Y. B. Chen - Senior Member, IEEE

Y. B. Chen
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Y. B. Chen
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Senior Member, IEEE
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Computer Science - Learning (9)
 
Statistics - Machine Learning (4)
 
Computer Science - Computation and Language (4)
 
Physics - Materials Science (4)
 
Computer Science - Neural and Evolutionary Computing (4)
 
Computer Science - Computer Vision and Pattern Recognition (4)
 
Earth and Planetary Astrophysics (3)
 
Physics - Strongly Correlated Electrons (3)
 
Computer Science - Distributed; Parallel; and Cluster Computing (3)
 
Physics - Chemical Physics (3)
 
Physics - Superconductivity (3)
 
Quantum Physics (3)
 
High Energy Physics - Experiment (3)
 
Physics - Instrumentation and Detectors (2)
 
Physics - Computational Physics (2)
 
Solar and Stellar Astrophysics (2)
 
Physics - Other (2)
 
Computer Science - Information Theory (2)
 
Mathematics - Information Theory (2)
 
Physics - Optics (2)
 
High Energy Physics - Theory (2)
 
Mathematics - Mathematical Physics (1)
 
Computer Science - Networking and Internet Architecture (1)
 
Mathematical Physics (1)
 
Computer Science - Sound (1)
 
Computer Science - Computer Science and Game Theory (1)
 
Mathematics - Combinatorics (1)
 
Statistics - Theory (1)
 
Physics - Biological Physics (1)
 
Statistics - Methodology (1)
 
Computer Science - Computers and Society (1)
 
Mathematics - Statistics (1)
 
Mathematics - Rings and Algebras (1)
 
Computer Science - Cryptography and Security (1)
 
Computer Science - Computational Complexity (1)
 
Statistics - Applications (1)
 
Physics - Accelerator Physics (1)

Publications Authored By Y. B. Chen

Beam commissioning of the SuperKEKB collider began in 2016. The Beam Exorcism for A STable experiment II (BEAST II) project is particularly designed to measure the beam backgrounds around the interaction point of the SuperKEKB collider for the Belle II experiment. We develop a system using bismuth germanium oxide (BGO) crystals with optical fibers connecting to a multianode photomultiplier tube (MAPMT) and a field-programmable gate array embedded data acquisition board for monitoring the real-time beam backgrounds in BEAST II. Read More

The cold classical Kuiper belt objects have low inclinations and eccentricities and are the only Kuiper belt population suspected to have formed in situ. Compared with the dynamically excited populations, which exhibit a broad range of colours and a low binary fraction of ~10% cold classical Kuiper belt objects typically have red optical colours with ~30% of the population found in binary pairs; the origin of these differences remains unclear. We report the detection of a population of blue-coloured, tenuously bound binaries residing among the cold classical Kuiper belt objects. Read More

In this paper, we address a major challenge confronting the Cloud Service Providers (CSPs) utilizing a tiered storage architecture - how to maximize their overall profit over a variety of storage tiers that offer distinct characteristics, as well as file placement and access request scheduling policies. Read More

We report a method for constructing bandpass functions that approximate a given analytic function with arbitrary accuracy over a finite interval. A corollary is that bandpass functions can be obtained that oscillate arbitrarily slower than their minimum frequency component, a counter-intuitive phenomenon known as suboscillations. Read More

Deep neural models, particularly the LSTM-RNN model, have shown great potential in language identification (LID). However, the phonetic information has been largely overlooked by most of existing neural LID methods, although this information has been used in the conventional phonetic LID systems with a great success. We present a phonetic temporal neural model for LID, which is an LSTM-RNN LID system but accepts phonetic features produced by a phone-discriminative DNN as the input, rather than raw acoustic features. Read More

Both impurity- and magnetic-field-induced quasiparticle states in chiral $p$-wave superconductors are investigated theoretically by solving the Bogoliubov--de Gennes equations self-consistently. At the strong scattering limit, we find that a universal state bound to the impurity can be induced for both a single nonmagnetic impurity and a single magnetic impurity. Furthermore, we find that different chiral order parameters and the corresponding supercurrents have uniform distributions around linear impurities. Read More

The Sachdev-Ye-Kitaev (SYK) model is a concrete solvable model to study non-Fermi liquid properties, holographic duality and maximally chaotic behavior. In this work, we consider a generalization of the SYK model that contains two SYK models with different number of Majorana modes coupled by quadratic terms. This model is also solvable, and the solution shows a zero-temperature quantum phase transition between two non-Fermi liquid chaotic phases. Read More

Hydrogen-rich compounds are important for understanding the dissociation of dense molecular hydrogen, as well as searching for room temperature Bardeen-Cooper-Schrieffer (BCS) superconductors. A recent high pressure experiment reported the successful synthesis of novel insulating lithium polyhydrides when above 130 GPa. However, the results are in sharp contrast to previous theoretical prediction by PBE functional that around this pressure range all lithium polyhydrides (LiHn (n = 2-8)) should be metallic. Read More

