T. Yang - MicroBooNE Collaboration

T. Yang
Are you T. Yang?

Claim your profile, edit publications, add additional information:

Contact Details

Name
T. Yang
Affiliation
MicroBooNE Collaboration
Location

Pubs By Year

Pub Categories

 
High Energy Physics - Experiment (8)
 
Physics - Instrumentation and Detectors (6)
 
Computer Science - Learning (6)
 
Mathematics - Optimization and Control (5)
 
Mathematics - Analysis of PDEs (5)
 
Statistics - Machine Learning (4)
 
High Energy Physics - Theory (3)
 
Mathematical Physics (3)
 
Mathematics - Mathematical Physics (3)
 
General Relativity and Quantum Cosmology (3)
 
Mathematics - Number Theory (3)
 
Cosmology and Nongalactic Astrophysics (3)
 
Computer Science - Information Theory (2)
 
Mathematics - Quantum Algebra (2)
 
Mathematics - Probability (2)
 
Physics - Optics (2)
 
Physics - Statistical Mechanics (2)
 
High Energy Physics - Phenomenology (2)
 
Mathematics - Information Theory (2)
 
Computer Science - Computer Vision and Pattern Recognition (2)
 
Computer Science - Distributed; Parallel; and Cluster Computing (1)
 
Astrophysics of Galaxies (1)
 
Quantum Physics (1)
 
Mathematics - Rings and Algebras (1)
 
Physics - Biological Physics (1)
 
High Energy Astrophysical Phenomena (1)
 
Statistics - Computation (1)
 
Physics - Materials Science (1)
 
Mathematics - Algebraic Geometry (1)
 
Mathematics - Geometric Topology (1)
 
Computer Science - Multimedia (1)
 
Computer Science - Data Structures and Algorithms (1)
 
Mathematics - Differential Geometry (1)
 
Solar and Stellar Astrophysics (1)

Publications Authored By T. Yang

2017May
Authors: MicroBooNE collaboration, R. Acciarri, C. Adams, R. An, J. Anthony, J. Asaadi, M. Auger, L. Bagby, S. Balasubramanian, B. Baller, C. Barnes, G. Barr, M. Bass, F. Bay, M. Bishai, A. Blake, T. Bolton, B. Bullard, L. Camilleri, D. Caratelli, B. Carls, R. Castillo Fernandez, F. Cavanna, H. Chen, E. Church, D. Cianci, E. Cohen, G. H. Collin, J. M. Conrad, M. Convery, J. I. Crespo-Anadon, G. De Geronimo, M. Del Tutto, D. Devitt, S. Dytman, B. Eberly, A. Ereditato, L. Escudero Sanchez, J. Esquivel, A. A. Fadeeva, B. T. Fleming, W. Foreman, A. P. Furmanski, D. Garcia-Gamez, G. T. Garvey, V. Genty, D. Goeldi, S. Gollapinni, N. Graf, E. Gramellini, H. Greenlee, R. Grosso, R. Guenette, A. Hackenburg, P. Hamilton, O. Hen, J. Hewes, C. Hill, J. Ho, G. Horton-Smith, A. Hourlier, E. -C. Huang, C. James, J. Jan de Vries, C. -M. Jen, L. Jiang, R. A. Johnson, J. Joshi, H. Jostlein, D. Kaleko, G. Karagiorgi, W. Ketchum, B. Kirby, M. Kirby, T. Kobilarcik, I. Kreslo, A. Laube, S. Li, Y. Li, A. Lister, B. R. Littlejohn, S. Lockwitz, D. Lorca, W. C. Louis, M. Luethi, B. Lundberg, X. Luo, A. Marchionni, C. Mariani, J. Marshall, D. A. Martinez Caicedo, V. Meddage, T. Miceli, G. B. Mills, J. Moon, M. Mooney, C. D. Moore, J. Mousseau, R. Murrells, D. Naples, P. Nienaber, J. Nowak, O. Palamara, V. Paolone, V. Papavassiliou, S. F. Pate, Z. Pavlovic, E. Piasetzky, D. Porzio, G. Pulliam, X. Qian, J. L. Raaf, V. Radeka, A. Rafique, S. Rescia, L. Rochester, C. Rudolf von Rohr, B. Russell, D. W. Schmitz, A. Schukraft, W. Seligman, M. H. Shaevitz, J. Sinclair, A. Smith, E. L. Snider, M. Soderberg, S. Soldner-Rembold, S. R. Soleti, P. Spentzouris, J. Spitz, J. St. John, T. Strauss, A. M. Szelc, N. Tagg, K. Terao, M. Thomson, C. Thorn, M. Toups, Y. -T. Tsai, S. Tufanli, T. Usher, W. Van De Pontseele, R. G. Van de Water, B. Viren, M. Weber, D. A. Wickremasinghe, S. Wolbers, T. Wongjirad, K. Woodruff, T. Yang, L. Yates, B. Yu, G. P. Zeller, J. Zennamo, C. Zhang

The low-noise operation of readout electronics in a liquid argon time projection chamber (LArTPC) is critical to properly extract the distribution of ionization charge deposited on the wire planes of the TPC, especially for the induction planes. This paper describes the characteristics and mitigation of the observed noise in the MicroBooNE detector. The MicroBooNE's single-phase LArTPC comprises two induction planes and one collection sense wire plane with a total of 8256 wires. Read More

The lasso model has been widely used for model selection in data mining, machine learning, and high-dimensional statistical analysis. However, due to the ultrahigh-dimensional, large-scale data sets collected in many real-world applications, it remains challenging to solve the lasso problems even with state-of-the-art algorithms. Feature screening is a powerful technique for addressing the Big Data challenge by discarding inactive features from the lasso optimization. Read More

The panoramic video is widely used to build virtual reality (VR) and is expected to be one of the next generation Killer-Apps. Transmitting panoramic VR videos is a challenging task because of two problems: 1) panoramic VR videos are typically much larger than normal videos but they need to be transmitted with limited bandwidth in mobile networks. 2) high-resolution and fluent views should be provided to guarantee a superior user experience and avoid side-effects such as dizziness and nausea. Read More

We consider the global consensus problem for multi-agent systems with input saturation over digraphs. Under a mild connectivity condition that the underlying digraph has a directed spanning tree, we use Lyapunov methods to show that the widely used distributed consensus protocol, which solves the consensus problem for the case without input saturation constraints, also solves the global consensus problem for the case with input saturation constraints. In order to reduce the overall need of communication and system updates, we then propose a distributed event-triggered control law. Read More

