1)
 
Physics - Other (1)
 
Computer Science - Databases (1)
 
Physics - Atomic Physics (1)
 
Physics - Accelerator Physics (1)
 
Earth and Planetary Astrophysics (1)
 
Computer Science - Neural and Evolutionary Computing (1)
 
Cosmology and Nongalactic Astrophysics (1)
 
Physics - Disordered Systems and Neural Networks (1)
 
Physics - Soft Condensed Matter (1)
 
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Computer Science - Performance (1)

Publications Authored By Y. F. Wang

A key challenge for modern Bayesian statistics is how to perform scalable inference of posterior distributions. To address this challenge, VB methods have emerged as a popular alternative to the classical MCMC methods. VB methods tend to be faster while achieving comparable predictive performance. Read More

We establish spherical variants of the Gleason-Kahane-Zelazko and Kowalski-S{\l}odkowski theorems, and we apply them to prove that every weak-2-local isometry between two uniform algebras is a linear map. Among the consequences, we solve a couple of problems posed by O. Hatori, T. Read More

It has been shown that Chinese poems can be successfully generated by sequence-to-sequence neural models, particularly with the attention mechanism. A potential problem of this approach, however, is that neural models can only learn abstract rules, while poem generation is a highly creative process that involves not only rules but also innovations for which pure statistical models are not appropriate in principle. This work proposes a memory-augmented neural model for Chinese poem generation, where the neural model and the augmented memory work together to balance the requirements of linguistic accordance and aesthetic innovation, leading to innovative generations that are still rule-compliant. Read More

By using first-principles calculation, the interaction of O2 and H2O molecules with the pristine and the defective InSe monolayers is studied. It is predicted that the single Se and In vacancies exhibit significantly enhanced chemical activity toward the adsorbates compared with the perfect InSe lattice site, and the Se vacancies have a much higher chemical activity than the In vacancies. H2O molecule should be only physisorbed on the various InSe monolayers at ambient conditions, according to the calculated energies. Read More

In this paper, we use simplicial Waldhausen theory to show the geometric realization of the topologized category of bounded chain complexes over $\mathbb{F}=\mathbb{C}$ (resp. $\mathbb{R}$) is an infinite loop space that represents connective complex (resp. real) topological $K$-theory. Read More

This paper presents the development of an Adaptive Algebraic Multiscale Solver for Compressible flow (C-AMS) in heterogeneous porous media. Similar to the recently developed AMS for incompressible (linear) flows [Wang et al., JCP, 2014], C-AMS operates by defining primal and dual-coarse blocks on top of the fine-scale grid. Read More

In this paper, we propose a single-agent logic of goal-directed knowing how extending the standard epistemic logic of knowing that with a new knowing how operator. The semantics of the new operator is based on the idea that knowing how to achieve $\phi$ means that there exists a (uniform) strategy such that the agent knows that it can make sure $\phi$. We give an intuitive axiomatization of our logic and prove the soundness, completeness, and decidability of the logic. Read More

Knowledge Graphs are important tools to model multi-relational data that serves as information pool for various applications. Traditionally, these graphs are considered to be static in nature. However, recent availability of large scale event-based interaction data has given rise to dynamically evolving knowledge graphs that contain temporal information for each edge. Read More

Electrons in two-dimensional graphene sheets behave as interacting chiral Dirac fermions and have unique screening properties due to their symmetry and reduced dimensionality. By using a combination of scanning tunneling spectroscopy (STM/STS) measurements and theoretical modeling we have characterized how graphene's massless charge carriers screen individual charged calcium atoms. A back-gated graphene device configuration has allowed us to directly visualize how the screening length for this system can be tuned with carrier density. Read More

We consider the problem of scheduling a group of heterogeneous, distributed processes, with different relative priorities and service preferences, to a group of heterogeneous virtual machines. Assuming linearly elastic IT resource needs, we extend prior results on proportional fair and max-min fair scheduling to a constrained multiresource case for a fam- ily of fairness criteria (including our recently proposed Per- Server Dominant-Share Fairness). Performance comparison is made by illustrative numerical example. Read More

Capacitively coupled radio-frequency (CCRF) CF_4 plasmas have been found to exhibit a self-organized striated structure at operating conditions, where the plasma is strongly electronegative and the ion-ion plasma in the bulk region (largely composed of CF_3^+ and F^- ions) resonates with the excitation frequency. In this work we explore the effects of the gas pressure, the RF voltage, and the electrode gap on this striated structure by Phase Resolved Optical Emission Spectroscopy and Particle-In-Cell/Monte Carlo Collisions simulations. The measured electronic excitation patterns at different external parameters show a good general agreement with the spatio-temporal plots of the ionization rate obtained from the simulations. Read More

The optomechanics can generate fantastic effects of optics due to appropriate mechanical control. Here we theoretically study effects of slow and fast lights in a single-sided optomechanical cavity with an external force. The force-induced transparency of slow/fast light and the force-dependent conversion between the slow and fast lights are resulted from involvement of anti-Stokes and Stokes processes, which can be controlled by properly modifying the effective cavity frequency due to the external force. Read More

The phosphorous activation in Ge n$^{+}$/p junctions is compared in terms of junction depth, by using laser spike annealing at 860{\deg}C for 400$\mu$s. The reverse junction leakage is found to strongly depend on the abruptness of dopant profiles. A shallow and abrupt junction is shown to have lower phosphorous activation level, due to surface dose loss, and higher band-to-band tunneling (BTBT) leakage, when compared to the deep junction. Read More