Data stewards seeking to provide access to large-scale social science data face a difficult challenge. They have to share data in ways that protect privacy and confidentiality, are informative for many analyses and purposes, and are relatively straightforward to use by data analysts. We present a framework for addressing this challenge. 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

In this paper we consider the cluster estimation problem under the Stochastic Block Model. We show that the semidefinite programming (SDP) formulation for this problem achieves an error rate that decays exponentially in the signal-to-noise ratio. The error bound implies weak recovery in the sparse graph regime with bounded expected degrees, as well as exact recovery in the dense regime. Read More

We present a general approach to speed up the adiabatic process without adding the traditional counterdiabatic driving (CD) Hamiltonian. The strategy is to design an easy-to-get intermediate Hamiltonian to connect the original Hamiltonian and final transitionless Hamiltonian. With final transitionless Hamiltonian, the same target can be achieved as in the adiabatic process governed by the original Hamiltonian, but in a shorter time. 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

Microscopic Imaging Ellipsometry is an optical technique that uses an objective and sensing procedure to measure the ellipsometric parameters {\Psi} and {\Delta} in the form of microscopic maps. This technique is well known for being non-invasive and label-free. Therefore it can be used to detect and characterize biological species without any impact. Read More

Many data producers seek to provide users access to confidential data without unduly compromising data subjects' privacy and confidentiality. When intense redaction is needed to do so, one general strategy is to require users to do analyses without seeing the confidential data, for example, by releasing fully synthetic data or by allowing users to query remote systems for disclosure-protected outputs of statistical models. With fully synthetic data or redacted outputs, the analyst never really knows how much to trust the resulting findings. Read More

OBJECTIVE: To test the hypothesis that variation in care coordination is related to LOS. DESIGN We applied a spectral co-clustering methodology to simultaneously infer groups of patients and care coordination patterns, in the form of interaction networks of health care professionals, from electronic medical record (EMR) utilization data. The care coordination pattern for each patient group was represented by standard social network characteristics and its relationship with hospital LOS was assessed via a negative binomial regression with a 95% confidence interval. 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

Some recent works revealed that deep neural networks (DNNs) are vulnerable to so-called adversarial attacks where input examples are intentionally perturbed to fool DNNs. In this work, we revisit the DNN training process that includes adversarial examples into the training dataset so as to improve DNN's resilience to adversarial attacks, namely, adversarial training. Our experiments show that different adversarial strengths, i. Read More

The Sachdev-Ye-Kitaev (SYK) model describes Majorana fermions with random interaction, which displays many interesting properties such as non-Fermi liquid behavior, quantum chaos, emergent conformal symmetry and holographic duality. Here we consider a SYK model or a chain of SYK models with $N$ Majorana fermion modes coupled to another SYK model with $N^2$ Majorana fermion modes, in which the latter has many more degrees of freedom and plays the role as a thermal bath. For a single SYK model coupled to the thermal bath, we show that although the Lyapunov exponent is still proportional to temperature, it monotonically decreases from $2\pi/\beta$ ($\beta=1/(k_BT)$, $T$ is temperature) to zero as the coupling strength to the thermal bath increases. Read More

While it is well established that ionic conduction in lithium aluminosilicates proceeds via hopping of Li ions, the nature of the various hoping-based mechanisms in different temperature regimes has not been fully elucidated. The difficulties associated with investigating the conduction have to do with the presence of grains and grain boundaries of different orientations in the these materials, which are usually polycrystalline materials. Herein, we investigate the ion conduction mechanisms in -eucryptite, a prototypical lithium aluminosilicate, using impedance spectroscopy. Read More

Recently, superconductivity in potassium (K) doped p-terphenyl (C18H14) has been suggested by the possible observation of the Meissner effect and subsequent photoemission spectroscopy measurements, but the detailed lattice structure and more-direct evidence are still lacking. Here we report a low temperature scanning tunneling microscopy/spectroscopy (STM/STS) study on K-doped single layer p-terphenyl films grown on Au (111). We observe several ordered phases with different morphologies and electronic behaviors, in two of which a sharp and symmetric low-energy gap of about 11 meV opens below 50 K. Read More

This work targets person re-identification (ReID) from depth sensors such as Kinect. Since depth is invariant to illumination and less sensitive than color to day-by-day appearance changes, a natural question is whether depth is an effective modality for Person ReID, especially in scenarios where individuals wear different colored clothes or over a period of several months. We explore the use of recurrent Deep Neural Networks for learning high-level shape information from low-resolution depth images. Read More