2017Apr
Authors: MicroBooNE collaboration, R. Acciarri, C. Adams, R. An, J. Anthony, J. Asaadi, M. Auger, L. Bagby, S. Balasubramanian, B. Baller, C. Barnes, G. Barr, M. Bass, F. Bay, M. Bishai, A. Blake, T. Bolton, L. Bugel, L. Camilleri, D. Caratelli, B. Carls, R. Castillo Fernandez, F. Cavanna, H. Chen, E. Church, D. Cianci, E. Cohen, G. H. Collin, J. M. Conrad, M. Convery, J. I. Crespo-Anadon, M. Del Tutto, D. Devitt, S. Dytman, B. Eberly, A. Ereditato, L. Escudero Sanchez, J. Esquivel, B. T. Fleming, W. Foreman, A. P. Furmanski, D. Garcia-Gamez, G. T. Garvey, V. Genty, D. Goeldi, S. Gollapinni, N. Graf, E. Gramellini, H. Greenlee, R. Grosso, R. Guenette, A. Hackenburg, P. Hamilton, O. Hen, J. Hewes, C. Hill, J. Ho, G. Horton-Smith, E. -C. Huang, C. James, J. Jan de Vries, C. -M. Jen, L. Jiang, R. A. Johnson, J. Joshi, H. Jostlein, D. Kaleko, G. Karagiorgi, W. Ketchum, B. Kirby, M. Kirby, T. Kobilarcik, I. Kreslo, A. Laube, Y. Li, A. Lister, B. R. Littlejohn, S. Lockwitz, D. Lorca, W. C. Louis, M. Luethi, B. Lundberg, X. Luo, A. Marchionni, C. Mariani, J. Marshall, D. A. Martinez Caicedo, V. Meddage, T. Miceli, G. B. Mills, J. Moon, M. Mooney, C. D. Moore, J. Mousseau, R. Murrells, D. Naples, P. Nienaber, J. Nowak, O. Palamara, V. Paolone, V. Papavassiliou, S. F. Pate, Z. Pavlovic, E. Piasetzky, D. Porzio, G. Pulliam, X. Qian, J. L. Raaf, A. Rafique, L. Rochester, C. Rudolf von Rohr, B. Russell, D. W. Schmitz, A. Schukraft, W. Seligman, M. H. Shaevitz, J. Sinclair, E. L. Snider, M. Soderberg, S. Soldner-Rembold, S. R. Soleti, P. Spentzouris, J. Spitz, J. St. John, T. Strauss, K. A. Sutton, A. M. Szelc, N. Tagg, K. Terao, M. Thomson, M. Toups, Y. -T. Tsai, S. Tufanli, T. Usher, R. G. Van de Water, B. Viren, M. Weber, D. A. Wickremasinghe, S. Wolbers, T. Wongjirad, K. Woodruff, T. Yang, L. Yates, G. P. Zeller, J. Zennamo, C. Zhang

The MicroBooNE liquid argon time projection chamber (LArTPC) has been taking data at Fermilab since 2015 collecting, in addition to neutrino beam, cosmic-ray muons. Results are presented on the reconstruction of Michel electrons produced by the decay at rest of cosmic-ray muons. Michel electrons are abundantly produced in the TPC, and given their well known energy spectrum can be used to study MicroBooNE's detector response to low-energy electrons (electrons with energies up to ~50 MeV). Read More

Efficiency is a critical factor limiting the applications of nonlinear plasmonic devices. We show by theory and experiments that high efficiency four-wave mixing (FWM) is achieved in nanometer size plasmonic hotspots, which open up opportunities for nanoscale light manipulation. First, we present a classical calculation on the efficiency of frequency conversion by quadruple-enhanced FWM for a Kerr nonlinear material loaded in the plasmonic hotspot of a gold nanosphere dimer. Read More

As a continuation of \cite{LXY}, the paper aims to justify the high Reynolds numbers limit for the MHD system with Prandtl boundary layer expansion when no-slip boundary condition is imposed on the velocity field and the perfect conducting boundary condition is given for the magnetic field. Under an assumption that the viscosity and resistivity coefficients are of the same order and the initial tangential magnetic field on the boundary is not degenerate, we justify the validity of the Prandtl boundary layer expansion and give a $L^{\infty}$ estimate on the error by multi-scale analysis. Read More

The Boltzmann H-theorem implies that the solution to the Boltzmann equation tends to an equilibrium, that is, a Maxwellian when time tends to infinity. This has been proved in varies settings when the initial energy is finite. However, when the initial energy is infinite, the time asymptotic state is no longer described by a Maxwellian, but a self-similar solution obtained by Bobylev-Cercignani. Read More

Deep neural networks (DNNs) are currently widely used for many artificial intelligence (AI) applications including computer vision, speech recognition, and robotics. While DNNs deliver state-of-the-art accuracy on many AI tasks, it comes at the cost of high computational complexity. Accordingly, techniques that enable efficient processing of deep neural network to improve energy-efficiency and throughput without sacrificing performance accuracy or increasing hardware cost are critical to enabling the wide deployment of DNNs in AI systems. Read More

We perform a forecast analysis of the ability of the LISA space-based interferometer to reconstruct the dark sector interaction using gravitational wave (GW) standard sirens at high redshift. We employ Gaussian process methods to reconstruct the distance-redshift relation in a model independent way. We adopt simulated catalogues of standard sirens given by merging massive black hole binaries (MBHBs) visible by LISA, with an electromagnetic (EM) counterpart detectable by future telescopes. Read More

