M. T. Yang - Peking University

M. T. Yang
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Name
M. T. Yang
Affiliation
Peking University
Country
China

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Computer Science - Computer Vision and Pattern Recognition (14)
 
Mathematics - Analysis of PDEs (5)
 
Quantum Physics (3)
 
Mathematics - Combinatorics (3)
 
Physics - Accelerator Physics (3)
 
Physics - Mesoscopic Systems and Quantum Hall Effect (3)
 
Mathematics - Information Theory (2)
 
High Energy Physics - Phenomenology (2)
 
Physics - Fluid Dynamics (2)
 
Instrumentation and Methods for Astrophysics (2)
 
Computer Science - Information Theory (2)
 
Astrophysics of Galaxies (2)
 
Physics - Materials Science (2)
 
Computer Science - Learning (2)
 
Statistics - Machine Learning (2)
 
Quantitative Biology - Quantitative Methods (1)
 
Mathematics - Numerical Analysis (1)
 
Quantitative Biology - Tissues and Organs (1)
 
Mathematics - Functional Analysis (1)
 
Statistics - Computation (1)
 
Mathematics - Optimization and Control (1)
 
Quantitative Biology - Neurons and Cognition (1)
 
Solar and Stellar Astrophysics (1)
 
Physics - Optics (1)
 
Physics - Soft Condensed Matter (1)
 
High Energy Physics - Theory (1)
 
High Energy Physics - Experiment (1)
 
Nuclear Experiment (1)
 
Computer Science - Robotics (1)
 
Computer Science - Networking and Internet Architecture (1)
 
Physics - Instrumentation and Detectors (1)
 
Statistics - Applications (1)

Publications Authored By M. T. Yang

Universal style transfer aims to transfer any arbitrary visual styles to content images. Existing feed-forward based methods, while enjoying the inference efficiency, are mainly limited by inability of generalizing to unseen styles or compromised visual quality. In this paper, we present a simple yet effective method that tackles these limitations without training on any pre-defined styles. Read More

We give the first correction to the suspension viscosity due to fluid elasticity for a dilute suspension of spheres in a viscoelastic medium. Our perturbation theory is valid to $O(\mathrm{Wi}^2)$ in the Weissenberg number $\mathrm{Wi}=\dot\gamma \lambda$, where $\dot\gamma$ is the typical magnitude of the suspension velocity gradient, and $\lambda$ is the relaxation time of the viscoelastic fluid. For shear flow we find that the suspension shear-thickens due to elastic stretching in strain 'hot spots' near the particle, despite the fact that the stress inside the particles decreases relative to the Newtonian case. Read More

We study the strong solution to the 3-D compressible Navier--Stokes equations. We propose a new blow up criterion for barotropic gases in terms of the integral norm of density $\rho$ and the divergence of the velocity $\bu$ without any restriction on the physical viscosity constants. Our blow up criteria can be seen as a partial realization of the underlying principle that the higher integrability implies the boundedness and then eventual regularity. Read More

We study the partial regularity problem of the incompressible Navier--Stokes equations. In this paper, we show that a reverse H\"older inequality of velocity gradient with increasing support holds under the condition that a scaled functional corresponding the local kinetic energy is uniformly bounded. As an application, we give a new bound for the Hausdorff dimension and the Minkowski dimension of singular set when weak solutions $v$ belong to $L^\infty(0,T;L^{3,w}(\mathbb{R}^3))$ where $L^{3,w}(\mathbb{R}^3)$ denotes the standard weak Lebesgue space. Read More

We establish the existence and the pointwise bound of the fundamental solution for the stationary Stokes system with measurable coefficients in the whole space $\mathbb{R}^d$, $d \ge 3$, under the assumption that weak solutions of the system are locally H\"older continuous. We also discuss the existence and the pointwise bound of the Green function for the Stokes system with measurable coefficients on $\Omega$, where $\Omega$ is an unbounded domain such that the divergence equation is solvable. Such a domain includes, for example, half space and an exterior domain. Read More

In this letter, we propose the extended Lorentz transformation in noncommutative geometry, as a possibility on protection of the Higgs mass. In order to reconcile this transformation with the noncommutative differential geometry, we introduce the doubled matrix which describe the differential forms. This formulation of matrix clearly shows the invariance of the bosonic Lagrangian under the transformation. Read More