2017May
Authors: BESIII Collaboration, M. Ablikim, M. N. Achasov, S. Ahmed, M. Albrecht, M. Alekseev, A. Amoroso, F. F. An, Q. An, J. Z. Bai, Y. Bai, O. Bakina, R. Baldini Ferroli, Y. Ban, D. W. Bennett, J. V. Bennett, N. Berger, M. Bertani, D. Bettoni, J. M. Bian, F. Bianchi, E. Boger, I. Boyko, R. A. Briere, H. Cai, X. Cai, O. Cakir, A. Calcaterra, G. F. Cao, S. A. Cetin, J. Chai, J. F. Chang, G. Chelkov, G. Chen, H. S. Chen, J. C. Chen, M. L. Chen, S. J. Chen, X. R. Chen, Y. B. Chen, X. K. Chu, G. Cibinetto, H. L. Dai, J. P. Dai, A. Dbeyssi, D. Dedovich, Z. Y. Deng, A. Denig, I. Denysenko, M. Destefanis, F. De Mori, Y. Ding, C. Dong, J. Dong, L. Y. Dong, M. Y. Dong, O. Dorjkhaidav, Z. L. Dou, S. X. Du, P. F. Duan, J. Fang, S. S. Fang, X. Fang, Y. Fang, R. Farinelli, L. Fava, S. Fegan, F. Feldbauer, G. Felici, C. Q. Feng, E. Fioravanti, M. Fritsch, C. D. Fu, Q. Gao, X. L. Gao, Y. Gao, Y. G. Gao, Z. Gao, B. Garillon, I. Garzia, K. Goetzen, L. Gong, W. X. Gong, W. Gradl, M. Greco, M. H. Gu, S. Gu, Y. T. Gu, A. Q. Guo, L. B. Guo, R. P. Guo, Y. P. Guo, Z. Haddadi, S. Han, X. Q. Hao, F. A. Harris, K. L. He, X. Q. He, F. H. Heinsius, T. Held, Y. K. Heng, T. Holtmann, Z. L. Hou, C. Hu, H. M. Hu, T. Hu, Y. Hu, G. S. Huang, J. S. Huang, S. H. Huang, X. T. Huang, X. Z. Huang, Z. L. Huang, T. Hussain, W. Ikegami Andersson, Q. Ji, Q. P. Ji, X. B. Ji, X. L. Ji, X. S. Jiang, X. Y. Jiang, J. B. Jiao, Z. Jiao, D. P. Jin, S. Jin, Y. Jin, T. Johansson, A. Julin, N. Kalantar-Nayestanaki, X. L. Kang, X. S. Kang, M. Kavatsyuk, B. C. Ke, T. Khan, A. Khoukaz, P. Kiese, R. Kliemt, L. Koch, O. B. Kolcu, B. Kopf, M. Kornicer, M. Kuemmel, M. Kuhlmann, A. Kupsc, W. Kühn, J. S. Lange, M. Lara, P. Larin, L. Lavezzi, H. Leithoff, C. Leng, C. Li, Cheng Li, D. M. Li, F. Li, F. Y. Li, G. Li, H. B. Li, H. J. Li, J. C. Li, Jin Li, K. Li, K. Li, K. J. Li, Lei Li, P. L. Li, P. R. Li, Q. Y. Li, T. Li, W. D. Li, W. G. Li, X. L. Li, X. N. Li, X. Q. Li, Z. B. Li, H. Liang, Y. F. Liang, Y. T. Liang, G. R. Liao, D. X. Lin, B. Liu, B. J. Liu, C. X. Liu, D. Liu, F. H. Liu, Fang Liu, Feng Liu, H. B. Liu, H. H. Liu, H. H. Liu, H. M. Liu, J. B. Liu, J. Y. Liu, K. Liu, K. Y. Liu, Ke Liu, L. D. Liu, P. L. Liu, Q. Liu, S. B. Liu, X. Liu, Y. B. Liu, Z. A. Liu, Zhiqing Liu, Y. F. Long, X. C. Lou, H. J. Lu, J. G. Lu, Y. Lu, Y. P. Lu, C. L. Luo, M. X. Luo, X. L. Luo, X. R. Lyu, F. C. Ma, H. L. Ma, L. L. Ma, M. M. Ma, Q. M. Ma, T. Ma, X. N. Ma, X. Y. Ma, Y. M. Ma, F. E. Maas, M. Maggiora, Q. A. Malik, Y. J. Mao, Z. P. Mao, S. Marcello, Z. X. Meng, J. G. Messchendorp, G. Mezzadri, J. Min, T. J. Min, R. E. Mitchell, X. H. Mo, Y. J. Mo, C. Morales Morales, G. Morello, N. Yu. Muchnoi, H. Muramatsu, A. Mustafa, Y. Nefedov, F. Nerling, I. B. Nikolaev, Z. Ning, S. Nisar, S. L. Niu, X. Y. Niu, S. L. Olsen, Q. Ouyang, S. Pacetti, Y. Pan, M. Papenbrock, P. Patteri, M. Pelizaeus, J. Pellegrino, H. P. Peng, K. Peters, J. Pettersson, J. L. Ping, R. G. Ping, A. Pitka, R. Poling, V. Prasad, H. R. Qi, M. Qi, T. . Y. Qi, S. Qian, C. F. Qiao, N. Qin, X. S. Qin, Z. H. Qin, J. F. Qiu, K. H. Rashid, C. F. Redmer, M. Richter, M. Ripka, M. Rolo, G. Rong, Ch. Rosner, A. Sarantsev, M. Savrié, C. Schnier, K. Schoenning, W. Shan, M. Shao, C. P. Shen, P. X. Shen, X. Y. Shen, H. Y. Sheng, M. R. Shepherd, J. J. Song, W. M. Song, X. Y. Song, S. Sosio, C. Sowa, S. Spataro, G. X. Sun, J. F. Sun, L. Sun, S. S. Sun, X. H. Sun, Y. J. Sun, Y. K Sun, Y. Z. Sun, Z. J. Sun, Z. T. Sun, C. J. Tang, G. Y. Tang, X. Tang, I. Tapan, M. Tiemens, B. T. Tsednee, I. Uman, G. S. Varner, B. Wang, B. L. Wang, D. Wang, D. Y. Wang, Dan Wang, K. Wang, L. L. Wang, L. S. Wang, M. Wang, P. Wang, P. L. Wang, W. P. Wang, X. F. Wang, Y. Wang, Y. D. Wang, Y. F. Wang, Y. Q. Wang, Z. Wang, Z. G. Wang, Z. H. Wang, Z. Y. Wang, Z. Y. Wang, T. Weber, D. H. Wei, J. H. Wei, P. Weidenkaff, S. P. Wen, U. Wiedner, M. Wolke, L. H. Wu, L. J. Wu, Z. Wu, L. Xia, Y. Xia, D. Xiao, H. Xiao, Y. J. Xiao, Z. J. Xiao, X. H. Xie, Y. G. Xie, Y. H. Xie, X. A. Xiong, Q. L. Xiu, G. F. Xu, J. J. Xu, L. Xu, Q. J. Xu, Q. N. Xu, X. P. Xu, L. Yan, W. B. Yan, W. C. Yan, Y. H. Yan, H. J. Yang, H. X. Yang, L. Yang, Y. H. Yang, Y. X. Yang, M. Ye, M. H. Ye, J. H. Yin, Z. Y. You, B. X. Yu, C. X. Yu, J. S. Yu, C. Z. Yuan, Y. Yuan, A. Yuncu, A. A. Zafar, Y. Zeng, Z. Zeng, B. X. Zhang, B. Y. Zhang, C. C. Zhang, D. H. Zhang, H. H. Zhang, H. Y. Zhang, J. Zhang, J. L. Zhang, J. Q. Zhang, J. W. Zhang, J. Y. Zhang, J. Z. Zhang, K. Zhang, L. Zhang, S. Q. Zhang, X. Y. Zhang, Y. Zhang, Y. Zhang, Y. H. Zhang, Y. T. Zhang, Yu Zhang, Z. H. Zhang, Z. P. Zhang, Z. Y. Zhang, G. Zhao, J. W. Zhao, J. Y. Zhao, J. Z. Zhao, Lei Zhao, Ling Zhao, M. G. Zhao, Q. Zhao, S. J. Zhao, T. C. Zhao, Y. B. Zhao, Z. G. Zhao, A. Zhemchugov, B. Zheng, J. P. Zheng, W. J. Zheng, Y. H. Zheng, B. Zhong, L. Zhou, X. Zhou, X. K. Zhou, X. R. Zhou, X. Y. Zhou, J. Zhu, K. Zhu, K. J. Zhu, S. Zhu, S. H. Zhu, X. L. Zhu, Y. C. Zhu, Y. S. Zhu, Z. A. Zhu, J. Zhuang, B. S. Zou, J. H. Zou