2017Mar
Authors: MicroBooNE collaboration, P. Abratenko, R. Acciarri, C. Adams, R. An, J. Asaadi, M. Auger, L. Bagby, S. Balasubramanian, B. Baller, C. Barnes, G. Barr, M. Bass, F. Bay, M. Bishai, A. Blake, T. Bolton, L. Bugel, L. Camilleri, D. Caratelli, B. Carls, R. Castillo Fernandez, F. Cavanna, H. Chen, E. Church, D. Cianci, E. Cohen, G. H. Collin, J. M. Conrad, M. Convery, J. I. Crespo-Anadon, M. Del Tutto, D. Devitt, S. Dytman, B. Eberly, A. Ereditato, L. Escudero Sanchez, J. Esquivel, B. T. Fleming, W. Foreman, A. P. Furmanski, D. Garcia-Gamez, G. T. Garvey, V. Genty, D. Goeldi, S. Gollapinni, N. Graf, E. Gramellini, H. Greenlee, R. Grosso, R. Guenette, A. Hackenburg, P. Hamilton, O. Hen, J. Hewes, C. Hill, J. Ho, G. Horton-Smith, E. -C. Huang, C. James, J. Jan de Vries, C. -M. Jen, L. Jiang, R. A. Johnson, B. J. P. Jones, J. Joshi, H. Jostlein, D. Kaleko, L. N. Kalousis, G. Karagiorgi, W. Ketchum, B. Kirby, M. Kirby, T. Kobilarcik, I. Kreslo, A. Laube, Y. Li, A. Lister, B. R. Littlejohn, S. Lockwitz, D. Lorca, W. C. Louis, M. Luethi, B. Lundberg, X. Luo, A. Marchionni, C. Mariani, J. Marshall, D. A. Martinez Caicedo, V. Meddage, T. Miceli, G. B. Mills, J. Moon, M. Mooney, C. D. Moore, J. Mousseau, R. Murrells, D. Naples, P. Nienaber, J. Nowak, O. Palamara, V. Paolone, V. Papavassiliou, S. F. Pate, Z. Pavlovic, E. Piasetzky, D. Porzio, G. Pulliam, X. Qian, J. L. Raaf, A. Rafique, L. Rochester, C. Rudolf von Rohr, B. Russell, D. W. Schmitz, A. Schukraft, W. Seligman, M. H. Shaevitz, J. Sinclair, E. L. Snider, M. Soderberg, S. Soldner-Rembold, S. R. Soleti, P. Spentzouris, J. Spitz, J. St. John, T. Strauss, A. M. Szelc, N. Tagg, K. Terao, M. Thomson, M. Toups, Y. -T. Tsai, S. Tufanli, T. Usher, R. G. Van de Water, B. Viren, M. Weber, J. Weston, D. A. Wickremasinghe, S. Wolbers, T. Wongjirad, K. Woodruff, T. Yang, L. Yates, G. P. Zeller, J. Zennamo, C. Zhang

We discuss a technique for measuring a charged particle's momentum by means of multiple Coulomb scattering (MCS) in the MicroBooNE liquid argon time projection chamber (LArTPC). This method does not require the full particle ionization track to be contained inside of the detector volume as other track momentum reconstruction methods do (range-based momentum reconstruction and calorimetric momentum reconstruction). We motivate use of this technique, describe a tuning of the underlying phenomenological formula, quantify its performance on fully contained beam-neutrino-induced muon tracks both in simulation and in data, and quantify its performance on exiting muon tracks in simulation. Read More

The direct detection of gravitational wave by LIGO indicates the coming of the era of gravitational wave astronomy and gravitational wave cosmology. It is expected that more and more gravitational wave events will be detected by currently existing and planed gravitational wave detectors. The gravitational waves open a new window to explore the Universe and various mysteries will be disclosed through the gravitational wave detection, combined with other cosmological probes. Read More

We consider a D2D-enabled cellular network where user equipments (UEs) owned by rational users are incentivized to form D2D pairs using tokens. They exchange tokens electronically to "buy" and "sell" D2D services. Meanwhile the devices have the ability to choose the transmission mode, i. Read More