Colloidal migration in temperature gradient is referred to as thermophoresis. In contrast to particles with spherical shape, we show that elongated colloids may have a thermophoretic response that varies with the colloid orientation. Remarkably, this can translate into a non-vanishing thermophoretic force in the direction perpendicular to the temperature gradient. Read More

The ability to engineer metamaterials with tunable nonlinear optical properties is crucial for nonlinear optics. Traditionally, metals have been employed to enhance nonlinear optical interactions through field localization. Here, inspired by the electronic properties of materials, we introduce and demonstrate experimentally an asymmetric metal-semiconductor-metal (MSM) metamaterial that exhibits a large and electronically tunable effective second-order optical susceptibility (\c{hi}(2)). Read More

In this paper, we propose an effective face completion algorithm using a deep generative model. Different from well-studied background completion, the face completion task is more challenging as it often requires to generate semantically new pixels for the missing key components (e.g. Read More

Text in natural images contains plenty of semantics that are often highly relevant to objects or scene. In this paper, we are concerned with the problem on fully exploiting scene text for visual understanding. The basic idea is combining word representations and deep visual features into a globally trainable deep convolutional neural network. Read More

Convolutional neural networks have recently demonstrated high-quality reconstruction for single-image super-resolution. In this paper, we propose the Laplacian Pyramid Super-Resolution Network (LapSRN) to progressively reconstruct the sub-band residuals of high-resolution images. At each pyramid level, our model takes coarse-resolution feature maps as input, predicts the high-frequency residuals, and uses transposed convolutions for upsampling to the finer level. Read More

Silicene offers an ideal platform for exploring the phase transition due to strong spin-orbit interaction and its unique structure with strong tunability. With applied electric field and circularly polarized light, siliccene is predicted to exhibit rich phases. We propose that these intricate phase transitions can be detected by measuring the bulk Ruderman-Kittel-Kasuya-Yosida (RKKY) interaction. Read More

2017Apr
Authors: F. P. An, A. B. Balantekin, H. R. Band, M. Bishai, S. Blyth, D. Cao, G. F. Cao, J. Cao, Y. L. Chan, J. F. Chang, Y. Chang, H. S. Chen, Q. Y. Chen, S. M. Chen, Y. X. Chen, Y. Chen, J. Cheng, Z. K. Cheng, J. J. Cherwinka, M. C. Chu, A. Chukanov, J. P. Cummings, Y. Y. Ding, M. V. Diwan, M. Dolgareva, J. Dove, D. A. Dwyer, W. R. Edwards, R. Gill, M. Gonchar, G. H. Gong, H. Gong, M. Grassi, W. Q. Gu, L. Guo, X. H. Guo, Y. H. Guo, Z. Guo, R. W. Hackenburg, S. Hans, M. He, K. M. Heeger, Y. K. Heng, A. Higuera, Y. B. Hsiung, B. Z. Hu, T. Hu, E. C. Huang, H. X. Huang, X. T. Huang, Y. B. Huang, P. Huber, W. Huo, G. Hussain, D. E. Jaffe, K. L. Jen, X. P. Ji, X. L. Ji, J. B. Jiao, R. A. Johnson, D. Jones, L. Kang, S. H. Kettell, A. Khan, S. Kohn, M. Kramer, K. K. Kwan, M. W. Kwok, T. J. Langford, K. Lau, L. Lebanowski, J. Lee, J. H. C. Lee, R. T. Lei, R. Leitner, J. K. C. Leung, C. Li, D. J. Li, F. Li, G. S. Li, Q. J. Li, S. Li, S. C. Li, W. D. Li, X. N. Li, X. Q. Li, Y. F. Li, Z. B. Li, H. Liang, C. J. Lin, G. L. Lin, S. Lin, S. K. Lin, Y. -C. Lin, J. J. Ling, J. M. Link, L. Littenberg, B. R. Littlejohn, J. L. Liu, J. C. Liu, C. W. Loh, C. Lu, H. Q. Lu, J. S. Lu, K. B. Luk, X. Y. Ma, X. B. Ma, Y. Q. Ma, Y. Malyshkin, D. A. Martinez Caicedo, K. T. McDonald, R. D. McKeown, I. Mitchell, Y. Nakajima, J. Napolitano, D. Naumov, E. Naumova, H. Y. Ngai, J. P. Ochoa-Ricoux, A. Olshevskiy, H. -R. Pan, J. Park, S. Patton, V. Pec, J. C. Peng, L. Pinsky, C. S. J. Pun, F. Z. Qi, M. Qi, X. Qian, R. M. Qiu, N. Raper, J. Ren, R. Rosero, B. Roskovec, X. C. Ruan, H. Steiner, P. Stoler, J. L. Sun, W. Tang, D. Taychenachev, K. Treskov, K. V. Tsang, C. E. Tull, N. Viaux, B. Viren, V. Vorobel, C. H. Wang, M. Wang, N. Y. Wang, R. G. Wang, W. Wang, X. Wang, Y. F. Wang, Z. Wang, Z. Wang, Z. M. Wang, H. Y. Wei, L. J. Wen, K. Whisnant, C. G. White, L. Whitehead, T. Wise, H. L. H. Wong, S. C. F. Wong, E. Worcester, C. -H. Wu, Q. Wu, W. J. Wu, D. M. Xia, J. K. Xia, Z. Z. Xing, J. L. Xu, Y. Xu, T. Xue, C. G. Yang, H. Yang, L. Yang, M. S. Yang, M. T. Yang, Y. Z. Yang, M. Ye, Z. Ye, M. Yeh, B. L. Young, Z. Y. Yu, S. Zeng, L. Zhan, C. Zhang, C. C. Zhang, H. H. Zhang, J. W. Zhang, Q. M. Zhang, R. Zhang, X. T. Zhang, Y. M. Zhang, Y. X. Zhang, Y. M. Zhang, Z. J. Zhang, Z. Y. Zhang, Z. P. Zhang, J. Zhao, L. Zhou, H. L. Zhuang, J. H. Zou