The capacity of a fractal wireless network with direct social interactions is studied in this paper. Specifically, we mathematically formulate the self-similarity of a fractal wireless network by a power-law degree distribution $ P(k) $, and we capture the connection feature between two nodes with degree $ k_{1} $ and $ k_{2} $ by a joint probability distribution $ P(k_{1},k_{2}) $. It is proved that if the source node communicates with one of its direct contacts randomly, the maximum capacity is consistent with the classical result $ \Theta\left(\frac{1}{\sqrt{n\log n}}\right) $ achieved by Kumar \cite{Gupta2000The}. Read More

We study the existence of the maximal quantum Fisher information matrix in multi-parameter quantum estimation, which bounds the ultimate precision limit. We show that when the maximal quantum Fisher information matrix exists, it can be directly obtained from the underlying dynamics. Examples are then provided to demonstrate the usefulness of the maximal quantum Fisher information matrix by deriving various tradeoff relations in multi-parameter quantum estimation and obtaining the bounds for the scalings of the precision limit. Read More

The key idea of current deep learning methods for dense prediction is to apply a model on a regular patch centered on each pixel to make pixel-wise predictions. These methods are limited in the sense that the patches are determined by network architecture instead of learned from data. In this work, we propose the dense transformer networks, which can learn the shapes and sizes of patches from data. Read More

In this paper, a scheme is put forward to design pulses which drive a three-level system based on the reverse engineering with Lewis-Riesenfeld invariant theory. The scheme can be applied to a three-level system even when the rotating-wave approximation (RWA) can not be used. The amplitudes of pulses and the maximal values of detunings in the system could be easily controlled by adjusting control parameters. Read More

By applying a Gr\"{o}bner-Shirshov basis of the symmetric group $S_{n}$, we give two formulas for Schubert polynomials, either of which involves only nonnegative monomials. We also prove some combinatorial properties of Schubert polynomials. As applications, we give two algorithms to calculate the structure constants for Schubert polynomials, one of which depends on Monk's formula. 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

We study the computational complexity of the infinite-horizon discounted-reward Markov Decision Problem (MDP) with a finite state space $|\mathcal{S}|$ and a finite action space $|\mathcal{A}|$. We show that any randomized algorithm needs a running time at least $\Omega(|\mathcal{S}|^2|\mathcal{A}|)$ to compute an $\epsilon$-optimal policy with high probability. We consider two variants of the MDP where the input is given in specific data structures, including arrays of cumulative probabilities and binary trees of transition probabilities. 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

The application of high pressure can fundamentally modify the crystalline and electronic structures of elements as well as their chemical reactivity, which could lead to the formation of novel materials. Here, we explore the reactivity of lithium with sodium under high pressure, using a swarm structure searching techniques combined with first-principles calculations, which identify a thermodynamically stable LiNa compound adopting an orthorhombic oP8 phase at pressure above 355 GPa. The formation of LiNa may be a consequence of strong concentration of electrons transfer from the lithium and the sodium atoms into the interstitial sites, which also leads to opening a relatively wide band gap for LiNa-op8. Read More

Double coronal hard X-ray (HXR) sources are believed to be critical observational evidence of bi-directional energy release through magnetic reconnection in a large-scale current sheet in solar ares. Here we present a study on double coronal sources observed in both HXR and microwave regimes, revealing new characteristics distinct from earlier reports. This event is associated with a footpoint-occulted X1. Read More

The 10 MeV accelerator-driven subcritical system (ADS) Injector-I test stand at Institute of High Energy Physics (IHEP) is a testing facility dedicated to demonstrate one of the two injector design schemes [Injector Scheme-I, which works at 325 MHz], for the ADS project in China. The Injector adopted a four vane copper structure RFQ with output energy of 3.2 MeV and a superconducting (SC) section accommodating fourteen \b{eta}g=0. Read More

We consider the problem of distributed statistical machine learning in adversarial settings, where some unknown and time-varying subset of working machines may be compromised and behave arbitrarily to prevent an accurate model from being learned. This setting captures the potential adversarial attacks faced by Federated Learning -- a modern machine learning paradigm that is proposed by Google researchers and has been intensively studied for ensuring user privacy. Formally, we focus on a distributed system consisting of a parameter server and $m$ working machines. Read More

Generalized expressions for second harmonic scattering from isotropically distributed liquid molecules are derived for arbitrary scattering angles and polarization states. 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

In this paper, we show that an order $m$ dimension 2 tensor is primitive if and only if its majorization matrix is primitive, and then we obtain the characterization of order $m$ dimension 2 strongly primitive tensors and the bound of the strongly primitive degree. Furthermore, we study the properties of strongly primitive tensors with $n\geq 3$, and propose some problems for further research. 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