2017Mar
Authors: CDF Collaboration, T. Aaltonen, M. G. Albrow, S. Amerio, D. Amidei, A. Anastassov, A. Annovi, J. Antos, G. Apollinari, J. A. Appel, T. Arisawa, A. Artikov, J. Asaadi, W. Ashmanskas, B. Auerbach, A. Aurisano, F. Azfar, W. Badgett, T. Bae, A. Barbaro-Galtieri, V. E. Barnes, B. A. Barnett, P. Barria, P. Bartos, M. Bauce, F. Bedeschi, S. Behari, G. Bellettini, J. Bellinger, D. Benjamin, A. Beretvas, A. Bhatti, K. R. Bland, B. Blumenfeld, A. Bocci, A. Bodek, D. Bortoletto, J. Boudreau, A. Boveia, L. Brigliadori, C. Bromberg, E. Brucken, J. Budagov, H. S. Budd, K. Burkett, G. Busetto, P. Bussey, P. Butti, A. Buzatu, A. Calamba, S. Camarda, M. Campanelli, F. Canelli, B. Carls, D. Carlsmith, R. Carosi, S. Carrillo, B. Casal, M. Casarsa, A. Castro, P. Catastini, D. Cauz, V. Cavaliere, A. Cerri, L. Cerrito, Y. C. Chen, M. Chertok, G. Chiarelli, G. Chlachidze, K. Cho, D. Chokheli, A. Clark, C. Clarke, M. E. Convery, J. Conway, M. Corbo, M. Cordelli, C. A. Cox, D. J. Cox, M. Cremonesi, D. Cruz, J. Cuevas, R. Culbertson, N. d'Ascenzo, M. Datta, P. de Barbaro, L. Demortier, M. Deninno, F. Devoto, M. D'Errico, A. Di Canto, B. Di Ruzza, J. R. Dittmann, M. D'Onofrio, S. Donati, M. Dorigo, A. Driutti, K. Ebina, R. Edgar, R. Erbacher, S. Errede, B. Esham, S. Farrington, J. P. Fernández Ramos, R. Field, G. Flanagan, R. Forrest, M. Franklin, J. C. Freeman, H. Frisch, Y. Funakoshi, C. Galloni, A. F. Garfinkel, P. Garosi, H. Gerberich, E. Gerchtein, S. Giagu, V. Giakoumopoulou, K. Gibson, C. M. Ginsburg, N. Giokaris, P. Giromini, V. Glagolev, D. Glenzinski, M. Gold, D. Goldin, A. Golossanov, G. Gomez, G. Gomez-Ceballos, M. Goncharov, O. González López, I. Gorelov, A. T. Goshaw, K. Goulianos, E. Gramellini, C. Grosso-Pilcher, J. Guimaraes da Costa, S. R. Hahn, J. Y. Han, F. Happacher, K. Hara, M. Hare, R. F. Harr, T. Harrington-Taber, K. Hatakeyama, C. Hays, J. Heinrich, M. Herndon, A. Hocker, Z. Hong, W. Hopkins, S. Hou, R. E. Hughes, U. Husemann, M. Hussein, J. Huston, G. Introzzi, M. Iori, A. Ivanov, E. James, D. Jang, B. Jayatilaka, E. J. Jeon, S. Jindariani, M. Jones, K. K. Joo, S. Y. Jun, T. R. Junk, M. Kambeitz, T. Kamon, P. E. Karchin, A. Kasmi, Y. Kato, W. Ketchum, J. Keung, B. Kilminster, D. H. Kim, H. S. Kim, J. E. Kim, M. J. Kim, S. B. Kim, S. H. Kim, Y. K. Kim, Y. J. Kim, N. Kimura, M. Kirby, K. Kondo, D. J. Kong, J. Konigsberg, A. V. Kotwal, M. Kreps, J. Kroll, M. Kruse, T. Kuhr, M. Kurata, A. T. Laasanen, S. Lammel, M. Lancaster, K. Lannon, G. Latino, H. S. Lee, J. S. Lee, S. Leo, S. Leone, J. D. Lewis, A. Limosani, E. Lipeles, A. Lister, Q. Liu, T. Liu, S. Lockwitz, A. Loginov, A. Lucà, D. Lucchesi, J. Lueck, P. Lujan, P. Lukens, G. Lungu, J. Lys, R. Lysak, R. Madrak, P. Maestro, S. Malik, G. Manca, A. Manousakis-Katsikakis, L. Marchese, F. Margaroli, P. Marino, K. Matera, M. E. Mattson, A. Mazzacane, P. Mazzanti, R. McNulty, A. Mehta, P. Mehtala, C. Mesropian, T. Miao, D. Mietlicki, A. Mitra, H. Miyake, S. Moed, N. Moggi, C. S. Moon, R. Moore, M. J. Morello, A. Mukherjee, Th. Muller, P. Murat, M. Mussini, J. Nachtman, Y. Nagai, J. Naganoma, I. Nakano, A. Napier, J. Nett, T. Nigmanov, L. Nodulman, S. Y. Noh, O. Norniella, L. Oakes, S. H. Oh, Y. D. Oh, T. Okusawa, R. Orava, L. Ortolan, C. Pagliarone, E. Palencia, P. Palni, V. Papadimitriou, W. Parker, G. Pauletta, M. Paulini, C. Paus, T. J. Phillips, G. Piacentino, E. Pianori, J. Pilot, K. Pitts, C. Plager, L. Pondrom, S. Poprocki, K. Potamianos, F. Prokoshin, A. Pranko, F. Ptohos, G. Punzi, I. Redondo Fernández, P. Renton, M. Rescigno, F. Rimondi, L. Ristori, A. Robson, T. Rodriguez, S. Rolli, M. Ronzani, R. Roser, J. L. Rosner, F. Ruffini, A. Ruiz, J. Russ, V. Rusu, W. K. Sakumoto, Y. Sakurai, L. Santi, K. Sato, V. Saveliev, A. Savoy-Navarro, P. Schlabach, E. E. Schmidt, T. Schwarz, L. Scodellaro, F. Scuri, S. Seidel, Y. Seiya, A. Semenov, F. Sforza, S. Z. Shalhout, T. Shears, P. F. Shepard, M. Shimojima, M. Shochet, I. Shreyber-Tecker, A. Simonenko, P. Sinervo, K. Sliwa, J. R. Smith, F. D. Snider, V. Sorin, H. Song, M. Stancari, R. St. Denis, D. Stentz, J. Strologas, Y. Sudo, A. Sukhanov, I. Suslov, K. Takemasa, Y. Takeuchi, J. Tang, M. Tecchio, P. K. Teng, J. Thom, E. Thomson, V. Thukral, D. Toback, S. Tokar, K. Tollefson, T. Tomura, D. Tonelli, S. Torre, D. Torretta, P. Totaro, M. Trovato, F. Ukegawa, S. Uozumi, F. Vázquez, G. Velev, C. Vellidis, C. Vernieri, M. Vidal, R. Vilar, J. Vizán, M. Vogel, G. Volpi, P. Wagner, R. Wallny, S. M. Wang, D. Waters, W. C. Wester III, D. Whiteson, A. B. Wicklund, S. Wilbur, H. H. Williams, J. S. Wilson, P. Wilson, B. L. Winer, P. Wittich, S. Wolbers, H. Wolfe, T. Wright, X. Wu, Z. Wu, K. Yamamoto, D. Yamato, T. Yang, U. K. Yang, Y. C. Yang, W. -M. Yao, G. P. Yeh, K. Yi, J. Yoh, K. Yorita, T. Yoshida, G. B. Yu, I. Yu, A. M. Zanetti, Y. Zeng, C. Zhou, S. Zucchelli

A measurement of the inclusive production cross section of isolated prompt photons in proton-antiproton collisions at center-of-mass energy $\sqrt{s}$=1.96TeV is presented. The results are obtained using the full Run II data sample collected with the Collider Detector at the Fermilab Tevatron, which corresponds to an integrated luminosity of 9. Read More

Single-phased, single-oriented thin films of Mn-doped ZnAs-based diluted magnetic semiconductor (DMS) Ba1-xKx(Zn1-yMny)2As2 (x = 0.03, 0.08; y = 0. Read More

In this paper, we proved an arithmetic Siegel-Weil formula and the modularity of some arithmetic theta function on the modular curve $X_0(N)$ when $N$ is square free. In the process, we also construct some generalized Delta function for $\Gamma_0(N)$ and proved some explicit Kronecker limit formula for Eisenstein series on $X_0(N)$. Read More

We form generating series of special divisors, valued in the Chow group and in the arithmetic Chow group, on the compactified integral model of a Shimura variety associated to a unitary group of signature (n-1,1), and prove their modularity. The main ingredient of the proof is the calculation of the vertical components appearing in the divisor of a Borcherds product on the integral model. Read More

Although there exist plentiful theories of empirical risk minimization (ERM) for supervised learning, current theoretical understandings of ERM for a related problem---stochastic convex optimization (SCO), are limited. In this work, we strengthen the realm of ERM for SCO by exploiting smoothness and strong convexity conditions to improve the risk bounds. First, we establish an $\widetilde{O}(d/n + \sqrt{F_*/n})$ risk bound when the random function is nonnegative, convex and smooth, and the expected function is Lipschitz continuous, where $d$ is the dimensionality of the problem, $n$ is the number of samples, and $F_*$ is the minimal risk. Read More

In this note, we construct canonical bases for the spaces of weakly holomorphic modular forms with poles supported at the cusp $\infty$ for $\Gamma_{0}(4)$ of integral weight $k$ for $k\leq-1$, and we make use of the basis elements for the case $k=-1$ to construct explicit Borcherds products on unitary group $U(2,1)$. Read More

We obtain a formula for the Turaev-Viro invariants of a link complement in terms of values of the colored Jones polynomial of the link. As an application we give the first examples for which the volume conjecture of Chen and the third named author\,\cite{Chen-Yang} is verified. Namely, we show that the asymptotics of the Turaev-Viro invariants of the Figure-eight knot and the Borromean rings complement determine the corresponding hyperbolic volumes. Read More

