17,227 research outputs found
Momentum-resolved radio-frequency spectroscopy of a spin-orbit coupled atomic Fermi gas near a Feshbach resonance in harmonic traps
We theoretically investigate the momentum-resolved radio-frequency
spectroscopy of a harmonically trapped atomic Fermi gas near a Feshbach
resonance in the presence of equal Rashba and Dresselhaus spin-orbit coupling.
The system is qualitatively modeled as an ideal gas mixture of atoms and
molecules, in which the properties of molecules, such as the wavefunction,
binding energy and effective mass, are determined from the two-particle
solution of two-interacting atoms. We calculate separately the radio-frequency
response from atoms and molecules at finite temperatures by using the standard
Fermi golden rule, and take into account the effect of harmonic traps within
local density approximation. The total radio-frequency spectroscopy is
discussed, as functions of temperature and spin-orbit coupling strength. Our
results give a qualitative picture of radio-frequency spectroscopy of a
resonantly interacting spin-orbit coupled Fermi gas and can be directly tested
in atomic Fermi gases of K40 atoms at Shanxi University and of Li6 atoms at
MIT.Comment: 11 pages, 9 Figure
Two-channel model description of confinement-induced Feshbach molecules
Using a two-channel model, we investigate theoretically the binding energy of
confinement-induced Feshbach molecules in two- and one-dimensional ultracold
atomic systems, near a Feshbach resonance. We show that the two-channel
prediction will evidently deviate from the simple single-channel theory as the
width of Feshbach resonances decreases. For one-dimensional system, we perform
a full two-channel calculation, with the inclusion of bare interatomic
interactions in the open channel. Away from the resonance, we find a sizable
correction to the binding energy, if we neglect incorrectly the bare
interatomic interactions as in the previous work [Dickerscheid and Stoof, Phys.
Rev. A 72, 053625 (2005)]. We compare our theoretical results with existing
experimental data and present predictions for narrow Feshbach resonances that
could be tested in future experiments.Comment: 8 pages, 5 figure
Radio-frequency spectroscopy of weakly bound molecules in spin-orbit coupled atomic Fermi gases
We investigate theoretically radio-frequency spectroscopy of weakly bound
molecules in an ultracold spin-orbit-coupled atomic Fermi gas. We consider two
cases with either equal Rashba and Dresselhaus coupling or pure Rashba
coupling. The former system has been realized very recently at Shanxi
University [Wang et al., arXiv:1204.1887] and MIT [Cheuk et al.,
arXiv:1205.3483]. We predict realistic radio-frequency signals for revealing
the unique properties of anisotropic molecules formed by spin-orbit coupling.Comment: 11 pages, 7 figure
Angular Stripe Phase in Spin-Orbital-Angular-Momentum Coupled Bose Condensates
We propose that novel superfluid with supersolid-like properties - angular
stripe phase - can be realized in a pancake-like spin-1/2 Bose gas with
spin-orbital-angular-momentum coupling. We predict a rich ground-state phase
diagram, including the vortex-antivortex pair phase, half-skyrmion phase, and
two different angular stripe phases. The stripe phases feature modulated
angular density-density correlation with sizable contrast and can occupy a
relatively large parameter space. The low-lying collective excitations, such as
the dipole and breathing modes, show distinct behaviors in different phases.
The existence of the novel stripe phase is also clearly indicated in the
energetic and dynamic instabilities of collective modes near phase transitions.
Our predictions of the angular stripe phase could be readily examined in
current cold-atom experiments with Rb and K.Comment: 5+3 pages, 4+2 figure
Confinement-induced resonance in quasi-one-dimensional systems under transversely anisotropic confinement
We theoretically investigate the confinement-induced resonance for
quasi-one-dimensional quan- tum systems under transversely anisotropic
confinement, using a two-body s-wave scattering model in the zero-energy
collision limit. We predict a single resonance for any transverse anisotropy,
whose position shows a slight downshift with increasing anisotropy. We compare
our prediction with the recent experimental result by Haller et al. [Phys. Rev.
