35,618 research outputs found
Dynamics of ultra-intense circularly polarized solitons under inhomogeneous plasmas
The dynamics of the ultra-intense circularly polarized solitons under
inhomogeneous plasmas are examined. The interaction is modeled by the Maxwell
and relativistic hydrodynamic equations and is solved with fully implicit
energy-conserving numerical scheme. It is shown that a propagating weak soliton
can be decreased and reflected by increasing plasma background, which is
consistent with the existing studies based on hypothesis of weak density
response. However it is found that ultra-intense soliton is well trapped and
kept still when encountering increasing background. Probably, this founding can
be applied for trapping and amplifying high-intensity laser-fields.Comment: 4 pages, 3 figures, submitted to Phys. Plasma
Quantum criticality and nodal superconductivity in the FeAs-based superconductor KFe2As2
The in-plane resistivity and thermal conductivity of
FeAs-based superconductor KFeAs single crystal were measured down to 50
mK. We observe non-Fermi-liquid behavior at =
5 T, and the development of a Fermi liquid state with when
further increasing field. This suggests a field-induced quantum critical point,
occurring at the superconducting upper critical field . In zero field
there is a large residual linear term , and the field dependence of
mimics that in d-wave cuprate superconductors. This indicates that
the superconducting gaps in KFeAs have nodes, likely d-wave symmetry.
Such a nodal superconductivity is attributed to the antiferromagnetic spin
fluctuations near the quantum critical point.Comment: 4 pages, 4 figures - replaces arXiv:0909.485
Suppressing longitudinal double-layer oscillations by using elliptically polarized laser pulses in the hole-boring radiation pressure acceleration regime
It is shown that well collimated mono-energetic ion beams with a large
particle number can be generated in the hole-boring radiation pressure
acceleration regime by using an elliptically polarized laser pulse with
appropriate theoretically determined laser polarization ratio. Due to the
effect, the double-layer charge separation region is
imbued with hot electrons that prevent ion pileup, thus suppressing the
double-layer oscillations. The proposed mechanism is well confirmed by
Particle-in-Cell simulations, and after suppressing the longitudinal
double-layer oscillations, the ion beams driven by the elliptically polarized
lasers own much better energy spectrum than those by circularly polarized
lasers.Comment: 6 pages, 5 figures, Phys. Plasmas (2013) accepte
Nodeless superconductivity in Ca3Ir4Sn13: evidence from quasiparticle heat transport
We report resistivity and thermal conductivity measurements
on CaIrSn single crystals, in which superconductivity with K was claimed to coexist with ferromagnetic spin-fluctuations. Among
three crystals, only one crystal shows a small hump in resistivity near 20 K,
which was previously attributed to the ferromagnetic spin-fluctuations. Other
two crystals show the Fermi-liquid behavior at low temperature.
For both single crystals with and without the resistivity anomaly, the residual
linear term is negligible in zero magnetic field. In low fields,
shows a slow field dependence. These results demonstrate that
the superconducting gap of CaIrSn is nodeless, thus rule out
nodal gap caused by ferromagnetic spin-fluctuations.Comment: 5 pages, 4 figure
network pruning via transformable architecture search
Network pruning reduces the computation costs of an over-parameterized
network without performance damage. Prevailing pruning algorithms pre-define
the width and depth of the pruned networks, and then transfer parameters from
the unpruned network to pruned networks. To break the structure limitation of
the pruned networks, we propose to apply neural architecture search to search
directly for a network with flexible channel and layer sizes. The number of the
channels/layers is learned by minimizing the loss of the pruned networks. The
feature map of the pruned network is an aggregation of K feature map fragments
(generated by K networks of different sizes), which are sampled based on the
probability distribution.The loss can be back-propagated not only to the
network weights, but also to the parameterized distribution to explicitly tune
the size of the channels/layers. Specifically, we apply channel-wise
interpolation to keep the feature map with different channel sizes aligned in
the aggregation procedure. The maximum probability for the size in each
distribution serves as the width and depth of the pruned network, whose
parameters are learned by knowledge transfer, e.g., knowledge distillation,
from the original networks. Experiments on CIFAR-10, CIFAR-100 and ImageNet
demonstrate the effectiveness of our new perspective of network pruning
compared to traditional network pruning algorithms. Various searching and
knowledge transfer approaches are conducted to show the effectiveness of the
two components. Code is at: https://github.com/D-X-Y/NAS-Projects.Comment: Published in the 33rd Conference on Neural Information Processing
Systems (NeurIPS 2019
Phase equilibrium in two orbital model under magnetic field
The phase equilibrium in manganites under magnetic field is studied using a
two orbital model, based on the equivalent chemical potential principle for the
competitive phases. We focus on the magnetic field induced melting process of
CE phase in half-doped manganites. It is predicted that the homogenous CE phase
begins to decompose into coexisting ferromagnetic phase and CE phase once the
magnetic field exceeds the threshold field. In a more quantitative way, the
volume fractions of the two competitive phases in the phase separation regime
are evaluated.Comment: 4 pages, 4 figure
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