We present first evidence for the process $e^+e^-\to \gamma\eta_c(1S)$ at six center-of-mass energies between 4.01 and 4.60~GeV using data collected by the BESIII experiment operating at BEPCII. Read More

Recent diffraction experiments on metallic glasses have unveiled an unexpected non-cubic scaling law between density and average interatomic distance, which lead to the speculations on the presence of fractal glass order. Using X-ray tomography we identify here a similar non-cubic scaling law in disordered granular packing of spherical particles. We find that the scaling law is directly related to the contact neighbors within first nearest neighbor shell, and therefore is closely connected to the phenomenon of jamming. Read More

It is shown that the concept of topological phase transitions can be used to design nonlinear photonic structures exhibiting power thresholds and discontinuities in their transmittance. This provides a novel route to devising nonlinear optical isolators. We study three representative designs: (i) a waveguide array implementing a nonlinear 1D Su-Schrieffer-Heeger (SSH) model, (ii) a waveguide array implementing a nonlinear 2D Haldane model, and (iii) a 2D lattice of coupled-ring waveguides. Read More

Previous studies by our group have shown that three-dimensional high-frequency quantitative ultrasound methods have the potential to differentiate metastatic lymph nodes from cancer-free lymph nodes dissected from human cancer patients. To successfully perform these methods inside the lymph node parenchyma, an automatic segmentation method is highly desired to exclude the surrounding thin layer of fat from quantitative ultrasound processing and accurately correct for ultrasound attenuation. In high-frequency ultrasound images of lymph nodes, the intensity distribution of lymph node parenchyma and fat varies spatially because of acoustic attenuation and focusing effects. Read More

In this paper, we extend an attention-based neural machine translation (NMT) model by allowing it to access an entire training set of parallel sentence pairs even after training. The proposed approach consists of two stages. In the first stage--retrieval stage--, an off-the-shelf, black-box search engine is used to retrieve a small subset of sentence pairs from a training set given a source sentence. Read More

Elucidating the interaction between magnetic moments and itinerant carriers is an important step to spintronic applications. Here, we investigate magnetic and transport properties in d0 ferromagnetic SiC single crystals prepared by postimplantation pulsed laser annealing. Magnetic moments are contributed by the p states of carbon atoms, but their magnetic circular dichroism is different from that in semi-insulating SiC samples. Read More

In this paper, a sixth order energy-conserved method is proposed for solving the three-dimensional time-domain Maxwell's equations. Based on the method of lines, the spatial derivatives of the Maxwell's equations are approximated with the aid of Fourier pseudo-spectral methods. The resulting ordinary differential equations can be cast as a canonical Hamiltonian system. Read More

We present ten $R$-band photometric observations of eight different transits of the hot Jupiter HAT-P-33b, which has been targeted by our Transiting Exoplanet Monitoring Project (TEMP). The data were obtained by two telescopes at the Xinglong Station of National Astronomical Observatories of China (NAOC) from 2013 December through 2016 January, and exhibit photometric scatter of $1.6-3. Read More

In this paper, we first use the super-sub solution method to prove the local exponential asymptotic stability of some entire solutions to reaction diffusion equations, including the bistable and monostable cases. In the bistable case, we not only obtain the similar asymptotic stability result given by Yagisita in 2003, but also simplify his proof. For the monostable case, it is the first time to discuss the local asymptotic stability of entire solutions. Read More

