Y. Chi

Y. Chi
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Mathematics - Information Theory (12)
 
Computer Science - Information Theory (12)
 
Statistics - Machine Learning (6)
 
Physics - Accelerator Physics (6)
 
Mathematics - Numerical Analysis (4)
 
High Energy Physics - Phenomenology (3)
 
Quantum Physics (3)
 
Computer Science - Learning (3)
 
Solar and Stellar Astrophysics (2)
 
Mathematics - Statistics (2)
 
Mathematics - Optimization and Control (2)
 
Statistics - Theory (2)
 
Physics - Space Physics (2)
 
Physics - Physics and Society (2)
 
Physics - Superconductivity (1)
 
Computer Science - Artificial Intelligence (1)
 
Statistics - Methodology (1)
 
Computer Science - Databases (1)
 
Computer Science - Computation and Language (1)
 
High Energy Physics - Experiment (1)
 
Physics - Plasma Physics (1)
 
Computer Science - Networking and Internet Architecture (1)

Publications Authored By Y. Chi

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

Keyphrase provides highly-summative information that can be effectively used for understanding, organizing and retrieving text content. Though previous studies have provided many workable solutions for automated keyphrase extraction, they commonly divided the to-be-summarized content into multiple text chunks, then ranked and selected the most meaningful ones. These approaches could neither identify keyphrases that do not appear in the text, nor capture the real semantic meaning behind the text. Read More

In order to ensure the beam quality and meet the requirements introduced by the BEPCII storage ring, the beam energy feedback system has been developed at the exit of the linac. This paper describes the implementation and commissioning of this system in detail. The energy feedback system consists of an energy measurement unit, an application software and an execution unit. 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. Karimian, C. Lingwood, M. D. Buckland, G. Casse, J. Vossebeld, A. Bosco, P. Karataev, K. Kruchinin, K. Lekomtsev, L. Nevay, J. Snuverink, E. Yamakawa, V. Boisvert, S. Boogert, G. Boorman, S. Gibson, A. Lyapin, W. Shields, P. Teixeira-Dias, S. West, R. Jones, N. Joshi, R. Bodenstein, P. N. Burrows, G. B. Christian, D. Gamba, C. Perry, J. Roberts, J. A. Clarke, N. A. Collomb, S. P. Jamison, B. J. A. Shepherd, D. Walsh, M. Demarteau, J. Repond, H. Weerts, L. Xia, J. D. Wells, C. Adolphsen, T. Barklow, M. Breidenbach, N. Graf, J. Hewett, T. Markiewicz, D. McCormick, K. Moffeit, Y. Nosochkov, M. Oriunno, N. Phinney, T. Rizzo, S. Tantawi, F. Wang, J. Wang, G. White, M. Woodley

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

Magnetic flux ropes (MFRs) are one kind of fundamental structures in the solar physics, and involved in various eruption phenomena. Twist, characterizing how the magnetic field lines wind around a main axis, is an intrinsic property of MFRs, closely related to the magnetic free energy and stableness. So far it is unclear how much amount of twist is carried by MFRs in the solar atmosphere and in heliosphere and what role the twist played in the eruptions of MFRs. Read More

Four kinds of waveguide power dividers with different structures working at 2.856 GHz are developed. By comparing the simulation performances of these four structures, the power divider with matching rod in the middle of its structure has got the best performance and finally be chosen for fabrication. Read More

We study the phase retrieval problem, which solves quadratic system of equations, i.e., recovers a vector $\boldsymbol{x}\in \mathbb{R}^n$ from its magnitude measurements $y_i=|\langle \boldsymbol{a}_i, \boldsymbol{x}\rangle|, i=1,. Read More

This paper investigates the phase retrieval problem, which aims to recover a signal from the magnitudes of its linear measurements. We develop statistically and computationally efficient algorithms for the situation when the measurements are corrupted by sparse outliers that can take arbitrary values. We propose a novel approach to robustify the gradient descent algorithm by using the sample median as a guide for pruning spurious samples in initialization and local search. Read More

We study the problem of estimating a low-rank positive semidefinite (PSD) matrix from a set of rank-one measurements using sensing vectors composed of i.i.d. Read More

Recent studies show that graph processing systems on a single machine can achieve competitive performance compared with cluster-based graph processing systems. In this paper, we present NXgraph, an efficient graph processing system on a single machine. With the abstraction of vertex intervals and edge sub-shards, we propose the Destination-Sorted Sub-Shard (DSSS) structure to store a graph. Read More

This paper describes beam energy online measurement of BEPCII linac, presents the calculation formula and some of the results. The method mentioned here measures the beam energy by acquiring beam positions in the horizontal direction with three beam position monitors (BPM) eliminating the effect of orbit fluctuation, which is much better than the one using the single BPM. The error analysis indicates that this online measurement has further potential usage such as a part of beam energy feedback system. Read More