The Daya Bay experiment has observed correlations between reactor core fuel evolution and changes in the reactor antineutrino flux and energy spectrum. Four antineutrino detectors in two experimental halls were used to identify 2.2 million inverse beta decays (IBDs) over 1230 days spanning multiple fuel cycles for each of six 2. Read More

Band alignment between solids is a crucial issue in condensed matter physics and electronic devices. Although the XPS method has been used as a routine method for determination of the band alignment, the theoretical calculations by copying the XPS band alignment procedure usually fail to match the measured results. In this work, a reliable ab-initio calculation method for band alignment is proposed on the basis of the XPS procedure and in consideration of surface polarity and lattice deformation. Read More

Global optimization algorithms have shown impressive performance in data-association based multi-object tracking, but handling online data remains a difficult hurdle to overcome. In this paper, we present a hybrid data association framework with a min-cost multi-commodity network flow for robust online multi-object tracking. We build local target-specific models interleaved with global optimization of the optimal data association over multiple video frames. Read More

We present a system for converting a fully panoramic ($360^\circ$) video into a normal field-of-view (NFOV) hyperlapse for an optimal viewing experience. Our system exploits visual saliency and semantics to non-uniformly sample in space and time for generating hyperlapses. In addition, users can optionally choose objects of interest for customizing the hyperlapses. Read More

We introduce a new problem of generating an image based on a small number of key local patches without any geometric prior. In this work, key local patches are defined as informative regions of the target object or scene. This is a challenging problem since it requires generating realistic images and predicting locations of parts at the same time. Read More

Network Function Virtualization (NFV) on Software-Defined Networks (SDN) can effectively optimize the allocation of Virtual Network Functions (VNFs) and the routing of network flows simultaneously. Nevertheless, most previous studies on NFV focus on unicast service chains and thereby are not scalable to support a large number of destinations in multicast. On the other hand, the allocation of VNFs has not been supported in the current SDN multicast routing algorithms. Read More

