482 research outputs found
Quenching depends on morphologies: implications from the ultraviolet-optical radial color distributions in Green Valley Galaxies
In this Letter, we analyse the radial UV-optical color distributions in a
sample of low redshift green valley (GV) galaxies, with the Galaxy Evolution
Explorer (GALEX)+Sloan Digital Sky Survey (SDSS) images, to investigate how the
residual recent star formation distribute in these galaxies. We find that the
dust-corrected colors of early-type galaxies (ETGs) are flat out to
, while the colors turn blue monotonously when for
late-type galaxies (LTGs). More than a half of the ETGs are blue-cored and have
remarkable positive NUV color gradients, suggesting that their star
formation are centrally concentrated; the rest have flat color distributions
out to . The centrally concentrated star formation activity in a large
portion of ETGs is confirmed by the SDSS spectroscopy, showing that 50 %
ETGs have EW(H) \AA. For the LTGs, 95% of them show uniform
radial color profiles, which can be interpreted as a red bulge plus an extended
blue disk. The links between the two kinds of ETGs, e.g., those objects having
remarkable "blue-cored" and those having flat color gradients, are less known
and require future investigations. It is suggested that the LTGs follow a
general picture that quenching first occur in the core regions, and then
finally extend to the rest of the galaxy. Our results can be re-examined and
have important implications for the IFU surveys, such as MaNGA and SAMI.Comment: ApJ Letter, accepted. Five figure
From outside-in to inside-out: galaxy assembly mode depends on stellar mass
In this Letter, we investigate how galaxy mass assembly mode depends on
stellar mass , using a large sample of 10, 000 low redshift
galaxies. Our galaxy sample is selected to have SDSS R_{90}>5\arcsec.0, which
allows the measures of both the integrated and the central NUV color
indices. We find that: in the NUV) green valley, the
M_{\ast}<10^{10}~M_{\sun} galaxies mostly have positive or flat color
gradients, while most of the M_{\ast}>10^{10.5}~M_{\sun} galaxies have
negative color gradients. When their central index values exceed
1.6, the M_{\ast}<10^{10.0}~M_{\sun} galaxies have moved to the UV red
sequence, whereas a large fraction of the M_{\ast}>10^{10.5}~M_{\sun}
galaxies still lie on the UV blue cloud or the green valley region. We conclude
that the main galaxy assembly mode is transiting from "the outside-in" mode to
"the inside-out" mode at M_{\ast}
10^{10.5}~M_{\sun}. We argue that the physical origin of this is the
compromise between the internal and the external process that driving the star
formation quenching in galaxies. These results can be checked with the upcoming
large data produced by the on-going IFS survey projects, such as CALIFA, MaNGA
and SAMI in the near future.Comment: Accepted for publication in ApJL,6 pages, 5 figure
Satellite Alignment: I. Distribution of Substructures and Their Dependence On Assembly History From N-Body Simulations
Observations have shown that the spatial distribution of satellite galaxies
is not random, but aligned with the major axes of central galaxies. This
alignment is dependent on galaxy properties, such that red satellites are more
strongly aligned than blue satellites. Theoretical work done to interpret this
phenomena has found that it is due to the non-spherical nature of dark matter
halos. However, most studies over-predict the alignment signal under the
assumption that the central galaxy shape follows the shape of the host halo. It
is also not clear whether the color dependence of alignment is due to an
assembly bias or an evolution effect. In this paper we study these problems
using a cosmological N-body simulation. Subhalos are used to trace the
positions of satellite galaxies. It is found that the shape of dark matter
halos are mis-aligned at different radii. If the central galaxy shares the same
shape as the inner host halo, then the alignment effect is weaker and agrees
with observational data. However, it predicts almost no dependence of alignment
on the color of satellite galaxies, though the late accreted subhalos show
stronger alignment with the outer layer of the host halo than their early
accreted counterparts. We find that this is due to the limitation of pure
N-body simulations that satellites galaxies without associated subhalos
('orphan galaxies') are not resolved. These orphan (mostly red) satellites
often reside in the inner region of host halos and should follow the shape of
the host halo in the inner region.Comment: 12 pages, 11 figures, Published on Ap
The Distribution of Satellites Around Central Galaxies in a Cosmological Hydrodynamical Simulation
Observations have shown that the spatial distribution of satellite galaxies
is not random, but rather is aligned with the major axes of central galaxies
(CGs). The strength of the alignment is dependent on the properties of both the
satellites and centrals. Theoretical studies using dissipationless N-body
simulations are limited by their inability to directly predict the shape of