To cope with changing environments, recent developments in online learning have introduced the concepts of adaptive regret and dynamic regret independently. In this paper, we illustrate an intrinsic connection between these two concepts by showing that the dynamic regret can be expressed in terms of the adaptive regret and the functional variation. This observation implies that strongly adaptive algorithms can be directly leveraged to minimize the dynamic regret. Read More

A sketch is a probabilistic data structure used to record frequencies of items in a multi-set. Sketches are widely used in various fields, especially those that involve processing and storing data streams. In streaming applications with high data rates, a sketch "fills up" very quickly. Read More

Demand response represents a significant but largely untapped resource that can greatly enhance the flexibility and reliability of power systems. This paper proposes a hierarchical control framework to facilitate the integrated coordination between distributed energy resources and demand response. The proposed framework consists of coordination and device layers. Read More

2016Dec
Authors: MicroBooNE Collaboration, R. Acciarri, C. Adams, R. An, A. Aparicio, S. Aponte, J. Asaadi, M. Auger, N. Ayoub, L. Bagby, B. Baller, R. Barger, G. Barr, M. Bass, F. Bay, K. Biery, M. Bishai, A. Blake, V. Bocean, D. Boehnlein, V. D. Bogert, T. Bolton, L. Bugel, C. Callahan, L. Camilleri, D. Caratelli, B. Carls, R. Castillo Fernandez, F. Cavanna, S. Chappa, H. Chen, K. Chen, C. Y. Chi, C. S. Chiu, E. Church, D. Cianci, G. H. Collin, J. M. Conrad, M. Convery, J. Cornele, P. Cowan, J. I. Crespo-Anadon, G. Crutcher, C. Darve, R. Davis, M. Del Tutto, D. Devitt, S. Duffin, S. Dytman, B. Eberly, A. Ereditato, D. Erickson, L. Escudero Sanchez, J. Esquivel, S. Farooq, J. Farrell, D. Featherston, B. T. Fleming, W. Foreman, A. P. Furmanski, V. Genty, M. Geynisman, D. Goeldi, B. Goff, S. Gollapinni, N. Graf, E. Gramellini, J. Green, A. Greene, H. Greenlee, T. Griffin, R. Grosso, R. Guenette, A. Hackenburg, R. Haenni, P. Hamilton, P. Healey, O. Hen, E. Henderson, J. Hewes, C. Hill, K. Hill, L. Himes, J. Ho, G. Horton-Smith, D. Huffman, C. M. Ignarra, C. James, E. James, J. Jan de Vries, W. Jaskierny, C. M. Jen, L. Jiang, B. Johnson, M. Johnson, R. A. Johnson, B. J. P. Jones, J. Joshi, H. Jostlein, D. Kaleko, L. N. Kalousis, G. Karagiorgi, T. Katori, P. Kellogg, W. Ketchum, J. Kilmer, B. King, B. Kirby, M. Kirby, E. Klein, T. Kobilarcik, I. Kreslo, R. Krull, R. Kubinski, G. Lange, F. Lanni, A. Lathrop, A. Laube, W. M. Lee, Y. Li, D. Lissauer, A. Lister, B. R. Littlejohn, S. Lockwitz, D. Lorca, W. C. Louis, G. Lukhanin, M. Luethi, B. Lundberg, X. Luo, G. Mahler, I. Majoros, D. Makowiecki, A. Marchionni, C. Mariani, D. Markley, J. Marshall, D. A. Martinez Caicedo, K. T. McDonald, D. McKee, A. McLean, J. Mead, V. Meddage, T. Miceli, G. B. Mills, W. Miner, J. Moon, M. Mooney, C. D. Moore, Z. Moss, J. Mousseau, R. Murrells, D. Naples, P. Nienaber, B. Norris, N. Norton, J. Nowak, M. OBoyle, T. Olszanowski, O. Palamara, V. Paolone, V. Papavassiliou, S. F. Pate, Z. Pavlovic, R. Pelkey, M. Phipps, S. Pordes, D. Porzio, G. Pulliam, X. Qian, J. L. Raaf, V. Radeka, A. Rafique, R. A Rameika, B. Rebel, R. Rechenmacher, S. Rescia, L. Rochester, C. Rudolf von Rohr, A. Ruga, B. Russell, R. Sanders, W. R. Sands III, M. Sarychev, D. W. Schmitz, A. Schukraft, R. Scott, W. Seligman, M. H. Shaevitz, M. Shoun, J. Sinclair, W. Sippach, T. Smidt, A. Smith, E. L. Snider, M. Soderberg, M. Solano-Gonzalez, S. Soldner-Rembold, S. R. Soleti, J. Sondericker, P. Spentzouris, J. Spitz, J. St. John, T. Strauss, K. Sutton, A. M. Szelc, K. Taheri, N. Tagg, K. Tatum, J. Teng, K. Terao, M. Thomson, C. Thorn, J. Tillman, M. Toups, Y. T. Tsai, S. Tufanli, T. Usher, M. Utes, R. G. Van de Water, C. Vendetta, S. Vergani, E. Voirin, J. Voirin, B. Viren, P. Watkins, M. Weber, T. Wester, J. Weston, D. A. Wickremasinghe, S. Wolbers, T. Wongjirad, K. Woodruff, K. C. Wu, T. Yang, B. Yu, G. P. Zeller, J. Zennamo, C. Zhang, M. Zuckerbrot

This paper describes the design and construction of the MicroBooNE liquid argon time projection chamber and associated systems. MicroBooNE is the first phase of the Short Baseline Neutrino program, located at Fermilab, and will utilize the capabilities of liquid argon detectors to examine a rich assortment of physics topics. In this document details of design specifications, assembly procedures, and acceptance tests are reported. Read More

The wide-field synoptic sky surveys, known as the Palomar Transient Factory (PTF) and the intermediate Palomar Transient Factory (iPTF), will accumulate a large number of known and new RR Lyrae. These RR Lyrae are good tracers to study the substructure of the Galactic halo if their distance, metallicity, and galactocentric velocity can be measured. Candidates of halo RR Lyrae can be identified from their distance and metallicity before requesting spectroscopic observations for confirmation. Read More

In this paper, we address learning problems for high dimensional data. Previously, oblivious random projection based approaches that project high dimensional features onto a random subspace have been used in practice for tackling high-dimensionality challenge in machine learning. Recently, various non-oblivious randomized reduction methods have been developed and deployed for solving many numerical problems such as matrix product approximation, low-rank matrix approximation, etc. Read More

