23,783 research outputs found
X-ray cavities in the hot corona of the lenticular galaxy NGC~4477
NGC 4477 is a low-mass lenticular galaxy in the Virgo Cluster, residing at
100\,kpc to the north of M87. Using a total of 116\,ks {\sl Chandra}
observations, we study the interplay between its hot (0.3\,keV) gas halo
and the central supermassive black hole. A possible cool core is indicated by
the short cooling time of the gas at the galaxy centre. We identify a pair of
symmetric cavities lying 1.1\,kpc southeast and 0.9\,kpc northwest of the
galaxy centre with diameters of 1.3\,kpc and 0.9\,kpc, respectively. We
estimate that these cavities are newly formed with an age of 4\,Myr. No
radio emission is detected at the positions of the cavities with the existing
VLA data. The total energy required to produce the two cavities is
\,erg, at least two orders of magnitude smaller than that of
typical X-ray cavities. NGC 4477 is arguably far the smallest system and the
only lenticular galaxy in which AGN X-ray cavities have been found. It falls on
the scaling relation between the cavity power and the AGN radio luminosity,
calibrated for groups and clusters. Our findings suggest that AGN feedback is
universal among all cool core systems. Finally, we note the presence of
molecular gas in NGC~4477 in the shape of a regular disk with ordered rotation,
which may not be related to the feedback loop.Comment: 9 pages, 9 figures, accepted for publication in MNRA
Joint Channel Assignment and Opportunistic Routing for Maximizing Throughput in Cognitive Radio Networks
In this paper, we consider the joint opportunistic routing and channel
assignment problem in multi-channel multi-radio (MCMR) cognitive radio networks
(CRNs) for improving aggregate throughput of the secondary users. We first
present the nonlinear programming optimization model for this joint problem,
taking into account the feature of CRNs-channel uncertainty. Then considering
the queue state of a node, we propose a new scheme to select proper forwarding
candidates for opportunistic routing. Furthermore, a new algorithm for
calculating the forwarding probability of any packet at a node is proposed,
which is used to calculate how many packets a forwarder should send, so that
the duplicate transmission can be reduced compared with MAC-independent
opportunistic routing & encoding (MORE) [11]. Our numerical results show that
the proposed scheme performs significantly better that traditional routing and
opportunistic routing in which channel assignment strategy is employed.Comment: 5 pages, 4 figures, to appear in Proc. of IEEE GlobeCom 201
The -spectral radius of graphs with given degree sequence
Let be a graph with adjacency matrix , and let be the
diagonal matrix of the degrees of . For any real , write
for the matrix This
paper presents some extremal results about the spectral radius
of that generalize previous results about
and . In this paper, we give some
results on graph perturbation for -matrix with . As
applications, we characterize all extremal trees with the maximum
-spectral radius in the set of all trees with prescribed degree
sequence firstly. Furthermore, we characterize the unicyclic graphs that have
the largest -spectral radius for a given unicycilc degree sequence
Boundary H\"{o}lder Regularity for Elliptic Equations
This paper investigates the relation between the boundary geometric
properties and the boundary regularity of the solutions of elliptic equations.
We prove by a new unified method the pointwise boundary H\"{o}lder regularity
under proper geometric conditions. "Unified" means that our method is
applicable for the Laplace equation, linear elliptic equations in divergence
and non-divergence form, fully nonlinear elliptic equations, the Laplace
equations and the fractional Laplace equations etc. In addition, these
geometric conditions are quite general. In particular, for local equations, the
measure of the complement of the domain near the boundary point concerned could
be zero. The key observation in the method is that the strong maximum principle
implies a decay for the solution, then a scaling argument leads to the
H\"{o}lder regularity. Moreover, we also give a geometric condition, which
guarantees the solvability of the Dirichlet problem for the Laplace equation.