In this paper we are concerned with the entire solutions for the classical competitive Lotka-Volterra system with diffusion in the weak competition. For this purpose we firstly analyze the asymptotic behavior of traveling front solutions for this system connecting the origin and the positive equilibrium. Then, by using two different ways to construct pairs of coupled super-sub solutions of this system, we obtain two different kinds of entire solutions. Read More

This paper presents two unsupervised learning layers (UL layers) for label-free video analysis: one for fully connected layers, and the other for convolutional ones. The proposed UL layers can play two roles: they can be the cost function layer for providing global training signal; meanwhile they can be added to any regular neural network layers for providing local training signals and combined with the training signals backpropagated from upper layers for extracting both slow and fast changing features at layers of different depths. Therefore, the UL layers can be used in either pure unsupervised or semi-supervised settings. Read More

Sparsity helps reduce the computational complexity of deep neural networks by skipping zeros. Taking advantage of sparsity is listed as a high priority in next generation DNN accelerators such as TPU. The structure of sparsity, i. Read More

Artificial defects embedded in periodic structures are important foundation for creating localized states with vast range of applications in condensed matter physics, photonics and acoustics. In photonics, localized states are extensively used to confine and manipulate photons. Up to now, all the proposed localized states are reciprocal and restricted by time reversal symmetry. Read More

In voxel-based neuroimage analysis, lesion features have been the main focus in disease prediction due to their interpretability with respect to the related diseases. However, we observe that there exists another type of features introduced during the preprocessing steps and we call them "\textbf{Procedural Bias}". Besides, such bias can be leveraged to improve classification accuracy. Read More

Mapping relationships, such as (country, country-code) or (company, stock-ticker), are versatile data assets for an array of applications in data cleaning and data integration like auto-correction and auto-join. However, today there are no good repositories of mapping tables that can enable these intelligent applications. Given a corpus of tables such as web tables or spreadsheet tables, we observe that values of these mappings often exist in pairs of columns in same tables. Read More

Retention of plasma-implanted D is studied in W targets damaged by a Cu ion beam at up to 0.2 dpa with sample temperatures between 300 K and 1200 K. At a D plasma ion fluence of $10^{24}/m^2$ on samples damaged to 0. Read More

Learning Bayesian networks using both observational and interventional data is now a fundamentally important problem due to recent technological developments in genomics that generate such single-cell gene expression data at a very large scale. In order to utilize this data for learning gene regulatory networks, efficient and reliable causal inference algorithms are needed that can make use of both observational and interventional data. In this paper, we present two algorithms of this type and prove that both are consistent under the faithfulness assumption. Read More

In genetic epidemiological studies, family history data are collected on relatives of study participants and used to estimate the age-specific risk of disease for individuals who carry a causal mutation. However, a family member's genotype data may not be collected due to the high cost of in-person interview to obtain blood sample or death of a relative. Previously, efficient nonparametric genotype-specific risk estimation in censored mixture data has been proposed without considering covariates. Read More