Bell's theorem shows a profound contradiction between local realism and quantum mechanics on the level of statistical predictions. It does not involve directly Einstein-Podolsky-Rosen (EPR) correlations. The paradox of Greenberger-Horne-Zeilinger (GHZ) disproves directly the concept of EPR elements of reality, based on the EPR correlations, in an all-versus-nothing way. Read More

Recent studies have shown that proximal gradient (PG) method and accelerated gradient method (APG) with restarting can enjoy a linear convergence under a weaker condition than strong convexity, namely a quadratic growth condition (QGC). However, the faster convergence of restarting APG method relies on the potentially unknown constant in QGC to appropriately restart APG, which restricts its applicability. We address this issue by developing a novel adaptive gradient converging methods, i. Read More

We study the well-posedness theory for the MHD boundary layer. The boundary layer equations are governed by the Prandtl type equations that are derived from the incompressible MHD system with non-slip boundary condition on the velocity and perfectly conducting condition on the magnetic field. Under the assumption that the initial tangential magnetic field is not zero, we establish the local-in-time existence, uniqueness of solution for the nonlinear MHD boundary layer equations. Read More

2016Nov
Authors: MicroBooNE collaboration, R. Acciarri, C. Adams, R. An, J. Asaadi, M. Auger, L. Bagby, B. Baller, G. Barr, M. Bass, F. Bay, M. Bishai, A. Blake, T. Bolton, L. Bugel, L. Camilleri, D. Caratelli, B. Carls, R. Castillo Fernandez, F. Cavanna, H. Chen, E. Church, D. Cianci, G. H. Collin, J. M. Conrad, M. Convery, J. I. Crespo-Anadón, M. Del Tutto, D. Devitt, S. Dytman, B. Eberly, A. Ereditato, L. Escudero Sanchez, J. Esquivel, B. T. Fleming, W. Foreman, A. P. Furmanski, G. T. Garvey, V. Genty, D. Goeldi, S. Gollapinni, N. Graf, E. Gramellini, H. Greenlee, R. Grosso, R. Guenette, A. Hackenburg, P. Hamilton, O. Hen, J. Hewes, C. Hill, J. Ho, G. Horton-Smith, C. James, J. Jan de Vries, C. -M. Jen, L. Jiang, R. A. Johnson, B. J. P. Jones, J. Joshi, H. Jostlein, D. Kaleko, G. Karagiorgi, W. Ketchum, B. Kirby, M. Kirby, T. Kobilarcik, I. Kreslo, A. Laube, Y. Li, A. Lister, B. R. Littlejohn, S. Lockwitz, D. Lorca, W. C. Louis, M. Luethi, B. Lundberg, X. Luo, A. Marchionni, C. Mariani, J. Marshall, D. A. Martinez Caicedo, V. Meddage, T. Miceli, G. B. Mills, J. Moon, M. Mooney, C. D. Moore, J. Mousseau, R. Murrells, D. Naples, P. Nienaber, J. Nowak, O. Palamara, V. Paolone, V. Papavassiliou, S. F. Pate, Z. Pavlovic, D. Porzio, G. Pulliam, X. Qian, J. L. Raaf, A. Rafique, L. Rochester, C. Rudolf von Rohr, B. Russell, D. W. Schmitz, A. Schukraft, W. Seligman, M. H. Shaevitz, J. Sinclair, E. L. Snider, M. Soderberg, S. Söldner-Rembold, S. R. Soleti, P. Spentzouris, J. Spitz, J. St. John, T. Strauss, A. M. Szelc, N. Tagg, K. Terao, M. Thomson, M. Toups, Y. -T. Tsai, S. Tufanli, T. Usher, R. G. Van de Water, B. Viren, M. Weber, J. Weston, D. A. Wickremasinghe, S. Wolbers, T. Wongjirad, K. Woodruff, T. Yang, G. P. Zeller, J. Zennamo, C. Zhang

We present several studies of convolutional neural networks applied to data coming from the MicroBooNE detector, a liquid argon time projection chamber (LArTPC). The algorithms studied include the classification of single particle images, the localization of single particle and neutrino interactions in an image, and the detection of a simulated neutrino event overlaid with cosmic ray backgrounds taken from real detector data. These studies demonstrate the potential of convolutional neural networks for particle identification or event detection on simulated neutrino interactions. Read More

Deep convolutional neural networks (CNNs) are indispensable to state-of-the-art computer vision algorithms. However, they are still rarely deployed on battery-powered mobile devices, such as smartphones and wearable gadgets, where vision algorithms can enable many revolutionary real-world applications. The key limiting factor is the high energy consumption of CNN processing due to its high computational complexity. Read More

In this paper, we consider a system of forward-backward stochastic differential equations (FBSDEs) with monotone functionals. We show the existence and uniqueness of such a system by the method of continuation similarly to Peng and Wu (1999) for classical FBSDEs and obtain estimates under conditional probability. As applications, we prove the well-posedness result for a mean field FBSDE with conditional law and show the existence of a decoupling function. Read More

We consider the Czir\'ok model for collective motion of locusts along a one-dimensional torus. In the model, each agent's velocity locally interacts with other agents' velocities in the system, and there is also exogenous randomness to each agent's velocity. The interaction tends to create the alignment of collective motion. Read More