We consider simultaneously identifying the membership and locations of point sources that are convolved with different band-limited point spread functions, from the observation of their superpositions. This problem arises in three-dimensional super-resolution single-molecule imaging, neural spike sorting, multi-user channel identification, among other applications. We propose a novel algorithm, based on convex programming, and establish its near-optimal performance guarantee for exact recovery in the noise-free setting by exploiting the spectral sparsity of the point source models as well as the incoherence between point spread functions. Read More

Neural recordings, returns from radars and sonars, images in astronomy and single-molecule microscopy can be modeled as a linear superposition of a small number of scaled and delayed copies of a band-limited or diffraction-limited point spread function, which is either determined by the nature or designed by the users; in other words, we observe the convolution between a point spread function and a sparse spike signal with unknown amplitudes and delays. While it is of great interest to accurately resolve the spike signal from as few samples as possible, however, when the point spread function is not known a priori, this problem is terribly ill-posed. This paper proposes a convex optimization framework to simultaneously estimate the point spread function as well as the spike signal, by mildly constraining the point spread function to lie in a known low-dimensional subspace. Read More

In this work, we establish an ICME list from 1996 to 2014 based on the in-situ observations from the WIND and ACE satellites. Based on this ICME list, we extend the statistical analysis of the ICMEs to the solar maximum phase of solar cycle 24th. The analysis of the annual variations of the properties of ICMEs show that the number of ICMEs, the number of shocks, the percentage of ICMEs drove shocks, the magnetic field and plasma properties of ICMEs are well correlated with the solar cycle variation. Read More

We consider simultaneously identifying the membership and locations of point sources that are convolved with different low-pass point spread functions, from the observation of their superpositions. This problem arises in three-dimensional super-resolution single-molecule imaging, neural spike sorting, multi-user channel identification, among others. We propose a novel algorithm, based on convex programming, and establish its near-optimal performance guarantee for exact recovery by exploiting the sparsity of the point source model as well as incoherence between the point spread functions. Read More

The difference between the $\Lambda$ and $\bar \Lambda$ longitudinal spin transfers in the semi-inclusive deep inelastic scattering process is intensively studied. The study is performed in the current fragmentation region, by considering the intermediate hyperon decay processes and sea quark fragmentation processes, while the strange sea $s\bar s$ asymmetry in the nucleon is taken into account. The calculation in the light-cone quark-diquark model shows that the strange sea asymmetry gives a proper trend to the difference between the $\Lambda$ and $\bar \Lambda$ longitudinal spin transfers. Read More

The congestion control algorithms in TCP may incur inferior performance in a lossy network context like wireless networks. Previous works have shown that random linear network coding can improve the throughput of TCP in such networks, although it introduces extra decoding delay at the destination. In this paper we try to alleviate the decoding delay by replacing random linear network coding with LT Codes. Read More

Compressed Sensing suggests that the required number of samples for reconstructing a signal can be greatly reduced if it is sparse in a known discrete basis, yet many real-world signals are sparse in a continuous dictionary. One example is the spectrally-sparse signal, which is composed of a small number of spectral atoms with arbitrary frequencies on the unit interval. In this paper we study the problem of line spectrum denoising and estimation with an ensemble of spectrally-sparse signals composed of the same set of continuous-valued frequencies from their partial and noisy observations. Read More

Networked sensing, where the goal is to perform complex inference using a large number of inexpensive and decentralized sensors, has become an increasingly attractive research topic due to its applications in wireless sensor networks and internet-of-things. To reduce the communication, sensing and storage complexity, this paper proposes a simple sensing and estimation framework to faithfully recover the principal subspace of high-dimensional data streams using a collection of binary measurements from distributed sensors, without transmitting the whole data. The binary measurements are designed to indicate comparison outcomes of aggregated energy projections of the data samples over pairs of randomly selected directions. Read More

Compressed Sensing (CS) is an effective approach to reduce the required number of samples for reconstructing a sparse signal in an a priori basis, but may suffer severely from the issue of basis mismatch. In this paper we study the problem of simultaneously recovering multiple spectrally-sparse signals that are supported on the same frequencies lying arbitrarily on the unit circle. We propose an atomic norm minimization problem, which can be regarded as a continuous counterpart of the discrete CS formulation and be solved efficiently via semidefinite programming. Read More

We perform a study on the struck quark to the $\Lambda$-hyperon fragmentation processes by taking into account the anti-quark fragmentations and intermediate decays from other hyperons. We concentrate on how the longitudinally polarized quark fragments to the longitudinally polarized $\Lambda$, how unpolarized quark and anti-quark fragment to the unpolarized $\Lambda$, and how quark and anti-quark fragment to the $\Lambda$ through the intermediate decay processes. We calculate the effective fragmentation functions in the light-cone SU(6) quark-spectator-diquark model via the Gribov-Lipatov relation, with the Melosh-Wigner rotation effect also included. Read More