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

2017May
Authors: BESIII Collaboration, M. Ablikim, M. N. Achasov, S. Ahmed, X. C. Ai, O. Albayrak, M. Albrecht, D. J. Ambrose, A. Amoroso, F. F. An, Q. An, J. Z. Bai, R. Baldini Ferroli, Y. Ban, D. W. Bennett, J. V. Bennett, N. Berger, M. Bertani, D. Bettoni, J. M. Bian, F. Bianchi, E. Boger, I. Boyko, R. A. Briere, H. Cai, X. Cai, O. Cakir, A. Calcaterra, G. F. Cao, S. A. Cetin, J. Chai, J. F. Chang, G. Chelkov, G. Chen, H. S. Chen, J. C. Chen, M. L. Chen, S. Chen, S. J. Chen, X. Chen, X. R. Chen, Y. B. Chen, H. P. Cheng, X. K. Chu, G. Cibinetto, H. L. Dai, J. P. Dai, A. Dbeyssi, D. Dedovich, Z. Y. Deng, A. Denig, I. Denysenko, M. Destefanis, F. De Mori, Y. Ding, C. Dong, J. Dong, L. Y. Dong, M. Y. Dong, Z. L. Dou, S. X. Du, P. F. Duan, J. Z. Fan, J. Fang, S. S. Fang, X. Fang, Y. Fang, R. Farinelli, L. Fava, O. Fedorov, F. Feldbauer, G. Felici, C. Q. Feng, E. Fioravanti, M. Fritsch, C. D. Fu, Q. Gao, X. L. Gao, Y. Gao, Z. Gao, I. Garzia, K. Goetzen, L. Gong, W. X. Gong, W. Gradl, M. Greco, M. H. Gu, Y. T. Gu, Y. H. Guan, A. Q. Guo, L. B. Guo, R. P. Guo, Y. Guo, Y. P. Guo, Z. Haddadi, A. Hafner, S. Han, X. Q. Hao, F. A. Harris, K. L. He, F. H. Heinsius, T. Held, Y. K. Heng, T. Holtmann, Z. L. Hou, C. Hu, H. M. Hu, J. F. Hu, T. Hu, Y. Hu, G. S. Huang, J. S. Huang, X. T. Huang, X. Z. Huang, Y. Huang, Z. L. Huang, T. Hussain, Q. Ji, Q. P. Ji, X. B. Ji, X. L. Ji, L. W. Jiang, X. S. Jiang, X. Y. Jiang, J. B. Jiao, Z. Jiao, D. P. Jin, S. Jin, T. Johansson, A. Julin, N. Kalantar-Nayestanaki, X. L. Kang, X. S. Kang, M. Kavatsyuk, B. C. Ke, P. Kiese, R. Kliemt, B. Kloss, O. B. Kolcu, B. Kopf, M. Kornicer, A. Kupsc, W. Kühn, J. S. Lange, M. Lara, P. Larin, H. Leithoff, C. Leng, C. Li, Cheng Li, D. M. Li, F. Li, F. Y. Li, G. Li, H. B. Li, H. J. Li, J. C. Li, Jin Li, K. Li, K. Li, Lei Li, P. R. Li, Q. Y. Li, T. Li, W. D. Li, W. G. Li, X. L. Li, X. N. Li, X. Q. Li, Y. B. Li, Z. B. Li, H. Liang, Y. F. Liang, Y. T. Liang, G. R. Liao, D. X. Lin, B. Liu, B. J. Liu, C. X. Liu, D. Liu, F. H. Liu, Fang Liu, Feng Liu, H. B. Liu, H. H. Liu, H. H. Liu, H. M. Liu, J. Liu, J. B. Liu, J. P. Liu, J. Y. Liu, K. Liu, K. Y. Liu, L. D. Liu, P. L. Liu, Q. Liu, S. B. Liu, X. Liu, Y. B. Liu, Y. Y. Liu, Z. A. Liu, Zhiqing Liu, H. Loehner, Y. F. Long, X. C. Lou, H. J. Lu, J. G. Lu, Y. Lu, Y. P. Lu, C. L. Luo, M. X. Luo, T. Luo, X. L. Luo, X. R. Lyu, F. C. Ma, H. L. Ma, L. L. Ma, M. M. Ma, Q. M. Ma, T. Ma, X. N. Ma, X. Y. Ma, Y. M. Ma, F. E. Maas, M. Maggiora, Q. A. Malik, Y. J. Mao, Z. P. Mao, S. Marcello, J. G. Messchendorp, G. Mezzadri, J. Min, T. J. Min, R. E. Mitchell, X. H. Mo, Y. J. Mo, C. Morales Morales, N. Yu. Muchnoi, H. Muramatsu, P. Musiol, Y. Nefedov, F. Nerling, I. B. Nikolaev, Z. Ning, S. Nisar, S. L. Niu, X. Y. Niu, S. L. Olsen, Q. Ouyang, S. Pacetti, Y. Pan, P. Patteri, M. Pelizaeus, H. P. Peng, K. Peters, J. Pettersson, J. L. Ping, R. G. Ping, R. Poling, V. Prasad, H. R. Qi, M. Qi, S. Qian, C. F. Qiao, L. Q. Qin, N. Qin, X. S. Qin, Z. H. Qin, J. F. Qiu, K. H. Rashid, C. F. Redmer, M. Ripka, G. Rong, Ch. Rosner, X. D. Ruan, A. Sarantsev, M. Savrié, C. Schnier, K. Schoenning, S. Schumann, W. Shan, M. Shao, C. P. Shen, P. X. Shen, X. Y. Shen, H. Y. Sheng, M. Shi, W. M. Song, X. Y. Song, S. Sosio, S. Spataro, G. X. Sun, J. F. Sun, S. S. Sun, X. H. Sun, Y. J. Sun, Y. Z. Sun, Z. J. Sun, Z. T. Sun, C. J. Tang, X. Tang, I. Tapan, E. H. Thorndike, M. Tiemens, I. Uman, G. S. Varner, B. Wang, B. L. Wang, D. Wang, D. Y. Wang, K. Wang, L. L. Wang, L. S. Wang, M. Wang, P. Wang, P. L. Wang, W. Wang, W. P. Wang, X. F. Wang, Y. Wang, Y. D. Wang, Y. F. Wang, Y. Q. Wang, Z. Wang, Z. G. Wang, Z. H. Wang, Z. Y. Wang

To study the nature of the state $Y(2175)$, a dedicated data set of $e^+e^-$ collision data was collected at the center-of-mass energy of 2.125 GeV with the BESIII detector at the BEPCII collider. By analyzing large-angle Bhabha scattering events, the integrated luminosity of this data set is determined to be $108. Read More

We report the trapping of ultracold 87Rb atoms in a 0.7 micron-period 2D triangular magnetic lattice on an atom chip. The magnetic lattice is created by a lithographically patterned magnetic Co/Pd multilayer film plus bias fields. Read More

The quantum anomalous Hall (QAH) phase is a novel topological state of matter characterized by a nonzero quantized Hall conductivity without an external magnetic field. The realizations of QAH effect, however, are experimentally challengeable. Based on ab initio calculations, here we propose an intrinsic QAH phase in DCA Kagome lattice. Read More

Given large amount of real photos for training, Convolutional neural network shows excellent performance on object recognition tasks. However, the process of collecting data is so tedious and the background are also limited which makes it hard to establish a perfect database. In this paper, our generative model trained with synthetic images rendered from 3D models reduces the workload of data collection and limitation of conditions. Read More

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

Acoustic ranging based indoor positioning solutions have the advantage of higher ranging accuracy and better compatibility with commercial-off-the-self consumer devices. However, similar to other time-domain based approaches using Time-of-Arrival and Time-Difference-of-Arrival, they suffer from performance degradation in presence of multi-path propagation and low received signal-to-noise ratio (SNR) in indoor environments. In this paper, we improve upon our previous work on asynchronous acoustic indoor positioning and develop ARABIS, a robust and low-cost acoustic positioning system (IPS) for mobile devices. Read More

A number of real world problems in many domains (e.g. sociology, biology, political science and communication networks) can be modeled as dynamic networks with nodes representing entities of interest and edges representing interactions among the entities at different points in time. Read More

