15,502 research outputs found
Electron multipacting in long-bunch beam
The electron multipacting is an important factor for the development of the
electron cloud. There is a trailing-edge multipacting in the tail of the
long-bunch beam. It can be described by the energy gain and motion of
electrons. The analyses are in agreement with the simulation
EDA: Easy Data Augmentation Techniques for Boosting Performance on Text Classification Tasks
We present EDA: easy data augmentation techniques for boosting performance on
text classification tasks. EDA consists of four simple but powerful operations:
synonym replacement, random insertion, random swap, and random deletion. On
five text classification tasks, we show that EDA improves performance for both
convolutional and recurrent neural networks. EDA demonstrates particularly
strong results for smaller datasets; on average, across five datasets, training
with EDA while using only 50% of the available training set achieved the same
accuracy as normal training with all available data. We also performed
extensive ablation studies and suggest parameters for practical use.Comment: EMNLP-IJCNLP 2019 short pape
A finite element method of the self-consistent field theory on general curved surfaces
Block copolymers provide a wonderful platform in studying the soft condensed
matter systems. Many fascinating ordered structures have been discovered in
bulk and confined systems. Among various theories, the self-consistent field
theory (SCFT) has been proven to be a powerful tool for studying the
equilibrium ordered structures. Many numerical methods have been developed to
solve the SCFT model. However, most of these focus on the bulk systems, and
little work on the confined systems, especially on general curved surfaces. In
this work, we developed a linear surface finite element method, which has a
rigorous mathematical theory to guarantee numerical precsion, to study the
self-assembled phases of block copolymers on general curved surfaces based on
the SCFT. Furthermore, to capture the consistent surface for a given
self-assembled pattern, an adaptive approach to optimize the size of the
general curved surface has been proposed. To demonstrate the power of this
approach, we investigate the self-assembled patterns of diblock copolymers on
several distinct curved surfaces, including five closed surfaces and an
unclosed surface. Numerical results illustrate the efficiency of the proposed
method. The obtained ordered structures are consistent with the previous
results on standard surfaces, such as sphere and torus. Certainly, the proposed
numerical framework has the capability of studying the phase behaviors on
general surfaces precisely
Topological defects in two-dimensional crystals
By using topological current theory, we study the inner topological structure
of the topological defects in two-dimensional (2D) crystal. We find that there
are two elementary point defects topological current in two-dimensional
crystal, one for dislocations and the other for disclinations. The topological
quantization and evolution of topological defects in two-dimensional crystals
are discussed. Finally, We compare our theory with Brownian-dynamics
simulations in 2D Yukawa systems.Comment: 4 pages, 2 figure
Topological dynamics and dynamical scaling behavior of vortices in a two-dimensional XY model
By using topological current theory we study the inner topological structure
of vortices a two-dimensional (2D) XY model and find the topological current
relating to the order parameter field. A scalar field, , is introduced
through the topological current theory. By solving the scalar field, the
interaction energy of vortices in a 2D XY model is revisited. We study the
dynamical evolution of vortices and present the branch conditions for
generating, annihilating, crossing, splitting and merging of vortices. During
the growth or annihilation of vortices, the dynamical scaling law of relevant
length in a 2D XY model, , is obtained in the
neighborhood of the limit point, given the dynamic exponent . This
dynamical scaling behavior is consistent with renormalization group theory,
numerical simulations, and experimental results. Furthermore, it is found that
during the crossing, splitting and merging of vortices, the dynamical scaling
law of relevant length is . However, if vortices are at
rest during splitting or merging, the dynamical scaling law of relevant length
is a constat.Comment: 10 pages, 5 figures. any comments are favore
Testing the Cosmic Anisotropy with Supernovae Data: Hemisphere Comparison and Dipole Fitting
The cosmological principle is one of the cornerstones in modern cosmology. It
assumes that the universe is homogeneous and isotropic on cosmic scales. Both
the homogeneity and the isotropy of the universe should be tested carefully. In
the present work, we are interested in probing the possible preferred direction
in the distribution of type Ia supernovae (SNIa). To our best knowledge, two
main methods have been used in almost all of the relevant works in the
literature, namely the hemisphere comparison (HC) method and the dipole fitting