CGs. Using hydrodynamical simulations including gas cooling, star formation,
and feedback, we carry out a study of galaxy alignment and its dependence on
the galaxy properties predicted directly from the simulations.We found that the
observed alignment signal is well produced, as is the color dependence: red
satellites and red centrals both show stronger alignments than their blue
counterparts. The reason for the stronger alignment of red satellites is that
most of them stay in the inner region of the dark matter halo where the shape
of the CG better traces the dark matter distribution. The dependence of
alignment on the color of CGs arises from the halo mass dependence, since the
alignment between the shape of the central stellar component and the inner halo
increases with halo mass. We also find that the alignment of satellites is most
strongly dependent on their metallicity, suggesting that the metallicity of
satellites, rather than color, is a better tracer of galaxy alignment on small
scales. This could be tested in future observational studies.Comment: ApJ Letter, accepted. Four figures, no table. The resolution of Fig 1
was downgraded due to the limitation of file size. Updated to match the
version in pres
Telepath: Understanding Users from a Human Vision Perspective in Large-Scale Recommender Systems
Designing an e-commerce recommender system that serves hundreds of millions
of active users is a daunting challenge. From a human vision perspective,
there're two key factors that affect users' behaviors: items' attractiveness
and their matching degree with users' interests. This paper proposes Telepath,
a vision-based bionic recommender system model, which understands users from
such perspective. Telepath is a combination of a convolutional neural network
(CNN), a recurrent neural network (RNN) and deep neural networks (DNNs). Its
CNN subnetwork simulates the human vision system to extract key visual signals
of items' attractiveness and generate corresponding activations. Its RNN and
DNN subnetworks simulate cerebral cortex to understand users' interest based on
the activations generated from browsed items. In practice, the Telepath model
has been launched to JD's recommender system and advertising system. For one of
the major item recommendation blocks on the JD app, click-through rate (CTR),
gross merchandise value (GMV) and orders have increased 1.59%, 8.16% and 8.71%
respectively. For several major ads publishers of JD demand-side platform, CTR,
GMV and return on investment have increased 6.58%, 61.72% and 65.57%
respectively by the first launch, and further increased 2.95%, 41.75% and
41.37% respectively by the second launch.Comment: 8 pages, 11 figures, 1 tabl
Multi-Symplectic Simulation on Soliton-Collision for Nonlinear Perturbed Schrödinger Equation
Seeking solitary wave solutions and revealing their interactional characteristics for nonlinear evolution equations help us lot to comprehend the motion laws of the microparticles. As a local nonlinear dynamic behavior, the soliton-collision is difficult to be reproduced numerically. In this paper, the soliton-collision process in the nonlinear perturbed Schrödinger equation is simulated employing the multi-symplectic method. The multi-symplectic formulations are derived including the multi-symplectic form and three local conservation laws of the nonlinear perturbed Schrödinger equation. Employing the implicit midpoint rule, we construct a multi-symplectic scheme, which is equivalent to the Preissmann box scheme, for the nonlinear perturbed Schrödinger equation. The elegant structure-preserving properties of the multi-symplectic scheme are illustrated by the tiny maximum absolute residual of the discrete multi-symplectic structure at each time step in the numerical simulations. The effects of the perturbation strength on the soliton-collision in the nonlinear perturbed Schrödinger equation are reported in the numerical results in detail
A hybrid Decoder-DeepONet operator regression framework for unaligned observation data
Deep neural operators (DNOs) have been utilized to approximate nonlinear
mappings between function spaces. However, DNOs face the challenge of increased
dimensionality and computational cost associated with unaligned observation
data. In this study, we propose a hybrid Decoder-DeepONet operator regression
framework to handle unaligned data effectively. Additionally, we introduce a
Multi-Decoder-DeepONet, which utilizes an average field of training data as
input augmentation. The consistencies of the frameworks with the operator
approximation theory are provided, on the basis of the universal approximation
theorem. Two numerical experiments, Darcy problem and flow-field around an
airfoil, are conducted to validate the efficiency and accuracy of the proposed
methods. Results illustrate the advantages of Decoder-DeepONet and
Multi-Decoder-DeepONet in handling unaligned observation data and showcase
their potentials in improving prediction accuracy.Comment: 35 pages, 10 figures, 11 table
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