2017May
Authors: C. E. Aalseth, F. Acerbi, P. Agnes, I. F. M. Albuquerque, T. Alexander, A. Alici, A. K. Alton, P. Ampudia, P. Antonioli, S. Arcelli, R. Ardito, I. J. Arnquist, D. M. Asner, H. O. Back, G. Batignani, E. Bertoldo, S. Bettarini, M. G. Bisogni, V. Bocci, A. Bondar, G. Bonfini, W. Bonivento, M. Bossa, B. Bottino, R. Bunker, S. Bussino, A. Buzulutskov, M. Cadeddu, M. Cadoni, A. Caminata, N. Canci, A. Candela, C. Cantini, M. Caravati, M. Cariello, M. Carlini, M. Carpinelli, A. Castellani, S. Catalanotti, V. Cataudella, P. Cavalcante, R. Cereseto, Y. Chen, A. Chepurnov, A. Chiavassa, C. Cicalò, L. Cifarelli, M. Citterio, A. G. Cocco, M. Colocci, S. Corgiolu, G. Covone, P. Crivelli, I. D'Antone, M. D'Incecco, M. D. Da Rocha Rolo, M. Daniel, S. Davini, A. De Candia, S. De Cecco, M. De Deo, G. De Filippis, G. De Guido, G. De Rosa, G. Dellacasa, P. Demontis, A. V. Derbin, A. Devoto, F. Di Eusanio, G. Di Pietro, C. Dionisi, A. Dolgov, I. Dormia, S. Dussoni, A. Empl, A. Ferri, C. Filip, G. Fiorillo, K. Fomenko, D. Franco, G. E. Froudakis, F. Gabriele, A. Gabrieli, C. Galbiati, P. Garcia Abia, A. Gendotti, A. Ghisi, S. Giagu, G. Gibertoni, C. Giganti, M. Giorgi, G. K. Giovanetti, M. L. Gligan, A. Gola, O. Gorchakov, A. M. Goretti, F. Granato, M. Grassi, J. W. Grate, G. Y. Grigoriev, M. Gromov, M. Guan, M. B. B. Guerra, M. Guerzoni, M. Gulino, R. K. Haaland, B. Harrop, E. W. Hoppe, S. Horikawa, B. Hosseini, D. Hughes, P. Humble, E. V. Hungerford, An. Ianni, S. Jimenez Cabre, T. N. Johnson, K. Keeter, C. L. Kendziora, S. Kim, G. Koh, D. Korablev, G. Korga, A. Kubankin, R. Kugathasan, M. Kuss, X. Li, M. Lissia, G. U. Lodi, B. Loer, G. Longo, R. Lussana, L. Luzzi, Y. Ma, A. A. Machado, I. N. Machulin, L. Mais, A. Mandarano, L. Mapelli, M. Marcante, A. Margotti, S. M. Mari, M. Mariani, J. Maricic, M. Marinelli, D. Marras, C. J. Martoff, M. Mascia, A. Messina, P. D. Meyers, R. Milincic, A. Moggi, S. Moioli, S. Monasterio, J. Monroe, A. Monte, M. Morrocchi, W. Mu, V. N. Muratova, S. Murphy, P. Musico, R. Nania, J. Napolitano, A. Navrer Agasson, I. Nikulin, V. Nosov, A. O. Nozdrina, N. N. Nurakhov, A. Oleinik, V. Oleynikov, M. Orsini, F. Ortica, L. Pagani, M. Pallavicini, S. Palmas, L. Pandola, E. Pantic, E. Paoloni, G. Paternoster, V. Pavletcov, F. Pazzona, K. Pelczar, L. A. Pellegrini, N. Pelliccia, F. Perotti, R. Perruzza, C. Piemonte, F. Pilo, A. Pocar, D. Portaluppi, S. S. Poudel, D. A. Pugachev, H. Qian, B. Radics, F. Raffaelli, F. Ragusa, K. Randle, M. Razeti, A. Razeto, V. Regazzoni, C. Regenfus, B. Reinhold, A. L. Renshaw, M. Rescigno, Q. Riffard, A. Rivetti, A. Romani, L. Romero, B. Rossi, N. Rossi, A. Rubbia, D. Sablone, P. Salatino, O. Samoylov, W. Sands, M. Sant, R. Santorelli, C. Savarese, E. Scapparone, B. Schlitzer, G. Scioli, E. Sechi, E. Segreto, A. Seifert, D. A. Semenov, S. Serci, A. Shchagin, L. Shekhtman, E. Shemyakina, A. Sheshukov, M. Simeone, P. N. Singh, M. D. Skorokhvatov, O. Smirnov, G. Sobrero, A. Sokolov, A. Sotnikov, C. Stanford, G. B. Suffritti, Y. Suvorov, R. Tartaglia, G. Testera, A. Tonazzo, A. Tosi, P. Trinchese, E. V. Unzhakov, A. Vacca, M. Verducci, T. Viant, F. Villa, A. Vishneva, B. Vogelaar, M. Wada, J. Wahl, S. Walker, H. Wang, Y. Wang, A. W. Watson, S. Westerdale, J. Wilhelmi, R. Williams, M. M. Wojcik, S. Wu, X. Xiang, X. Xiao, C. Yang, Z. Ye, F. Zappa, G. Zappalà, C. Zhu, A. Zichichi, G. Zuzel

We report on the cryogenic characterization of Red Green Blue - High Density (RGB-HD) SiPMs developed at Fondazione Bruno Kessler (FBK) as part of the DarkSide program of dark matter searches with liquid argon time projection chambers. A dedicated setup was used to measure the primary dark noise, the correlated noise, and the gain of the SiPMs at varying temperatures. A custom-made data acquisition system and analysis software were used to precisely characterize these parameters. Read More

Because of the limitations of matrix factorization, such as losing spatial structure information, the concept of low-rank tensor factorization (LRTF) has been applied for the recovery of a low dimensional subspace from high dimensional visual data. The low-rank tensor recovery is generally achieved by minimizing the loss function between the observed data and the factorization representation. The loss function is designed in various forms under different noise distribution assumptions, like $L_1$ norm for Laplacian distribution and $L_2$ norm for Gaussian distribution. Read More