(DF) method. However, the results from these two methods are not always
approximately coincident with each other. In this work, we test the cosmic
anisotropy by using these two methods with the Joint Light-Curve Analysis (JLA)
and simulated SNIa datasets. In many cases, both methods work well, and their
results are consistent with each other. However, in the cases with two (or even
more) preferred directions, the DF method fails while the HC method still works
well. This might shed new light on our understanding of these two methods.Comment: 18 pages, 10 figures, 1 table, revtex4; v2: title changed,
discussions added, Phys. Rev. D in press; v3: published versio
Distributed Block-diagonal Approximation Methods for Regularized Empirical Risk Minimization
In recent years, there is a growing need to train machine learning models on
a huge volume of data. Designing efficient distributed optimization algorithms
for empirical risk minimization (ERM) has therefore become an active and
challenging research topic. In this paper, we propose a flexible framework for
distributed ERM training through solving the dual problem, which provides a
unified description and comparison of existing methods. Our approach requires
only approximate solutions of the sub-problems involved in the optimization
process, and is versatile to be applied on many large-scale machine learning
problems including classification, regression, and structured prediction. We
show that our approach enjoys global linear convergence for a broader class of
problems, and achieves faster empirical performance, compared with existing
works
The anomalous antiferromagnetic topological phase in pressurized SmB6
Antiferromagnetic materials, whose time-reversal symmetry is broken, can be
classified into the Z2 topology if they respect some specific symmetry. Since
the theoretical proposal, however, no materials have been found to host the
antiferromagnetic topological (AFT) phase to date. Here, for the first time, we
demonstrate that the topological Kondo insulator SmB6 can be an AFT system when
pressurized to undergo an antiferromagnetic phase transition. In addition to
propose the possible candidate for an AFT material, in this work we also
illustrate the anomalous topological surface states of the AFT phase which has
not been discussed before. Originating from the interplay between the
topological properties and the antiferromagnetic surface magnetization, the
topological surface states of the AFT phase behave differently as compared with
those of a topological insulator. Besides, the AFT insulators are also found
promising in the generation of tunable spin currents, which is an important
application in spintronics
Continuous-Scale Kinetic Fluid Simulation
Kinetic approaches, i.e., methods based on the lattice Boltzmann equations,
have long been recognized as an appealing alternative for solving
incompressible Navier-Stokes equations in computational fluid dynamics.
However, such approaches have not been widely adopted in graphics mainly due to
the underlying inaccuracy, instability and inflexibility. In this paper, we try
to tackle these problems in order to make kinetic approaches practical for
graphical applications. To achieve more accurate and stable simulations, we
propose to employ the non-orthogonal central-moment-relaxation model, where we
develop a novel adaptive relaxation method to retain both stability and
accuracy in turbulent flows. To achieve flexibility, we propose a novel
continuous-scale formulation that enables samples at arbitrary resolutions to
easily communicate with each other in a more continuous sense and with loose
geometrical constraints, which allows efficient and adaptive sample
construction to better match the physical scale. Such a capability directly
leads to an automatic sample construction which generates static and dynamic
scales at initialization and during simulation, respectively. This effectively
makes our method suitable for simulating turbulent flows with arbitrary
geometrical boundaries. Our simulation results with applications to smoke
animations show the benefits of our method, with comparisons for justification
and verification.Comment: 17 pages, 17 figures, accepted by IEEE Transactions on Visualization
and Computer Graphic
Optimal Puncturing of Polar Codes With a Fixed Information Set
For a given polar code construction, the existing literature on puncturing
for polar codes focuses in finding the optimal puncturing pattern, and then
re-selecting the information set. This paper devotes itself to find the optimal
puncturing pattern when the information set is fixed. Puncturing the coded bits
corresponding to the worst quality bit channels, called the worst quality
puncturing (WQP), is proposed, which is analyzed to minimize the bit channel
quality loss at the punctured positions. Simulation results show that WQP
outperforms the best existing puncturing schemes when the information set is
fixed.Comment: Polar codes, puncture, quasi-uniform puncturing,worst quality
puncturin
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