The effect of the next-nearest-neighbor (nnn) tunneling on the hard-core extended Bose-Hubbard model on square lattices is investigated. By means of the cluster mean-field theory, the ground-state phase diagrams are determined. When a modest nnn tunneling is introduced, depending on its sign, two distinct supersolid states with checkerboard crystal structures are found away from half-filing. Read More

In this paper we are interested in the following nonlinear Choquard equation $$ -\Delta u+(\lambda V(x)-\beta)u =\big(|x|^{-\mu}\ast |u|^{2_{\mu}^{\ast}}\big)|u|^{2_{\mu}^{\ast}-2}u\hspace{4.14mm}\mbox{in}\hspace{1.14mm} \mathbb{R}^N, $$ where $\lambda,\beta\in\mathbb{R}^+$, $0<\muRead More

We prove a new polygamy relation of multi-party quantum entanglement in terms of R\'{e}nyi-$\alpha$ entropy for $\left( {\sqrt 7 - 1} \right)/2\leq\alpha \leq \left( {\sqrt 13 - 1} \right)/2$. This class of polygamy inequality reduces to the polygamy inequality based on entanglement of assistance because R\'{e}nyi-$\alpha$ entanglement is the generalization of entanglement of formation. We further show that the polygamy inequality also holds for the $\mu$th power of R\'{e}nyi-$\alpha$ entanglement of assistance. Read More

This paper presents a collection of experimental results regarding permutation pattern avoidance, focusing on cases where there are "many" patterns to be avoided. Read More

We aim to construct an exceptionally deep (V ~< 27) catalog of variable objects in selected Galactic and extragalactic fields visited multiple times by the Hubble Space Telescope (HST). While HST observations of some of these fields were searched for specific types of variables before (most notably, the extragalactic Cepheids), we attempt a systematic study of the population of variable objects of all types at the magnitude range not easily accessible with ground-based telescopes. The variability timescales that can be probed range from hours to years depending on how often a particular field has been visited. Read More

Recent progresses on deep discriminative and generative modeling have shown promising results on texture synthesis. However, existing feed-forward based methods trade off generality for efficiency, which suffer from many issues, such as shortage of generality (i.e. Read More

