7,589 research outputs found
Determining the luminosity function of Swift long gamma-ray bursts with pseudo-redshifts
The determination of luminosity function (LF) of gamma-ray bursts (GRBs) is
of an important role for the cosmological applications of the GRBs, which is
however hindered seriously by some selection effects due to redshift
measurements. In order to avoid these selection effects, we suggest to
calculate pseudo-redshifts for Swift GRBs according to the empirical L-E_p
relationship. Here, such a relationship is determined by reconciling
the distributions of pseudo- and real redshifts of redshift-known GRBs. The
values of E_p taken from Butler's GRB catalog are estimated with Bayesian
statistics rather than observed. Using the GRB sample with pseudo-redshifts of
a relatively large number, we fit the redshift-resolved luminosity
distributions of the GRBs with a broken-power-law LF. The fitting results
suggest that the LF could evolve with redshift by a redshift-dependent break
luminosity, e.g., L_b=1.2\times10^{51}(1+z)^2\rm erg s^{-1}. The low- and
high-luminosity indices are constrained to 0.8 and 2.0, respectively. It is
found that the proportional coefficient between GRB event rate and star
formation rate should correspondingly decrease with increasing redshifts.Comment: 5 pages, 5 figures, accepted for publication in ApJ
Joint constraint on the jet structure from the short GRB population and GRB 170817A
The nearest GRB 170817A provided an opportunity to probe the angular
structure of the jet of this short gamma-ray burst (SGRB), by using its
off-axis observed afterglow emission. It is investigated that whether the
afterglow-constrained jet structures can be consistent with the luminosity of
the prompt emission of GRB 170817A. Furthermore, by assuming that all SGRBs
including GRB 170817A have the same explosive mechanism and jet structure, we
apply the different jet structures into the calculation of the flux and
redshfit distributions of the SGRB population, in comparison with the
observational distributions of the Swift and Fermi sources. As a result, it is
found that the single-Gaussian structure can be basically ruled out, whereas
the power-law and two-Gaussian models can in principle survive.Comment: 9 pages,6 figure
Phonon and Raman scattering of two-dimensional transition metal dichalcogenides from monolayer, multilayer to bulk material
Two-dimensional (2D) transition metal dichalcogenide (TMD) nanosheets exhibit
remarkable electronic and optical properties. The 2D features, sizable
bandgaps, and recent advances in the synthesis, characterization, and device
fabrication of the representative MoS, WS, WSe, and MoSe TMDs
make TMDs very attractive in nanoelectronics and optoelectronics. Similar to
graphite and graphene, the atoms within each layer in 2D TMDs are joined
together by covalent bonds, while van der Waals interactions keep the layers
together. This makes the physical and chemical properties of 2D TMDs layer
dependent. In this review, we discuss the basic lattice vibrations of
monolayer, multilayer, and bulk TMDs, including high-frequency optical phonons,
interlayer shear and layer breathing phonons, the Raman selection rule,
layer-number evolution of phonons, multiple phonon replica, and phonons at the
edge of the Brillouin zone. The extensive capabilities of Raman spectroscopy in
investigating the properties of TMDs are discussed, such as interlayer
coupling, spin--orbit splitting, and external perturbations. The interlayer
vibrational modes are used in rapid and substrate-free characterization of the
layer number of multilayer TMDs and in probing interface coupling in TMD
heterostructures. The success of Raman spectroscopy in investigating TMD
nanosheets paves the way for experiments on other 2D crystals and related van
der Waals heterostructures.Comment: 30 pages, 23 figure
Polytypism and Unexpected Strong Interlayer Coupling of two-Dimensional Layered ReS2
The anisotropic two-dimensional (2D) van der Waals (vdW) layered materials,
with both scientific interest and potential application, have one more
dimension to tune the properties than the isotropic 2D materials. The
interlayer vdW coupling determines the properties of 2D multi-layer materials
by varying stacking orders. As an important representative anisotropic 2D
materials, multilayer rhenium disulfide (ReS2) was expected to be random
stacking and lack of interlayer coupling. Here, we demonstrate two stable
stacking orders (aa and a-b) of N layer (NL, N>1) ReS2 from ultralow-frequency
and high-frequency Raman spectroscopy, photoluminescence spectroscopy and
first-principles density functional theory calculation. Two interlayer shear
modes are observed in aa-stacked NL-ReS2 while only one interlayer shear mode
appears in a-b-stacked NL-ReS2, suggesting anisotropic-like and isotropic-like
stacking orders in aa- and a-b-stacked NL-ReS2, respectively. The frequency of
the interlayer shear and breathing modes reveals unexpected strong interlayer
coupling in aa- and a-b-NL-ReS2, the force constants of which are 55-90% to
those of multilayer MoS2. The observation of strong interlayer coupling and
polytypism in multi-layer ReS2 stimulate future studies on the structure,
electronic and optical properties of other 2D anisotropic materials
Detaching and Boosting: Dual Engine for Scale-Invariant Self-Supervised Monocular Depth Estimation
Monocular depth estimation (MDE) in the self-supervised scenario has emerged
as a promising method as it refrains from the requirement of ground truth
depth. Despite continuous efforts, MDE is still sensitive to scale changes
especially when all the training samples are from one single camera. Meanwhile,
it deteriorates further since camera movement results in heavy coupling between
the predicted depth and the scale change. In this paper, we present a
scale-invariant approach for self-supervised MDE, in which scale-sensitive
features (SSFs) are detached away while scale-invariant features (SIFs) are
boosted further. To be specific, a simple but effective data augmentation by
imitating the camera zooming process is proposed to detach SSFs, making the
model robust to scale changes. Besides, a dynamic cross-attention module is
designed to boost SIFs by fusing multi-scale cross-attention features
adaptively. Extensive experiments on the KITTI dataset demonstrate that the
detaching and boosting strategies are mutually complementary in MDE and our
approach achieves new State-of-The-Art performance against existing works from
0.097 to 0.090 w.r.t absolute relative error. The code will be made public
soon.Comment: Accepted by IEEE Robotics and Automation Letters (RAL
Semi-supervised Cycle-GAN for face photo-sketch translation in the wild
The performance of face photo-sketch translation has improved a lot thanks to
deep neural networks. GAN based methods trained on paired images can produce
high-quality results under laboratory settings. Such paired datasets are,
however, often very small and lack diversity. Meanwhile, Cycle-GANs trained
with unpaired photo-sketch datasets suffer from the \emph{steganography}
phenomenon, which makes them not effective to face photos in the wild. In this
paper, we introduce a semi-supervised approach with a noise-injection strategy,
named Semi-Cycle-GAN (SCG), to tackle these problems. For the first problem, we
propose a {\em pseudo sketch feature} representation for each input photo
composed from a small reference set of photo-sketch pairs, and use the
resulting {\em pseudo pairs} to supervise a photo-to-sketch generator
. The outputs of can in turn help to train a sketch-to-photo
generator in a self-supervised manner. This allows us to train
and using a small reference set of photo-sketch pairs
together with a large face photo dataset (without ground-truth sketches). For
the second problem, we show that the simple noise-injection strategy works well
to alleviate the \emph{steganography} effect in SCG and helps to produce more
reasonable sketch-to-photo results with less overfitting than fully supervised
approaches. Experiments show that SCG achieves competitive performance on
public benchmarks and superior results on photos in the wild.Comment: 11 pages, 11 figures, 5 tables (+ 7 page appendix
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