We present measurements of the Baryon Acoustic Oscillation (BAO) scale in redshift-space using the clustering of quasars. We consider a sample of 147,000 quasars from the extended Baryon Oscillation Spectroscopic Survey (eBOSS) distributed over 2044 square degrees with redshifts $0.8 < z < 2. Read More

In this note, for any two orthogonal projection $P,Q$ on a Hilbert space, the characterization of spectrum of anticommutator $PQ+QP$ has been obtained. As a corollary, the norm formula $$\parallel PQ+QP\parallel=\parallel PQ\parallel+\parallel PQ\parallel^2$$ has been got an alternative proof (see Sam Waltrs, Anticommutator norm formula for projection operators, arXiv:1604.00699vl [math. Read More

The vertical configuration is a powerful tool recently developed experimentally to investigate field effects in quasi 2D systems. Prototype graphene-based vertical tunneling transistors can achieve an extraordinary control over current density utilizing gate voltages. In this work we study theoretically vertical tunneling junctions that consist of a monolayer of photo-switchable aryl-azobenzene molecules of sandwiched between two sheets of graphene. Read More

2017May
Authors: M. Ablikim, M. N. Achasov, X. C. Ai, O. Albayrak, M. Albrecht, D. J. Ambrose, A. Amoroso, F. F. An, Q. An, J. Z. Bai, R. Baldini Ferroli, Y. Ban, D. W. Bennett, J. V. Bennett, M. Bertani, D. Bettoni, J. M. Bian, F. Bianchi, E. Boger, I. Boyko, R. A. Briere, H. Cai, X. Cai, O. Cakir, A. Calcaterra, G. F. Cao, S. A. Cetin, J. F. Chang, G. Chelkov, G. Chen, H. S. Chen, H. Y. Chen, J. C. Chen, M. L. Chen, S. J. Chen, X. Chen, X. R. Chen, Y. B. Chen, H. P. Cheng, X. K. Chu, G. Cibinetto, H. L. Dai, J. P. Dai, A. Dbeyssi, D. Dedovich, Z. Y. Deng, A. Denig, I. Denysenko, M. Destefanis, F. De Mori, Y. Ding, C. Dong, J. Dong, L. Y. Dong, M. Y. Dong, S. X. Du, P. F. Duan, E. E. Eren, J. Z. Fan, J. Fang, S. S. Fang, X. Fang, Y. Fang, L. Fava, F. Feldbauer, G. Felici, C. Q. Feng, E. Fioravanti, M. Fritsch, C. D. Fu, Q. Gao, X. Y. Gao, Y. Gao, Z. Gao, I. Garzia, C. Geng, K. Goetzen, W. X. Gong, W. Gradl, M. Greco, M. H. Gu, Y. T. Gu, Y. H. Guan, A. Q. Guo, L. B. Guo, Y. Guo, Y. P. Guo, Z. Haddadi, A. Hafner, S. Han, Y. L. Han, X. Q. Hao, F. A. Harris, K. L. He, Z. Y. He, T. Held, Y. K. Heng, Z. L. Hou, C. Hu, H. M. Hu, J. F. Hu, T. Hu, Y. Hu, G. M. Huang, G. S. Huang, H. P. Huang, J. S. Huang, X. T. Huang, Y. Huang, T. Hussain, Q. Ji, Q. P. Ji, X. B. Ji, X. L. Ji, L. L. Jiang, L. W. Jiang, X. S. Jiang, X. Y. Jiang, J. B. Jiao, Z. Jiao, D. P. Jin, S. Jin, T. Johansson, A. Julin, N. Kalantar-Nayestanaki, X. L. Kang, X. S. Kang, M. Kavatsyuk, B. C. Ke, P. Kiese, R. Kliemt, B. Kloss, O. B. Kolcu, B. Kopf, M. Kornicer, W. Kuehn, A. Kupsc, J. S. Lange, M. Lara, P. Larin, C. Leng, C. Li, C. H. Li, Cheng Li, D. M. Li, F. Li, G. Li, H. B. Li, J. C. Li, Jin Li, K. Li, K. Li, Lei Li, P. R. Li, T. Li, W. D. Li, W. G. Li, X. L. Li, X. M. Li, X. N. Li, X. Q. Li, Z. B. Li, H. Liang, Y. F. Liang, Y. T. Liang, G. R. Liao, D. X. Lin, B. J. Liu, C. X. Liu, F. H. Liu, Fang Liu, Feng Liu, H. B. Liu, H. H. Liu, H. H. Liu, H. M. Liu, J. Liu, J. B. Liu, J. P. Liu, J. Y. Liu, K. Liu, K. Y. Liu, L. D. Liu, P. L. Liu, Q. Liu, S. B. Liu, X. Liu, X. X. Liu, Y. B. Liu, Z. A. Liu, Zhiqiang Liu, Zhiqing Liu, H. Loehner, X. C. Lou, H. J. Lu, J. G. Lu, R. Q. Lu, Y. Lu, Y. P. Lu, C. L. Luo, M. X. Luo, T. Luo, X. L. Luo, M. Lv, X. R. Lyu, F. C. Ma, H. L. Ma, L. L. Ma, Q. M. Ma, T. Ma, X. N. Ma, X. Y. Ma, F. E. Maas, M. Maggiora, Y. J. Mao, Z. P. Mao, S. Marcello, J. G. Messchendorp, J. Min, T. J. Min, R. E. Mitchell, X. H. Mo, Y. J. Mo, C. Morales Morales, K. Moriya, N. Yu. Muchnoi, H. Muramatsu, Y. Nefedov, F. Nerling, I. B. Nikolaev, Z. Ning, S. Nisar, S. L. Niu, X. Y. Niu, S. L. Olsen, Q. Ouyang, S. Pacetti, P. Patteri, M. Pelizaeus, H. P. Peng, K. Peters, J. Pettersson, J. L. Ping, R. G. Ping, R. Poling, V. Prasad, Y. N. Pu, M. Qi, S. Qian, C. F. Qiao, L. Q. Qin, N. Qin, X. S. Qin, Y. Qin, Z. H. Qin, J. F. Qiu, K. H. Rashid, C. F. Redmer, H. L. Ren, M. Ripka, G. Rong, Ch. Rosner, X. D. Ruan, V. Santoro, A. Sarantsev, M. Savrié, K. Schoenning, S. Schumann, W. Shan, M. Shao, C. P. Shen, P. X. Shen, X. Y. Shen, H. Y. Sheng, W. M. Song, X. Y. Song, S. Sosio, S. Spataro, G. X. Sun, J. F. Sun, S. S. Sun, Y. J. Sun, Y. Z. Sun, Z. J. Sun, Z. T. Sun, C. J. Tang, X. Tang, I. Tapan, E. H. Thorndike, M. Tiemens, M. Ullrich, I. Uman, G. S. Varner, B. Wang, B. L. Wang, D. Wang, D. Y. Wang, K. Wang, L. L. Wang, L. S. Wang, M. Wang, P. Wang, P. L. Wang, S. G. Wang, W. Wang, X. F. Wang, Y. D. Wang, Y. F. Wang, Y. Q. Wang, Z. Wang, Z. G. Wang, Z. H. Wang, Z. Y. Wang, T. Weber, D. H. Wei, J. B. Wei, P. Weidenkaff, S. P. Wen, U. Wiedner, M. Wolke, L. H. Wu, Z. Wu, L. G. Xia, Y. Xia, D. Xiao, H. Xiao, Z. J. Xiao, Y. G. Xie, Q. L. Xiu, G. F. Xu, L. Xu, Q. J. Xu, Q. N. Xu, X. P. Xu, L. Yan, W. B. Yan, W. C. Yan, Y. H. Yan, H. J. Yang, H. X. Yang, L. Yang, Y. Yang, Y. X. Yang, H. Ye, M. Ye, M. H. Ye, J. H. Yin, B. X. Yu, C. X. Yu, H. W. Yu, J. S. Yu, C. Z. Yuan, W. L. Yuan, Y. Yuan, A. Yuncu, A. A. Zafar, A. Zallo, Y. Zeng, B. X. Zhang, B. Y. Zhang, C. Zhang, C. C. Zhang, D. H. Zhang, H. H. Zhang, H. Y. Zhang, J. J. Zhang, J. L. Zhang, J. Q. Zhang, J. W. Zhang, J. Y. Zhang, J. Z. Zhang, K. Zhang, L. Zhang, S. H. Zhang, X. Y. Zhang, Y. Zhang, Y. N. Zhang, Y. H. Zhang, Y. T. Zhang, Yu Zhang, Z. H. Zhang, Z. P. Zhang, Z. Y. Zhang, G. Zhao, J. W. Zhao, J. Y. Zhao, J. Z. Zhao, Lei Zhao, Ling Zhao, M. G. Zhao, Q. Zhao, Q. W. Zhao, S. J. Zhao, T. C. Zhao, Y. B. Zhao, Z. G. Zhao, A. Zhemchugov, B. Zheng, J. P. Zheng, W. J. Zheng, Y. H. Zheng, B. Zhong, L. Zhou, Li Zhou, X. Zhou, X. K. Zhou, X. R. Zhou, X. Y. Zhou, K. Zhu, K. J. Zhu, S. Zhu, X. L. Zhu, Y. C. Zhu, Y. S. Zhu, Z. A. Zhu, J. Zhuang, L. Zotti, B. S. Zou, J. H. Zou