2017Feb
Authors: Michael R. Blanton, Matthew A. Bershady, Bela Abolfathi, Franco D. Albareti, Carlos Allende Prieto, Andres Almeida, Javier Alonso-García, Friedrich Anders, Scott F. Anderson, Brett Andrews, Erik Aquino-Ortíz, Alfonso Aragón-Salamanca, Maria Argudo-Fernández, Eric Armengaud, Eric Aubourg, Vladimir Avila-Reese, Carles Badenes, Stephen Bailey, Kathleen A. Barger, Jorge Barrera-Ballesteros, Curtis Bartosz, Dominic Bates, Falk Baumgarten, Julian Bautista, Rachael Beaton, Timothy C. Beers, Francesco Belfiore, Chad F. Bender, Andreas A. Berlind, Mariangela Bernardi, Florian Beutler, Jonathan C. Bird, Dmitry Bizyaev, Guillermo A. Blanc, Michael Blomqvist, Adam S. Bolton, Médéric Boquien, Jura Borissova, Remco van den Bosch, Jo Bovy, William N. Brandt, Jonathan Brinkmann, Joel R. Brownstein, Kevin Bundy, Adam J. Burgasser, Etienne Burtin, Nicolás G. Busca, Michele Cappellari, Maria Leticia Delgado Carigi, Joleen K. Carlberg, Aurelio Carnero Rosell, Ricardo Carrera, Brian Cherinka, Edmond Cheung, Yilen Gómez Maqueo Chew, Cristina Chiappini, Peter Doohyun Choi, Drew Chojnowski, Chia-Hsun Chuang, Haeun Chung, Rafael Fernando Cirolini, Nicolas Clerc, Roger E. Cohen, Johan Comparat, Luiz da Costa, Marie-Claude Cousinou, Kevin Covey, Jeffrey D. Crane, Rupert A. C. Croft, Irene Cruz-Gonzalez, Daniel Garrido Cuadra, Katia Cunha, Guillermo J. Damke, Jeremy Darling, Roger Davies, Kyle Dawson, Axel de la Macorra, Nathan De Lee, Timothée Delubac, Francesco Di Mille, Aleks Diamond-Stanic, Mariana Cano-Díaz, John Donor, Juan José Downes, Niv Drory, Hélion du Mas des Bourboux, Christopher J. Duckworth, Tom Dwelly, Jamie Dyer, Garrett Ebelke, Daniel J. Eisenstein, Eric Emsellem, Mike Eracleous, Stephanie Escoffier, Michael L. Evans, Xiaohui Fan, Emma Fernández-Alvar, J. G. Fernandez-Trincado, Diane K. Feuillet, Alexis Finoguenov, Scott W. Fleming, Andreu Font-Ribera, Alexander Fredrickson, Gordon Freischlad, Peter M. Frinchaboy, Lluís Galbany, R. Garcia-Dias, D. A. García-Hernández, Patrick Gaulme, Doug Geisler, Joseph D. Gelfand, Héctor Gil-Marín, Bruce A. Gillespie, Daniel Goddard, Violeta Gonzalez-Perez, Kathleen Grabowski, Paul J. Green, Catherine J. Grier, James E. Gunn, Hong Guo, Julien Guy, Alex Hagen, ChangHoon Hahn, Matthew Hall, Paul Harding, Sten Hasselquist, Suzanne L. Hawley, Fred Hearty, Jonay I. Gonzalez Hernández, Shirley Ho, David W. Hogg, Kelly Holley-Bockelmann, Jon A. Holtzman, Parker H. Holzer, Joseph Huehnerhoff, Timothy A. Hutchinson, Ho Seong Hwang, Héctor J. Ibarra-Medel, Gabriele da Silva Ilha, Inese I. Ivans, KeShawn Ivory, Kelly Jackson, Trey W. Jensen, Jennifer A. Johnson, Amy Jones, Henrik Jönsson, Eric Jullo, Vikrant Kamble, Karen Kinemuchi, David Kirkby, Francisco-Shu Kitaura, Mark Klaene, Gillian R. Knapp, Jean-Paul Kneib, Juna A. Kollmeier, Ivan Lacerna, Richard R. Lane, Dustin Lang, David R. Law, Daniel Lazarz, Jean-Marc Le Goff, Fu-Heng Liang, Cheng Li, Hongyu LI, Marcos Lima, Lihwai Lin, Yen-Ting Lin, Sara Bertran de Lis, Chao Liu, Miguel Angel C. de Icaza Lizaola, Dan Long, Sara Lucatello, Britt Lundgren, Nicholas K. MacDonald, Alice Deconto Machado, Chelsea