11,047 research outputs found
Measuring the saturation scale in nuclei
The saturation momentum seeing in the nuclear infinite momentum frame is
directly related to transverse momentum broadening of partons propagating
through the medium in the nuclear rest frame. Calculation of broadening within
the color dipole approach including the effects of saturation in the nucleus,
gives rise to an equation which describes well data on broadening in Drell-Yan
reaction and heavy quarkonium production.Comment: 11 pages, 5 figures, based on the talk presented by B.K. at the INT
workshop "Physics at a High Energy Electron Ion Collider", Seattle, October
200
Giant microwave-induced -periodic magnetoresistance oscillations in a two-dimensional electron gas with a bridged-gate tunnel point contact
We have studied the magnetoresistance of the quantum point contact fabricated
on the high mobility two-dimensional electron gas (2DEG) exposed to microwave
irradiation. The resistance reveals giant -periodic oscillations with the
relative amplitude of up to \% resulting from the propagation
and interference of the edge magnetoplasmons (EMPs) in the sample. This giant
photoconductance is attributed to the considerably large local electron density
modulation in the vicinity of the point contact. We have also analyzed the
oscillation periods of the resistance oscillations and, comparing
the data with the EMP theory, extracted the EMP interference length . We
have found that the length substantially exceeds the distance between the
contact leads but rather corresponds to the distance between metallic contact
pads measured along the edge of the 2DEG. This resolves existing controversy in
the literature and should help to properly design highly sensitive microwave
and terahertz spectrometers based on the discussed effect.Comment: 5 pages, 5 figure
Stereo Computation for a Single Mixture Image
This paper proposes an original problem of \emph{stereo computation from a
single mixture image}-- a challenging problem that had not been researched
before. The goal is to separate (\ie, unmix) a single mixture image into two
constitute image layers, such that the two layers form a left-right stereo
image pair, from which a valid disparity map can be recovered. This is a
severely illposed problem, from one input image one effectively aims to recover
three (\ie, left image, right image and a disparity map). In this work we give
a novel deep-learning based solution, by jointly solving the two subtasks of
image layer separation as well as stereo matching. Training our deep net is a
simple task, as it does not need to have disparity maps. Extensive experiments
demonstrate the efficacy of our method.Comment: Accepted by European Conference on Computer Vision (ECCV) 201
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