2016Oct
Authors: CDF Collaboration, T. Aaltonen, S. Amerio, D. Amidei, A. Anastassov, A. Annovi, J. Antos, G. Apollinari, J. A. Appel, T. Arisawa, A. Artikov, J. Asaadi, W. Ashmanskas, B. Auerbach, A. Aurisano, F. Azfar, W. Badgett, T. Bae, A. Barbaro-Galtieri, V. E. Barnes, B. A. Barnett, P. Barria, P. Bartos, M. Bauce, F. Bedeschi, S. Behari, G. Bellettini, J. Bellinger, D. Benjamin, A. Beretvas, A. Bhatti, K. R. Bland, B. Blumenfeld, A. Bocci, A. Bodek, D. Bortoletto, J. Boudreau, A. Boveia, L. Brigliadori, C. Bromberg, E. Brucken, J. Budagov, H. S. Budd, K. Burkett, G. Busetto, P. Bussey, P. Butti, A. Buzatu, A. Calamba, S. Camarda, M. Campanelli, F. Canelli, B. Carls, D. Carlsmith, R. Carosi, S. Carrillo, B. Casal, M. Casarsa, A. Castro, P. Catastini, D. Cauz, V. Cavaliere, A. Cerri, L. Cerrito, Y. C. Chen, M. Chertok, G. Chiarelli, G. Chlachidze, K. Cho, D. Chokheli, A. Clark, C. Clarke, M. E. Convery, J. Conway, M. Corbo, M. Cordelli, C. A. Cox, D. J. Cox, M. Cremonesi, D. Cruz, J. Cuevas, R. Culbertson, N. d'Ascenzo, M. Datta, P. de Barbaro, L. Demortier, M. Deninno, F. Devoto, M. D'Errico, A. Di Canto, B. Di Ruzza, J. R. Dittmann, M. D'Onofrio, S. Donati, M. Dorigo, A. Driutti, K. Ebina, R. Edgar, R. Erbacher, S. Errede, B. Esham, S. Farrington, J. P. Fernández Ramos, R. Field, G. Flanagan, R. Forrest, M. Franklin, J. C. Freeman, H. Frisch, Y. Funakoshi, C. Galloni, A. F. Garfinkel, P. Garosi, H. Gerberich, E. Gerchtein, S. Giagu, V. Giakoumopoulou, K. Gibson, C. M. Ginsburg, N. Giokaris, P. Giromini, V. Glagolev, D. Glenzinski, M. Gold, D. Goldin, A. Golossanov, G. Gomez, G. Gomez-Ceballos, M. Goncharov, O. González López, I. Gorelov, A. T. Goshaw, K. Goulianos, E. Gramellini, C. Grosso-Pilcher, J. Guimaraes da Costa, S. R. Hahn, J. Y. Han, F. Happacher, K. Hara, M. Hare, R. F. Harr, T. Harrington-Taber, K. Hatakeyama, C. Hays, J. Heinrich, M. Herndon, A. Hocker, Z. Hong, W. Hopkins, S. Hou, R. E. Hughes, U. Husemann, M. Hussein, J. Huston, G. Introzzi, M. Iori, A. Ivanov, E. James, D. Jang, B. Jayatilaka, E. J. Jeon, S. Jindariani, M. Jones, K. K. Joo, S. Y. Jun, T. R. Junk, M. Kambeitz, T. Kamon, P. E. Karchin, A. Kasmi, Y. Kato, W. Ketchum, J. Keung, B. Kilminster, D. H. Kim, H. S. Kim, J. E. Kim, M. J. Kim, S. B. Kim, S. H. Kim, Y. K. Kim, Y. J. Kim, N. Kimura, M. Kirby, K. Kondo, D. J. Kong, J. Konigsberg, A. V. Kotwal, M. Kreps, J. Kroll, M. Kruse, T. Kuhr, M. Kurata, A. T. Laasanen, S. Lammel, M. Lancaster, K. Lannon, G. Latino, H. S. Lee, J. S. Lee, S. Leo, S. Leone, J. D. Lewis, A. Limosani, E. Lipeles, A. Lister, Q. Liu, T. Liu, S. Lockwitz, A. Loginov, A. Lucà, D. Lucchesi, J. Lueck, P. Lujan, P. Lukens, G. Lungu, J. Lys, R. Lysak, R. Madrak, P. Maestro, S. Malik, G. Manca, A. Manousakis-Katsikakis, L. Marchese, F. Margaroli, P. Marino, K. Matera, M. E. Mattson, A. Mazzacane, P. Mazzanti, R. McNulty, A. Mehta, P. Mehtala, C. Mesropian, T. Miao, D. Mietlicki, A. Mitra, H. Miyake, S. Moed, N. Moggi, C. S. Moon, R. Moore, M. J. Morello, A. Mukherjee, Th. Muller, P. Murat, M. Mussini, J. Nachtman, Y. Nagai, J. Naganoma, I. Nakano, A. Napier, J. Nett, T. Nigmanov, L. Nodulman, S. Y. Noh, O. Norniella, L. Oakes, S. H. Oh, Y. D. Oh, T. Okusawa, R. Orava, L. Ortolan, C. Pagliarone, E. Palencia, P. Palni, V. Papadimitriou, W. Parker, G. Pauletta, M. Paulini, C. Paus, T. J. Phillips, G. Piacentino, E. Pianori, J. Pilot, K. Pitts, C. Plager, L. Pondrom, S. Poprocki, K. Potamianos, F. Prokoshin, A. Pranko, F. Ptohos, G. Punzi, I. Redondo Fernández, P. Renton, M. Rescigno, F. Rimondi, L. Ristori, A. Robson, T. Rodriguez, S. Rolli, M. Ronzani, R. Roser, J. L. Rosner, F. Ruffini, A. Ruiz, J. Russ, V. Rusu, W. K. Sakumoto, Y. Sakurai, L. Santi, K. Sato, V. Saveliev, A. Savoy-Navarro, P. Schlabach, E. E. Schmidt, T. Schwarz, L. Scodellaro, F. Scuri, S. Seidel, Y. Seiya, A. Semenov, F. Sforza, S. Z. Shalhout, T. Shears, P. F. Shepard, M. Shimojima, M. Shochet, I. Shreyber-Tecker, A. Simonenko, K. Sliwa, J. R. Smith, F. D. Snider, V. Sorin, H. Song, M. Stancari, R. St. Denis, D. Stentz, J. Strologas, Y. Sudo, A. Sukhanov, I. Suslov, K. Takemasa, Y. Takeuchi, J. Tang, M. Tecchio, P. K. Teng, J. Thom, E. Thomson, V. Thukral, D. Toback, S. Tokar, K. Tollefson, T. Tomura, D. Tonelli, S. Torre, D. Torretta, P. Totaro, M. Trovato, F. Ukegawa, S. Uozumi, F. Vázquez, G. Velev, C. Vellidis, C. Vernieri, M. Vidal, R. Vilar, J. Vizán, M. Vogel, G. Volpi, P. Wagner, R. Wallny, S. M. Wang, D. Waters, W. C. Wester III, D. Whiteson, A. B. Wicklund, S. Wilbur, H. H. Williams, J. S. Wilson, P. Wilson, B. L. Winer, P. Wittich, S. Wolbers, H. Wolfe, T. Wright, X. Wu, Z. Wu, K. Yamamoto, D. Yamato, T. Yang, U. K. Yang, Y. C. Yang, W. -M. Yao, G. P. Yeh, K. Yi, J. Yoh, K. Yorita, T. Yoshida, G. B. Yu, I. Yu, A. M. Zanetti, Y. Zeng, C. Zhou, S. Zucchelli

We report on a measurement of the $D^{+}$-meson production cross section as a function of transverse momentum ($p_T$) in proton-antiproton ($p\bar{p}$) collisions at 1.96 TeV center-of-mass energy, using the full data set collected by the Collider Detector at Fermilab in Tevatron Run II and corresponding to 10 fb$^{-1}$ of integrated luminosity. We use $D^{+} \to K^-\pi^+\pi^+$ decays fully reconstructed in the central rapidity region $|y|<1$ with transverse momentum down to 1. Read More