L. MacLeod, Suvrath Mahadevan, Marcio Antonio Geimba Maia, Roberto Maiolino, Steven R. Majewski, Elena Malanushenko, Viktor Malanushenko, Arturo Manchado, Shude Mao, Claudia Maraston, Rui Marques-Chaves, Karen L. Masters, Cameron K. McBride, Richard M. McDermid, Brianne McGrath, Ian D. McGreer, Nicolás Medina Peña, Matthew Melendez, Andrea Merloni, Michael R. Merrifield, Szabolcs Meszaros, Andres Meza, Ivan Minchev, Dante Minniti, Takamitsu Miyaji, Surhud More, John Mulchaey, Francisco Müller-Sánchez, Demitri Muna, Ricardo R. Munoz, Adam D. Myers, Preethi Nair, Kirpal Nandra, Janaina Correa do Nascimento, Alenka Negrete, Melissa Ness, Jeffrey A. Newman, Robert C. Nichol, David L. Nidever, Christian Nitschelm, Pierros Ntelis, Julia E. O'Connell, Ryan J. Oelkers, Audrey Oravetz, Daniel Oravetz, Zach Pace, Nelson Padilla, Nathalie Palanque-Delabrouille, Pedro Alonso Palicio, Kaike Pan, Taniya Parikh, Isabelle Pâris, Changbom Park, Alim Y. Patten, Sebastien Peirani, Marcos Pellejero-Ibanez, Samantha Penny, Will J. Percival, Ismael Perez-Fournon, Patrick Petitjean, Matthew M. Pieri, Marc Pinsonneault, Alice Pisani, Radosław Poleski, Francisco Prada, Abhishek Prakash, Anna Bárbara de Andrade Queiroz, M. Jordan Raddick, Anand Raichoor, Sandro Barboza Rembold, Hannah Richstein, Rogemar A. Riffel, Rogério Riffel, Hans-Walter Rix, Annie C. Robin, Constance M. Rockosi, Sergio Rodríguez-Torres, A. Roman-Lopes, Carlos Román-Zúñiga, Margarita Rosado, Ashley J. Ross, Graziano Rossi, John Ruan, Rossana Ruggeri, Eli S. Rykoff, Salvador Salazar-Albornoz, Mara Salvato, Ariel G. Sánchez, David Sánchez Aguado, José R. Sánchez-Gallego, Felipe A. Santana, Basílio Xavier Santiago, Conor Sayres, Ricardo P. Schiavon, Jaderson da Silva Schimoia, Edward F. Schlafly, David J. Schlegel, Donald P. Schneider, Mathias Schultheis, William J. Schuster, Axel Schwope, Hee-Jong Seo, Zhengyi Shao, Shiyin Shen, Matthew Shetrone, Michael Shull, Joshua D. Simon, Danielle Skinner, M. F. Skrutskie, Anže Slosar, Verne V. Smith, Jennifer S. Sobeck, Flavia Sobreira, Garrett Somers, Diogo Souto, David V. Stark, Keivan Stassun, Fritz Stauffer, Matthias Steinmetz, Thaisa Storchi-Bergmann, Alina Streblyanska, Guy S. Stringfellow, Genaro Suárez, Jing Sun, Nao Suzuki, Laszlo Szigeti, Manuchehr Taghizadeh-Popp, Baitian Tang, Charling Tao, Jamie Tayar, Mita Tembe, Johanna Teske, Aniruddha R. Thakar, Daniel Thomas, Benjamin A. Thompson, Jeremy L. Tinker, Patricia Tissera, Rita Tojeiro, Hector Hernandez Toledo, Sylvain de la Torre, Christy Tremonti, Nicholas W. Troup, Octavio Valenzuela, Inma Martinez Valpuesta, Jaime Vargas-González, Mariana Vargas-Magaña, Jose Alberto Vazquez, Sandro Villanova, M. Vivek, Nicole Vogt, David Wake, Rene Walterbos, Yuting Wang, Benjamin Alan Weaver, Anne-Marie Weijmans, David H. Weinberg, Kyle B. Westfall, David G. Whelan, Vivienne Wild, John Wilson, W. M. Wood-Vasey, Dominika Wylezalek, Ting Xiao, Renbin Yan, Meng Yang, Jason E. Ybarra, Christophe Yèche, Nadia Zakamska, Olga Zamora, Pauline Zarrouk, Gail Zasowski, Kai Zhang, Gong-Bo Zhao, Zheng Zheng, Zhi-Min Zhou, Guangtun B. Zhu, Manuela Zoccali, Hu Zou

