12,666 research outputs found
Quasinormal Modes of Self-Dual Warped AdS Black Hole in Topological Massive Gravity
We consider the various perturbations of self-dual warped AdS black hole
and obtain the exact expressions of quasinormal modes by imposing the vanishing
Dirichlet boundary condition at asymptotic infinity. It is expected that the
quasinormal modes agree with the poles of retarded Green's functions of the
dual CFT. Our results provide a quantitative test of the warped AdS/CFT
correspondence.Comment: 10 pages, no figure, some references and comments on gravitational
perturbations are adde
Bootstrapping Vector Models in
We use the conformal bootstrap to study conformal field theories with
global symmetry in and spacetime dimensions that have a scalar
operator transforming as an vector. The crossing symmetry of
the four-point function of this vector operator, along with unitarity
assumptions, determine constraints on the scaling dimensions of conformal
primary operators in the OPE. Imposing a lower bound on
the second smallest scaling dimension of such an -singlet conformal
primary, and varying the scaling dimension of the lowest one, we obtain an
allowed region that exhibits a kink located very close to the interacting
-symmetric CFT conjectured to exist recently by Fei, Giombi, and
Klebanov. Under reasonable assumptions on the dimension of the second lowest
singlet in the OPE, we observe that this kink
disappears in for small enough , suggesting that in this case an
interacting CFT may cease to exist for below a certain critical
value.Comment: 24 pages, 5 figures; v2 minor improvement
Siamese Instance Search for Tracking
In this paper we present a tracker, which is radically different from
state-of-the-art trackers: we apply no model updating, no occlusion detection,
no combination of trackers, no geometric matching, and still deliver
state-of-the-art tracking performance, as demonstrated on the popular online
tracking benchmark (OTB) and six very challenging YouTube videos. The presented
tracker simply matches the initial patch of the target in the first frame with
candidates in a new frame and returns the most similar patch by a learned
matching function. The strength of the matching function comes from being
extensively trained generically, i.e., without any data of the target, using a
Siamese deep neural network, which we design for tracking. Once learned, the
matching function is used as is, without any adapting, to track previously
unseen targets. It turns out that the learned matching function is so powerful
that a simple tracker built upon it, coined Siamese INstance search Tracker,
SINT, which only uses the original observation of the target from the first
frame, suffices to reach state-of-the-art performance. Further, we show the
proposed tracker even allows for target re-identification after the target was
absent for a complete video shot.Comment: This paper is accepted to the IEEE Conference on Computer Vision and
Pattern Recognition, 201
Measuring the energy handling capability of metal oxide varistors
Metal oxide varistors are widely used in many power electronics circuits to protect against transient over voltages. Certain applications are very demanding on the energy handling capability of the varistors. This paper gives an overview of the failure modes of ZnO varistors and investigates their characteristics when subjected to repetitive current pulses. It describes the puncture failure mode caused by melting of a region in the varistor of local current concentration. Experimental tests are performed to evaluate the puncture energy using an infrared imaging camera. A relationship between the energy absorption and the varistor maximum surface temperature is obtained. It is shown that the destructive energy depends strongly on the uniformity of the varistor; the more uniform, the higher the energy handling capability. The paper also presents the results of nondestructive tests using a scanning acoustic microscope to evaluate the uniformity of the varistor
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