In prior works, stochastic dual coordinate ascent (SDCA) has been parallelized in a multi-core environment where the cores communicate through shared memory, or in a multi-processor distributed memory environment where the processors communicate through message passing. In this paper, we propose a hybrid SDCA framework for multi-core clusters, the most common high performance computing environment that consists of multiple nodes each having multiple cores and its own shared memory. We distribute data across nodes where each node solves a local problem in an asynchronous parallel fashion on its cores, and then the local updates are aggregated via an asynchronous across-node update scheme. Read More

The capabilities of liquid argon time projection chambers (LArTPCs) to reconstruct the spatial and calorimetric information of neutrino events have made them the detectors of choice in a number of experiments, specifically those looking to observe electron neutrino ($\nu_e$) appearance. The LArTPC promises excellent background rejection capabilities, especially in this "golden" channel for both short and long baseline neutrino oscillation experiments. We present the first experimental observation of electron neutrinos and anti-neutrinos in the ArgoNeut LArTPC, in the energy range relevant to DUNE and the Fermilab Short Baseline Neutrino Program. Read More

A recent surge in the discovery of new ultrafaint dwarf satellites of the Milky Way has inspired the idea of searching for faint satellites, $10^3$\msun$< M_* < 10^6$\msun, around less massive field galaxies in the Local Group. Such satellites would be subject to weaker environmental influences than Milky Way satellites, and could lead to new insights on low mass galaxy formation. In this paper, we predict the number of luminous satellites expected around field dwarf galaxies by applying several abundance matching models and a reionization model to the dark-matter only \textit{Caterpillar} simulation suite. Read More

In the paper, we study the Prandtl system with initial data admitting non-degenerate critical points. For any index $\sigma\in[3/2, 2],$ we obtain the local in time well-posedness in the space of Gevrey class $G^\sigma$ in the tangential variable and Sobolev class in the normal variable so that the monotonicity condition on the tangential velocity is not needed to overcome the loss of tangential derivative. This answers the open question raised in the paper of D. Read More

Thick biological tissues give rise to not only the scattering of incoming light waves, but also aberrations of the remaining unscattered waves. Due to the inability of existing optical imaging methodologies to overcome both of these problems simultaneously, imaging depth at the sub- micron spatial resolution has remained extremely shallow. Here we present an experimental approach for identifying and eliminating aberrations even in the presence of strong multiple light scattering. Read More

Dynamics of vortex clusters is essential for understanding diverse superfluid phenomena. In this paper, we examine the dynamics of vortex quadrupoles in a trapped two-dimensional (2D) Bose-Einstein condensate. We find that the movement of these vortex-clusters fall into three distinct regimes which are fully described by the radial positions of the vortices in a 2D isotropic harmonic trap, or by the major radius (minor radius) of the elliptical equipotential lines decided by the vortex positions in a 2D anisotropic harmonic trap. Read More

In this paper, we show that Hennings construction of invariants of framed links and 3-manifolds obtained from Hopf algebras can also be carried out for some algebraic quantum groups. Read More

In this paper, we provide a pathwise spine decomposition for superprocesses with both local and non-local branching mechanisms under a martingale change of measure. This result complements the related results obtained in Evans (1993), Kyprianou et al. (2012) and Liu, Ren and Song (2009) for superprocesses with purely local branching mechanisms and in Chen, Ren and Song (2016) and Kyprianou and Palau (2016) for multitype superprocesses. Read More

In this paper, we study upper bounds on the sum capacity of the downlink multicell processing model with finite backhaul capacity for the simple case of 2 base stations and 2 mobile users. It is modelled as a two-user multiple access diamond channel. It consists of a first hop from the central processor to the base stations via orthogonal links of finite capacity, and the second hop from the base stations to the mobile users via a Gaussian interference channel. Read More

We investigate the constraint ability of the gravitational wave (GW) as the standard siren on the cosmological parameters by using the third-generation gravitational wave detector: the Einstein Telescope. We simulate the luminosity distances and redshift measurements from 100 to 1000 GW events. We use two different algorithms to constrain the cosmological parameters. Read More

The quantum $\tau_2$-model with generic site-dependent inhomogeneity and arbitrary boundary fields is studied via the off-diagonal Bethe Ansatz method. The eigenvalues of the corresponding transfer matrix are given in terms of an inhomogeneous T-Q relation, which is based on the operator product identities among the fused transfer matrices and the asymptotic behavior of the transfer matrices. Moreover, the associated Bethe Ansatz equations are also obtained. Read More

Genome-wide association studies (GWAS) offer new opportunities to identify genetic risk factors for Alzheimer's disease (AD). Recently, collaborative efforts across different institutions emerged that enhance the power of many existing techniques on individual institution data. However, a major barrier to collaborative studies of GWAS is that many institutions need to preserve individual data privacy. Read More

We investigate the thermodynamic limit of the su(n)-invariant spin chain models with unparallel boundary fields. It is found that the contribution of the inhomogeneous term in the associated T-Q relation to the ground state energy does vanish in the thermodynamic limit. This fact allows us to calculate the boundary energy of the system. Read More

2016Aug
Affiliations: 1National Central University, 2National Central University, 3National Central University, 4National Central University, 5National Central University

We report our measurements for orbital and spin parameters of X 1822-371 using its X-ray partial eclipsing profile and pulsar timing from data collected by the Rossi X-ray Timing Explorer (RXTE). Four more X-ray eclipse times obtained by the RXTE 2011 observations were combined with historical records to trace evolution of orbital period. We found that a cubic ephemeris likely better describes evolution of the X-ray eclipse times during a time span of about 34 years with a marginal second order derivative of $\ddot{P}_{orb}=(-1. Read More

Recently, there has been a growing research interest in the analysis of dynamic regret, which measures the performance of an online learner against a sequence of local minimizers. By exploiting the strong convexity, previous studies have shown that the dynamic regret can be upper bounded by the path-length of the comparator sequence. In this paper, we illustrate that the dynamic regret can be further improved by allowing the learner to query the gradient of the function multiple times, and meanwhile the strong convexity can be weakened to other non-degeneracy conditions. Read More

This paper focuses on convex constrained optimization problems, where the solution is subject to a convex inequality constraint. In particular, we aim at challenging problems for which both projection into the constrained domain and a linear optimization under the inequality constraint are time-consuming, which render both projected gradient methods and conditional gradient methods (a.k. Read More