5,813 research outputs found
Search for sterile neutrinos in holographic dark energy cosmology: Reconciling Planck observation with the local measurement of the Hubble constant
We search for sterile neutrinos in the holographic dark energy cosmology by
using the latest observational data. To perform the analysis, we employ the
current cosmological observations, including the cosmic microwave background
temperature power spectrum data from the Planck mission, the baryon acoustic
oscillation measurements, the type Ia supernova data, the redshift space
distortion measurements, the shear data of weak lensing observation, the Planck
lensing measurement, and the latest direct measurement of as well. We
show that, compared to the CDM cosmology, the holographic dark energy
cosmology with sterile neutrinos can relieve the tension between the Planck
observation and the direct measurement of much better. Once we include
the measurement in the global fit, we find that the hint of the existence
of sterile neutrinos in the holographic dark energy cosmology can be given.
Under the constraint of the all-data combination, we obtain and , indicating
that the detection of in the holographic dark energy
cosmology is at the level and the massless or very light sterile
neutrino is favored by the current observations.Comment: 10 pages, 4 figures; typos corrected, published in PR
Neutrinos in the holographic dark energy model: constraints from latest measurements of expansion history and growth of structure
The model of holographic dark energy (HDE) with massive neutrinos and/or dark
radiation is investigated in detail. The background and perturbation evolutions
in the HDE model are calculated. We employ the PPF approach to overcome the
gravity instability difficulty (perturbation divergence of dark energy) led by
the equation-of-state parameter evolving across the phantom divide
in the HDE model with . We thus derive the evolutions of density
perturbations of various components and metric fluctuations in the HDE model.
The impacts of massive neutrino and dark radiation on the CMB anisotropy power
spectrum and the matter power spectrum in the HDE scenario are discussed.
Furthermore, we constrain the models of HDE with massive neutrinos and/or dark
radiation by using the latest measurements of expansion history and growth of
structure, including the Planck CMB temperature data, the baryon acoustic
oscillation data, the JLA supernova data, the Hubble constant direct
measurement, the cosmic shear data of weak lensing, the Planck CMB lensing
data, and the redshift space distortions data. We find that
eV (95\% CL) and in the HDE model from the
constraints of these data.Comment: 18 pages, 5 figures; revised version accepted for publication in JCA
Revisiting the holographic dark energy in a non-flat universe: alternative model and cosmological parameter constraints
We propose an alternative model for the holographic dark energy in a non-flat
universe. This new model differs from the previous one in that the IR length
cutoff is taken to be exactly the event horizon size in a non-flat
universe, which is more natural and theoretically/conceptually concordant with
the model of holographic dark energy in a flat universe. We constrain the model
using the recent observational data including the type Ia supernova data from
SNLS3, the baryon acoustic oscillation data from 6dF, SDSS-DR7, BOSS-DR11, and
WiggleZ, the cosmic microwave background data from Planck, and the Hubble
constant measurement from HST. In particular, since some previous studies have
shown that the color-luminosity parameter of supernovae is likely to
vary during the cosmic evolution, we also consider such a case that in
SNLS3 is time-varying in our data fitting. Compared to the constant
case, the time-varying case reduces the value of by about 35
and results in that deviates from a constant at about 5 level,
well consistent with the previous studies. For the parameter of the
holographic dark energy, the constant fit gives and
the time-varying fit yields . In addition, an open
universe is favored (at about 2) for the model by the current data.Comment: 8 pages, 4 figure
Res2Net: A New Multi-scale Backbone Architecture
Representing features at multiple scales is of great importance for numerous
vision tasks. Recent advances in backbone convolutional neural networks (CNNs)
continually demonstrate stronger multi-scale representation ability, leading to
consistent performance gains on a wide range of applications. However, most
existing methods represent the multi-scale features in a layer-wise manner. In
this paper, we propose a novel building block for CNNs, namely Res2Net, by
constructing hierarchical residual-like connections within one single residual
block. The Res2Net represents multi-scale features at a granular level and
increases the range of receptive fields for each network layer. The proposed
Res2Net block can be plugged into the state-of-the-art backbone CNN models,
e.g., ResNet, ResNeXt, and DLA. We evaluate the Res2Net block on all these
models and demonstrate consistent performance gains over baseline models on
widely-used datasets, e.g., CIFAR-100 and ImageNet. Further ablation studies
and experimental results on representative computer vision tasks, i.e., object
detection, class activation mapping, and salient object detection, further
verify the superiority of the Res2Net over the state-of-the-art baseline
methods. The source code and trained models are available on
https://mmcheng.net/res2net/.Comment: 11 pages, 7 figure
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