The geometric meaning of this condition is more apparent than that of the
Wiener criterion.Comment: to appear in Journal de Math\'ematiques Pures et Appliqu\'ee
Improvement of the matching of the exact solution and variational approaches in an interacting two-fermion system
A more reasonable trial ground state wave function is constructed for the
relative motion of an interacting two-fermion system in a 1D harmonic
potential. At the boundaries both the wave function and its first derivative
are continuous and the quasi-momentum is determined by a more practical
constraint condition which associates two variational parameters. The upper
bound of the ground state energy is obtained by applying the variational
principle to the expectation value of the Hamiltonian of relative motion on the
trial wave function. The resulted energy and wave function show better
agreement with the analytical solution than the original proposal.Comment: 5 pages, 3 figures, submitted to PR
Pointwise densities of homogeneous Cantor measure and critical values
Let and . The homogenous Cantor set is the
self-similar set generated by the iterated function system
Let be the Hausdorff dimension of , and let be the -dimensional Hausdorff measure restricted to . In this
paper we describe, for each , the pointwise lower -density
and upper -density of at
. This extends some early results of Feng et al. (2000). Furthermore, we
determine two critical values and for the sets
respectively, such that if and only if , and that
if and only if . We emphasize that both values
and are related to the Thue-Morse type sequences, and our strategy to
find them relies on ideas from open dynamics and techniques from combinatorics
on words.Comment: 30 pages, 1 figure and 1 tabl
Semi-groups of stochastic gradient descent and online principal component analysis: properties and diffusion approximations
We study the Markov semigroups for two important algorithms from machine
learning: stochastic gradient descent (SGD) and online principal component
analysis (PCA). We investigate the effects of small jumps on the properties of
the semi-groups. Properties including regularity preserving,
contraction are discussed. These semigroups are the dual of the semigroups for
evolution of probability, while the latter are contracting and
positivity preserving. Using these properties, we show that stochastic
differential equations (SDEs) in (on the sphere
) can be used to approximate SGD (online PCA) weakly. These
SDEs may be used to provide some insights of the behaviors of these algorithms
The convexity of inclusions and gradient's concentration for Lam\'e systems with partially infinite coefficients
It is interesting to study the stress concentration between two adjacent
stiff inclusions in composite materials, which can be modeled by the Lam\'e
system with partially infinite coefficients. To overcome the difficulty from
the lack of maximum principle for elliptic systems, we use the energy method
and an iteration technique to study the gradient estimates of the solution. We
first find a novel phenomenon that the gradient will not blow up any more once
these two adjacent inclusions fail to be locally relatively strictly convex,
namely, the top and bottom boundaries of the narrow region are partially
"flat". This is contrary to our expectation. In order to further explore the
blow-up mechanism of the gradient, we next investigate two adjacent inclusions
with relative convexity of order m and finally reveal an underlying
relationship between the blow-up rate of the stress and the order of the
relative convexity of the subdomains in all dimensions.Comment: 61 page
Self-Attention Recurrent Network for Saliency Detection
Feature maps in deep neural network generally contain different semantics.
Existing methods often omit their characteristics that may lead to sub-optimal
results. In this paper, we propose a novel end-to-end deep saliency network
which could effectively utilize multi-scale feature maps according to their
characteristics. Shallow layers often contain more local information, and deep
layers have advantages in global semantics. Therefore, the network generates
elaborate saliency maps by enhancing local and global information of feature
maps in different layers. On one hand, local information of shallow layers is
enhanced by a recurrent structure which shared convolution kernel at different
time steps. On the other hand, global information of deep layers is utilized by
a self-attention module, which generates different attention weights for
salient objects and backgrounds thus achieve better performance. Experimental
results on four widely used datasets demonstrate that our method has advantages
in performance over existing algorithms
Center and isochronous center of a class of quasi-analytic switching systems
In this paper, we study the integrability and linearization of a class of
quadratic quasi-analytic switching systems. We improve an existing method to
compute the focus values and periodic constants of quasi-analytic switching
systems. In particular, with our method, we demonstrate that the dynamical
behaviors of quasi-analytic switching systems are more complex than that of
continuous quasi-analytic systems, by showing the existence of six and seven
limit cycles in the neighborhood of the origin and infinity, respectively, in a
quadratic quasi-analytic switching system. Moreover, explicit conditions are
obtained for classifying the centers and isochronous centers of the system.Comment: 24 pages, 3 figure
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