Using a data set of 2.93 fb$^{-1}$ taken at a center-of-mass energy $\sqrt{s}$ = 3.773 GeV with the BESIII detector at the BEPCII collider, we perform a search for an extra U(1) gauge boson, also denoted as a dark photon. Read More

Reducing the number of false positive discoveries is presently one of the most pressing issues in the life sciences. It is of especially great importance for many applications in neuroimaging and genomics, where datasets are typically high-dimensional, which means that the number of explanatory variables exceeds the sample size. The false discovery rate (FDR) is a criterion that can be employed to address that issue. Read More

Recent experimental realizations of superfluid mixtures of Bose and Fermi quantum gases provide a unique platform for exploring diverse superfluid phenomena. We study dipole oscillations of a double superfluid in a cigar-shaped optical dipole trap, consisting of $^{41}$K and $^{6}$Li atoms with a large mass imbalance, where the oscillations of the bosonic and fermionic components are coupled via the Bose-Fermi interaction. In our high-precision measurements, the frequencies of both components are observed to be shifted from the single-species ones, and exhibit unusual features. Read More

A wide bandwidth, dual polarized, modified four-square antenna is presented as a feed antenna for radio astronomical measurements. A linear array of these antennas is used as a line-feed for cylindrical reflectors for Tianlai, a radio interferometer designed for 21~cm intensity mapping. Simulations of the feed antenna beam patterns and scattering parameters are compared to experimental results at multiple frequencies across the 650 - 1420 MHz range. Read More

In this article, we analyze and numerically assess a new fictitious domain method for fluid-structure interactions in two and three dimensions. The distinguishing feature of the proposed method is that it only solves for one velocity field for the whole fluid-structure domain; the interactions remain decoupled until solving the final linear algebraic equations. To achieve this the finite element procedures are carried out separately on two different meshes for the fluid and solid respectively, and the assembly of the final linear system brings the fluid and solid parts together via an isoparametric interpolation matrix between the two meshes. Read More

Many unsupervised kernel methods rely on the estimation of the kernel covariance operator (kernel CO) or kernel cross-covariance operator (kernel CCO). Both kernel CO and kernel CCO are sensitive to contaminated data, even when bounded positive definite kernels are used. To the best of our knowledge, there are few well-founded robust kernel methods for statistical unsupervised learning. Read More