Recently deep neural networks (DNNs) have been used to learn speaker features. However, the quality of the learned features is not sufficiently good, so a complex back-end model, either neural or probabilistic, has to be used to address the residual uncertainty when applied to speaker verification, just as with raw features. This paper presents a convolutional time-delay deep neural network structure (CT-DNN) for speaker feature learning. Read More

One of the remaining obstacles to approaching the theoretical efficiency limit of crystalline silicon (c-Si) solar cells is the exceedingly high interface recombination loss for minority carriers at the Ohmic contacts. In ultra-thin-film c-Si solar cells, this contact recombination loss is far more severe than for traditional thick cells due to the smaller volume and higher minority carrier concentration of the former. This paper presents a novel design of an electron passing (Ohmic) contact to n-type Si that is hole-blocking with significantly reduced hole recombination. Read More

Pure acoustic neural models, particularly the LSTM-RNN model, have shown great potential in language identification (LID). However, the phonetic information has been largely overlooked by most of existing neural LID models, although this information has been used in the conventional phonetic LID systems with a great success. We present a phone-aware neural LID architecture, which is a deep LSTM-RNN LID system but accepts output from an RNN-based ASR system. Read More

2017May
Affiliations: 1Department of Applied Physics, Stanford University, 2Department of Applied Physics, Stanford University, 3Department of Applied Physics, Stanford University, 4Department of Applied Physics, Stanford University, 5Institute of Applied Physics, TU Dresden, 6Institute of Applied Physics, TU Dresden, 7National Laboratory of Solid State Microstructures and Department of Materials Science and Engineering, Nanjing University, 8National Laboratory of Solid State Microstructures and Department of Materials Science and Engineering, Nanjing University, 9National Laboratory of Solid State Microstructures and Department of Materials Science and Engineering, Nanjing University, 10Department of Applied Physics, Stanford University

Surface Acoustic Wave (SAW) resonances were imaged within a closed domain in the ferroelectric LiTaO$_3$ via scanning Microwave Impedance Microscopy (MIM). The MIM probe is used for both SAW generation and measurement, allowing contact-less measurement within a mesoscopic structure. Measurements taken over a range of microwave frequencies are consistent with a constant acoustic velocity, demonstrating the acoustic nature of the measurement. Read More

We report an investigation of the superconducting states of $\mathrm{Lu}_3\mathrm{Os}_4\mathrm{Ge}_{13}$ and $\mathrm{Y}_3\mathrm{Ru}_4\mathrm{Ge}_{13}$ single crystals by measurements of the electrical resistivity, ac susceptibility and London penetration depth. The analysis of the penetration depth and the derived superfluid density indicates the presence of nodeless superconductivity and suggest that there are multiple superconducting gaps in both materials. Furthermore, ac susceptibility measurements of both compounds display the peak effect in the low temperature region of the $H-T$ phase diagram. Read More

The Hyper Suprime-Cam Subaru Strategic Program (HSC-SSP) is currently the deepest wide- field survey in progress. The 8.2 m aperture of Subaru telescope is very powerful in detect- ing faint/small moving objects, including near-Earth objects, asteroids, centaurs and Tran- Neptunian objects (TNOs). Read More

Autoencoders have been successful in learning meaningful representations from image datasets. However, their performance on text datasets has not been widely studied. Traditional autoencoders tend to learn possibly trivial representations of text documents due to their confounding properties such as high-dimensionality, sparsity and power-law word distributions. Read More

This paper proposes two spoof surface plasmon polariton (SSPP) leaky-wave antennas using periodically loaded patches above perfect electric conductor (PEC) and artificial magnetic conductor (AMC) ground planes, respectively. The SSPP leaky-wave antenna is based on a SSPP transmission line, along which circular patches are periodically loaded on both sides to provide an additional momentum for phase matching with the radiated waves in the air. The PEC and AMC ground planes underneath the antenna reflect the radiated waves into the upward space, leading to an enhanced radiation gain. Read More

While end-to-end neural machine translation (NMT) has made remarkable progress recently, it still suffers from the data scarcity problem for low-resource language pairs and domains. In this paper, we propose a method for zero-resource NMT by assuming that parallel sentences have close probabilities of generating a sentence in a third language. Based on this assumption, our method is able to train a source-to-target NMT model ("student") without parallel corpora available, guided by an existing pivot-to-target NMT model ("teacher") on a source-pivot parallel corpus. Read More

For human pose estimation in monocular images, joint occlusions and overlapping upon human bodies often result in deviated pose predictions. Under these circumstances, biologically implausible pose predictions may be produced. In contrast, human vision is able to predict poses by exploiting geometric constraints of joint inter-connectivity. Read More

Optical refrigeration of solids holds tremendous promise for applications in thermal management. It can be achieved through multiple mechanisms including inelastic anti-Stokes Brillouin and Raman scattering. However, engineering of these mechanisms remains relatively unexplored. Read More