We describe the Sloan Digital Sky Survey IV (SDSS-IV), a project encompassing three major spectroscopic programs. The Apache Point Observatory Galactic Evolution Experiment 2 (APOGEE-2) is observing hundreds of thousands of Milky Way stars at high resolution and high signal-to-noise ratio in the near-infrared. The Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey is obtaining spatially-resolved spectroscopy for thousands of nearby galaxies (median redshift of z = 0. Read More

The Hubble Catalog of Variables (HCV) is a 3 year ESA funded project that aims to develop a set of algorithms to identify variables among the sources included in the Hubble Source Catalog (HSC) and produce the HCV. We will process all HSC sources with more than a predefined number of measurements in a single filter/instrument combination and compute a range of lightcurve features to determine the variability status of each source. At the end of the project, the first release of the Hubble Catalog of Variables will be made available at the Mikulski Archive for Space Telescopes (MAST) and the ESA Science Archives. Read More

Compositing is one of the most common operations in photo editing. To generate realistic composites, the appearances of foreground and background need to be adjusted to make them compatible. Previous approaches to harmonize composites have focused on learning statistical relationships between hand-crafted appearance features of the foreground and background, which is unreliable especially when the contents in the two layers are vastly different. Read More

This paper addresses the task of designing a modular neural network architecture that jointly solves different tasks. As an example we use the tasks of depth estimation and semantic segmentation given a single RGB image. The main focus of this work is to analyze the cross-modality influence between depth and semantic prediction maps on their joint refinement. Read More

In this paper we are concerned with the following nonlinear Choquard equation $$-\Delta u+V(x)u =\left(\int_{\mathbb{R}^N}\frac{G(y,u)}{|x-y|^{\mu}}dy\right)g(x,u)\hspace{4.14mm}\mbox{in}\hspace{1.14mm} \mathbb{R}^N, $$ where $N\geq4$, $0<\muRead More

2017Feb
Affiliations: 1Fermilab, 2Fermilab, 3Fermilab, 4Fermilab, 5Fermilab, 6Fermilab

The transfer line for beam extraction from the Recycler ring to P1 line provides a way to deliver 8 GeV kinetic energy protons from the Booster to the Delivery ring, via the Recycler, using existing beam transport lines, and without the need for new civil construction. It was designed in 2012. The kicker magnets at RR520 and the lambertson magnet at RR522 in the RR were installed in 2014 Summer Shutdown, the elements of RR to P1 Stub (permanent quads, trim quads, correctors, BPMs, the toroid at 703 and vertical bending dipole at V703 (ADCW) were installed in 2015 Summer Shutdown. Read More

Short-term probabilistic wind power forecasting can provide critical quantified uncertainty information of wind generation for power system operation and control. As the complicated characteristics of wind power prediction error, it would be difficult to develop a universal forecasting model dominating over other alternative models. Therefore, a novel multi-model combination (MMC) approach for short-term probabilistic wind generation forecasting is proposed in this paper to exploit the advantages of different forecasting models. Read More

Recent research has demonstrated that the rotor angle stability can be assessed by identifying the sign of the system maximal Lyapunov exponent (MLE). A positive (negative) MLE implies unstable (stable) rotor angle dynamics. However, because the MLE may fluctuate between positive and negative values for a long time after a severe disturbance, it is difficult to determine the system stability when observing a positive or negative MLE without knowing its further fluctuation trend. Read More

The standard design method for conventional straight dipole magnets is improved in this paper. The good field region is not symmetric with respect to the magnet mechanical center, and its width is not enlarged to include the beam sagitta. The integrated field quality is obtained by integrating the field along nominal beam paths. Read More

In this paper, we propose a new framework for segmenting feature-based moving objects under affine subspace model. Since the feature trajectories in practice are high-dimensional and contain a lot of noise, we firstly apply the sparse PCA to represent the original trajectories with a low-dimensional global subspace, which consists of the orthogonal sparse principal vectors. Subsequently, the local subspace separation will be achieved via automatically searching the sparse representation of the nearest neighbors for each projected data. Read More

The electron-photon interaction in 2D materials obeys the rule of electron valley-photon polarization correspondence. At the quantum level, such correspondence can be utilized to entangle valleys and polarizations and attain the transfer of quantum states (or information) between valley and photon qubits. Our work presents a theoretical study of the interaction between the two types of qubits and the resultant quantum state transfer. Read More

Strong external difference family (SEDF) and its generalizations GSEDF, BGSEDF in a finite abelian group $G$ are combinatorial designs raised by Paterson and Stinson [7] in 2016 and have applications in communication theory to construct optimal strong algebraic manipulation detection codes. In this paper we firstly present some general constructions of these combinatorial designs by using difference sets and partial difference sets in $G$. Then, as applications of the general constructions, we construct series of SEDF, GSEDF and BGSEDF in finite fields by using cyclotomic classes. Read More

The notion of strong external difference family (SEDF) in a finite abelian group $(G,+)$ is raised by M. B. Paterson and D. Read More

In this paper, we attempt to build an unified model with democratic texture, that have some unification between $Y_{\nu}$ and $Y_{u}$. Since the $S_{3L} \times S_{3R}$ flavor symmetry is chiral, the unified gauge group is assumed to be Pati-Salam type $SU(4)_{c} \times SU(2)_{L} \times SU(2)_{R}$. The flavor symmetry breaking scheme is considered to be $S_{3L} \times S_{3R} \to S_{2L} \times S_{2R} \to 0$. Read More

