9,998 research outputs found
Tight Bounds for Maximal Identifiability of Failure Nodes in Boolean Network Tomography
We study maximal identifiability, a measure recently introduced in Boolean
Network Tomography to characterize networks' capability to localize failure
nodes in end-to-end path measurements. We prove tight upper and lower bounds on
the maximal identifiability of failure nodes for specific classes of network
topologies, such as trees and -dimensional grids, in both directed and
undirected cases. We prove that directed -dimensional grids with support
have maximal identifiability using monitors; and in the
undirected case we show that monitors suffice to get identifiability of
. We then study identifiability under embeddings: we establish relations
between maximal identifiability, embeddability and graph dimension when network
topologies are model as DAGs. Our results suggest the design of networks over
nodes with maximal identifiability using
monitors and a heuristic to boost maximal identifiability on a given network by
simulating -dimensional grids. We provide positive evidence of this
heuristic through data extracted by exact computation of maximal
identifiability on examples of small real networks
Timelike duality, -theory and an exotic form of the Englert solution
Through timelike dualities, one can generate exotic versions of -theory
with different spacetime signatures. These are the -theory with signature
, the -theory, with signature and the theories with
reversed signatures , and . In ,
is the number of space directions, the number of time directions, and
refers to the sign of the kinetic term of the form.
The only irreducible pseudo-riemannian manifolds admitting absolute
parallelism are, besides Lie groups, the seven-sphere
and its pseudo-riemannian version . [There is
also the complexification , but it is of
dimension too high for our considerations.] The seven-sphere has been found to play an important role in -dimensional
supergravity, both through the Freund-Rubin solution and the Englert solution
that uses its remarkable parallelizability to turn on non trivial internal
fluxes. The spacetime manifold is in both cases . We show
that enjoys a similar role in -theory and construct the exotic
form of the Englert solution, with non zero internal
fluxes turned on. There is no analogous solution in -theory.Comment: 18 pages, v2: typos fixe
Conformal field theories from deformations of theories with symmetry
We construct a set of non-rational conformal field theories that consist of
deformations of Toda field theory for sl(n). Besides conformal invariance, the
theories still enjoy a remnant infinite-dimensional affine symmetry. The case
n=3 is used to illustrate this phenomenon, together with further deformations
that yield enhanced Kac-Moody symmetry algebras. For generic n we compute
N-point correlation functions on the Riemann sphere and show that these can be
expressed in terms of sl(n) Toda field theory correlation functions.Comment: 27 pages. Typos corrected. Discussion adde
Screening Stringy Horizons
It has been argued recently that string theory effects qualitatively modify
the effective black hole geometry experienced by modes with radial momentum of
order . At tree level, these -effects can be
explicitly worked out in two-dimensional string theory, and have a natural
explanation in the T-dual description as coming from the integration of the
zero-mode of the linear dilaton, what yields a contribution that affects the
scattering phase-shift in a peculiar manner. It has also been argued that the
phase-shift modification has its origin in a region of the moduli space that
does not belong to the exterior black hole geometry, leading to the conclusion
that at high energy the physics of the problem is better described by the dual
model. Here, we elaborate on this argument. We consider the contribution of
worldsheet instantons in the 2D Euclidean black hole sigma-model and study its
influence on the phase-shift at high energy.Comment: 14 page
Can you tell a face from a HEVC bitstream?
Image and video analytics are being increasingly used on a massive scale. Not
only is the amount of data growing, but the complexity of the data processing
pipelines is also increasing, thereby exacerbating the problem. It is becoming
increasingly important to save computational resources wherever possible. We
focus on one of the poster problems of visual analytics -- face detection --
and approach the issue of reducing the computation by asking: Is it possible to
detect a face without full image reconstruction from the High Efficiency Video
Coding (HEVC) bitstream? We demonstrate that this is indeed possible, with
accuracy comparable to conventional face detection, by training a Convolutional
Neural Network on the output of the HEVC entropy decoder
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