In NSC KIPT linac, a neutron source based on a subcritical assembly driven by a 100MeV/100kW electron linear accelerator is under design and development. The linear accelerator needs a new high current electron gun. In this paper, the physical design, mechanical fabrication and beam test of this new electron gun are described. Read More

Statistical inference and information processing of high-dimensional data often require efficient and accurate estimation of their second-order statistics. With rapidly changing data, limited processing power and storage at the acquisition devices, it is desirable to extract the covariance structure from a single pass over the data and a small number of stored measurements. In this paper, we explore a quadratic (or rank-one) measurement model which imposes minimal memory requirements and low computational complexity during the sampling process, and is shown to be optimal in preserving various low-dimensional covariance structures. Read More

The paper explores the problem of \emph{spectral compressed sensing}, which aims to recover a spectrally sparse signal from a small random subset of its $n$ time domain samples. The signal of interest is assumed to be a superposition of $r$ multi-dimensional complex sinusoids, while the underlying frequencies can assume any \emph{continuous} values in the normalized frequency domain. Conventional compressed sensing paradigms suffer from the basis mismatch issue when imposing a discrete dictionary on the Fourier representation. Read More

The paper studies the problem of recovering a spectrally sparse object from a small number of time domain samples. Specifically, the object of interest with ambient dimension $n$ is assumed to be a mixture of $r$ complex multi-dimensional sinusoids, while the underlying frequencies can assume any value in the unit disk. Conventional compressed sensing paradigms suffer from the {\em basis mismatch} issue when imposing a discrete dictionary on the Fourier representation. Read More

Multi-User Detection is fundamental not only to cellular wireless communication but also to Radio-Frequency Identification (RFID) technology that supports supply chain management. The challenge of Multi-user Detection (MUD) is that of demodulating mutually interfering signals, and the two biggest impediments are the asynchronous character of random access and the lack of channel state information. Given that at any time instant the number of active users is typically small, the promise of Compressive Sensing (CS) is the demodulation of sparse superpositions of signature waveforms from very few measurements. Read More

In this paper we analyze influence in the blogosphere. Recently, influence analysis has become an increasingly important research topic, as online communities, such as social networks and e-commerce sites, playing a more and more significant role in our daily life. However, so far few studies have succeeded in extracting influence from online communities in a satisfactory way. Read More

In this paper, we present coherence-based performance guarantees of Orthogonal Matching Pursuit (OMP) for both support recovery and signal reconstruction of sparse signals when the measurements are corrupted by noise. In particular, two variants of OMP either with known sparsity level or with a stopping rule are analyzed. It is shown that if the measurement matrix $X\in\mathbb{C}^{n\times p}$ satisfies the strong coherence property, then with $n\gtrsim\mathcal{O}(k\log p)$, OMP will recover a $k$-sparse signal with high probability. Read More

Many real world data sets exhibit an embedding of low-dimensional structure in a high-dimensional manifold. Examples include images, videos and internet traffic data. It is of great significance to reduce the storage requirements and computational complexity when the data dimension is high. Read More

This paper addresses the problem of community detection in networked data that combines link and content analysis. Most existing work combines link and content information by a generative model. There are two major shortcomings with the existing approaches. Read More

In principle a quantum system could be used to simulate another quantum system. The purpose of such a simulation would be to obtain information about problems which cannot be simulated with a classical computer due to the exponential increase of the Hilbert space with the size of the system and which cannot be measured or controlled in an actual experiment. The system will interact with the surrounding environment, with the other particles in the system and be implemented using imperfect controls making it subject to noise. Read More

With the parametrization of parton distribution functions (PDFs) of the proton by Soffer \textit{et al.}, we extend the valence quark contents to other octet baryons by utilizing SU(3) flavor symmetry. We find the method practically useful. Read More

We discuss excess noise contributions of a practical balanced homodyne detector in Gaussian-modulated coherent-state (GMCS) quantum key distribution (QKD). We point out the key generated from the original realistic model of GMCS QKD may not be secure. In our refined realistic model, we take into account excess noise due to the finite bandwidth of the homodyne detector and the fluctuation of the local oscillator. Read More

We present a high speed random number generation scheme based on measuring the quantum phase noise of a single mode diode laser operating at a low intensity level near the lasing threshold. A delayed self-heterodyning system has been developed to measure the random phase fluctuation.By actively stabilizing the phase of the fiber interferometer, a random number generation rate of 500Mbit/s has been demonstrated and the generated random numbers have passed all the DIEHARD tests. Read More

We have grown MgB2 films in a postannealing process. Precursors were prepared on Al2O3(0001) substrates by codeposition of Mg and MgB2 using pulsed laser deposition technique. Superconducting MgB2 thin films were obtained via an ex situ postannealing process, with various annealing temperatures and durations. Read More