Brain development during adolescence is marked by substantial changes in brain structure and function, leading to a stable network topology in adulthood. However, most prior work has examined the data through the lens of brain areas connected to one another in large-scale functional networks. Here, we apply a recently-developed hypergraph approach that treats network connections (edges) rather than brain regions as the unit of interest, allowing us to describe functional network topology from a fundamentally different perspective. Read More

Visual tracking addresses the problem of identifying and localizing an unknown target in a video given the target specified by a bounding box in the first frame. In this paper, we propose a dual network to better utilize features among layers for visual tracking. It is observed that features in higher layers encode semantic context while its counterparts in lower layers are sensitive to discriminative appearance. Read More

Numerous single-image super-resolution algorithms have been proposed in the literature, but few studies address the problem of performance evaluation based on visual perception. While most super-resolution images are evaluated by fullreference metrics, the effectiveness is not clear and the required ground-truth images are not always available in practice. To address these problems, we conduct human subject studies using a large set of super-resolution images and propose a no-reference metric learned from visual perceptual scores. Read More

The classical multi-set split feasibility problem seeks a point in the intersection of finitely many closed convex domain constraints, whose image under a linear mapping also lies in the intersection of finitely many closed convex range constraints. Split feasibility generalizes important inverse problems including convex feasibility, linear complementarity, and regression with constraint sets. When a feasible point does not exist, solution methods that proceed by minimizing a proximity function can be used to obtain optimal approximate solutions to the problem. Read More

We construct equivalent semi-norms of non-local Dirichlet forms on the Sierpi\'nski gasket and apply these semi-norms to a convergence problem and a trace problem. We also construct explicitly a sequence of non-local Dirichlet forms with jumping kernels equivalent to $|x-y|^{-\alpha-\beta}$ that converges exactly to local Dirichlet form. Read More

The human body is a complex organism whose gross mechanical properties are enabled by an interconnected musculoskeletal network controlled by the nervous system. The nature of musculoskeletal interconnection facilitates stability, voluntary movement, and robustness to injury. However, a fundamental understanding of this network and its control by neural systems has remained elusive. Read More

One of the factors which may limit the intensity in the Fermilab Recycler is a fast transverse instability. It develops within a hundred turns and, in certain conditions, may lead to a beam loss. The high rate of the instability suggest that its cause is electron cloud. Read More

Cross-entropy loss together with softmax is arguably one of the most common used supervision components in convolutional neural networks (CNNs). Despite its simplicity, popularity and excellent performance, the component does not explicitly encourage discriminative learning of features. In this paper, we propose a generalized large-margin softmax (L-Softmax) loss which explicitly encourages intra-class compactness and inter-class separability between learned features. Read More

In this paper, we give the spectrum of a matrix by using the quotient matrix, then we apply this result to various matrices associated to a graph and a digraph, including adjacency matrix, (signless) Laplacian matrix, distance matrix, distance (signless) Laplacian matrix, to obtain some known and new results. Moreover, we propose some problems for further research. Read More

We report on the stability of the quantum Hall plateau in wide Hall bars made from a chemically gated graphene film grown on SiC. The $\nu=2$ quantized plateau appears from fields $B \simeq 5$ T and persists up to $B \simeq 80$ T. At high current density, in the breakdown regime, the longitudinal resistance oscillates with a $1/B$ periodicity and an anomalous phase, which we relate to the presence of additional electron reservoirs. Read More

Random numbers are indispensable for a variety of applications ranging from testing physics foundation to information encryption. In particular, nonlocality tests provide a strong evidence to our current understanding of nature -- quantum mechanics. All the random number generators (RNG) used for the existing tests are constructed locally, making the test results vulnerable to the freedom-of-choice loophole. Read More

In this paper, we propose a fully convolutional networks for iterative non-blind deconvolution We decompose the non-blind deconvolution problem into image denoising and image deconvolution. We train a FCNN to remove noises in the gradient domain and use the learned gradients to guide the image deconvolution step. In contrast to the existing deep neural network based methods, we iteratively deconvolve the blurred images in a multi-stage framework. Read More