Lett. 104, 153203 (2010)], in which two resonances are observed in the presence
of transverse anisotropy. The discrepancy between theory and experiment remains
to be resolved.Comment: 6 pages, 5 figures, accepted for publication in Phys. Rev.
An electron acceptor molecule in a nanomesh: F4TCNQ on h-BN/Rh(111)
The adsorption of molecules on surfaces affects the surface dipole and thus
changes in the work function may be expected. The effect in change of work
function is particularly strong if charge between substrate and adsorbate is
involved. Here we report the deposition of a strong electron acceptor molecule,
tetrafluorotetracyanoquinodimethane CFN (FTCNQ) on a
monolayer of hexagonal boron nitride nanomesh (-BN on Rh(111)). The work
function of the FTCNQ/-BN/Rh system increases upon increasing
molecular coverage. The magnitude of the effect indicates electron transfer
from the substrate to the FTCNQ molecules. Density functional theory
calculations confirm the work function shift and predict doubly charged
FTCNQ in the nanomesh pores, where the -BN is closest to the Rh
substrate, and to have the largest binding energy there. The preferred
adsorption in the pores is conjectured from a series of ultraviolet
photoelectron spectroscopy data, where the bands in the pores are
first attenuated. Scanning tunneling microscopy measurements indicate that
FTCNQ molecules on the nanomesh are mobile at room temperature, as
"hopping" between neighboring pores is observed
Distributed state estimation for uncertain Markov-type sensor networks with mode-dependent distributed delays
This the post-print version of the Article. The official published version can be accessed from the link below - Copyright @ 2012 John Wiley & Sons, Ltd.In this paper, the distributed state estimation problem is investigated for a class of sensor networks described by uncertain discrete-time dynamical systems with Markovian jumping parameters and distributed time-delays. The sensor network consists of sensor nodes characterized by a directed graph with a nonnegative adjacency matrix that specifies the interconnection topology (or the distribution in the space) of the network. Both the parameters of the target plant and the sensor measurements are subject to the switches from one mode to another at different times according to a Markov chain. The parameter uncertainties are norm-bounded that enter into both the plant system as well as the network outputs. Furthermore, the distributed time-delays are considered, which are also dependent on the Markovian jumping mode. Through the measurements from a small fraction of the sensors, this paper aims to design state estimators that allow the nodes of the sensor network to track the states of the plant in a distributed way. It is verified that such state estimators do exist if a set of matrix inequalities is solvable. A numerical example is provided to demonstrate the effectiveness of the designed distributed state estimators.This work was supported in part by the Royal Society of the U.K., the National Natural Science Foundation of China under Grants 60804028 and 61028008, the Specialized Research Fund for the Doctoral Program of Higher Education for New Teachers in China under Grant 200802861044, the Teaching and Research Fund for Excellent Young Teachers at Southeast University of China, the International Science and Technology Cooperation Project of China under Grant No. 2009DFA32050, and the Alexander von Humboldt Foundation of Germany
SRDA-Net: Super-Resolution Domain Adaptation Networks for Semantic Segmentation
Recently, Unsupervised Domain Adaptation was proposed to address the domain
shift problem in semantic segmentation task, but it may perform poor when
source and target domains belong to different resolutions. In this work, we
design a novel end-to-end semantic segmentation network, Super-Resolution
Domain Adaptation Network (SRDA-Net), which could simultaneously complete
super-resolution and domain adaptation. Such characteristics exactly meet the
requirement of semantic segmentation for remote sensing images which usually
involve various resolutions. Generally, SRDA-Net includes three deep neural
networks: a Super-Resolution and Segmentation (SRS) model focuses on recovering
high-resolution image and predicting segmentation map; a pixel-level domain
classifier (PDC) tries to distinguish the images from which domains; and
output-space domain classifier (ODC) discriminates pixel label distributions
from which domains. PDC and ODC are considered as the discriminators, and SRS
is treated as the generator. By the adversarial learning, SRS tries to align
the source with target domains on pixel-level visual appearance and
output-space. Experiments are conducted on the two remote sensing datasets with
different resolutions. SRDA-Net performs favorably against the state-of-the-art
methods in terms of accuracy and visual quality. Code and models are available
at https://github.com/tangzhenjie/SRDA-Net
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