5,458 research outputs found
Quantifying the impact of future Sandage-Loeb test data on dark energy constraints
The Sandage-Loeb (SL) test is a unique method to probe dark energy in the
"redshift desert" of , and thus it provides an important
supplement to the other dark energy probes. Therefore, it is of great
importance to quantify how the future SL test data impact on the dark energy
constraints. To avoid the potential inconsistency in data, we use the
best-fitting model based on the other geometric measurements as the fiducial
model to produce 30 mock SL test data. The 10-yr, 20-yr, and 30-yr observations
of SL test are analyzed and compared in detail. We show that compared to the
current combined data of type Ia supernovae, baryon acoustic oscillation,
cosmic microwave background, and Hubble constant, the 30-yr observation of SL
test could improve the constraint on by about and the
constraint on by about . Furthermore, the SL test can also improve the
measurement of the possible direct interaction between dark energy and dark
matter. We show that the SL test 30-yr data could improve the constraint on
by about and for the and models, respectively.Comment: 10 pages, 3 figure
Parameter estimation with Sandage-Loeb test
The Sandage-Loeb (SL) test directly measures the expansion rate of the
universe in the redshift range of by detecting redshift
drift in the spectra of Lyman- forest of distant quasars. We discuss
the impact of the future SL test data on parameter estimation for the
CDM, the CDM, and the CDM models. To avoid the potential
inconsistency with other observational data, we take the best-fitting dark
energy model constrained by the current observations as the fiducial model to
produce 30 mock SL test data. The SL test data provide an important supplement
to the other dark energy probes, since they are extremely helpful in breaking
the existing parameter degeneracies. We show that the strong degeneracy between
and in all the three dark energy models is well broken by the
SL test. Compared to the current combined data of type Ia supernovae, baryon
acoustic oscillation, cosmic microwave background, and Hubble constant, the
30-yr observation of SL test could improve the constraints on and
by more than 60\% for all the three models. But the SL test can only
moderately improve the constraint on the equation of state of dark energy. We
show that a 30-yr observation of SL test could help improve the constraint on
constant by about 25\%, and improve the constraints on and by
about 20\% and 15\%, respectively. We also quantify the constraining power of
the SL test in the future high-precision joint geometric constraints on dark
energy. The mock future supernova and baryon acoustic oscillation data are
simulated based on the space-based project JDEM. We find that the 30-yr
observation of SL test would help improve the measurement precision of
, , and by more than 70\%, 20\%, and 60\%, respectively,
for the CDM model.Comment: 16 pages, 9 figures, 3 tables; adding a new section to address future
SN and BAO observations; accepted for publication in JCA
Neutrinos and dark energy after Planck and BICEP2: data consistency tests and cosmological parameter constraints
The detection of the B-mode polarization of the cosmic microwave background
(CMB) by the BICEP2 experiment implies that the tensor-to-scalar ratio
should be involved in the base standard cosmology. In this paper, we extend the
CDM++neutrino/dark radiation models by replacing the cosmological
constant with the dynamical dark energy with constant . Four neutrino plus
dark energy models are considered, i.e., the CDM+, CDM+r +
, CDM+r + + , and CDM+r + + models. The current observational
data considered in this paper include the Planck temperature data, the WMAP
9-year polarization data, the baryon acoustic oscillation data, the Hubble
constant direct measurement data, the Planck Sunyaev-Zeldovich cluster counts
data, the Planck CMB lensing data, the cosmic shear data, and the BICEP2
polarization data. We test the data consistency in the four cosmological
models, and then combine the consistent data sets to perform joint constraints
on the models. We focus on the constraints on the parameters , ,
, and .Comment: 22 pages, 8 figures, 5 table
Redshift drift exploration for interacting dark energy
By detecting redshift drift in the spectra of Lyman- forest of
distant quasars, Sandage-Loeb (SL) test directly measures the expansion of the
universe, covering the "redshift desert" of . Thus this
method is definitely an important supplement to the other geometric
measurements and will play a crucial role in cosmological constraints. In this
paper, we quantify the ability of SL test signal by a CODEX-like spectrograph
for constraining interacting dark energy. Four typical interacting dark energy
models are considered: (i) , (ii) ,
(iii) , and (iv) . The results show
that for all the considered interacting dark energy models, relative to the
current joint SN+BAO+CMB+ observations, the constraints on and
would be improved by about 60\% and 30--40\%, while the constraints on
and would be slightly improved, with a 30-yr observation of SL
test. We also explore the impact of SL test on future joint geometric
observations. In this analysis, we take the model with as an
example, and simulate future SN and BAO data based on the space-based project
WFIRST. We find that in the future geometric constraints, the redshift drift
observations would help break the geometric degeneracies in a meaningful way,
thus the measurement precisions of , , , and could
be substantially improved using future probes.Comment: 6 pages, 5 figures; accepted for publication in EPJC. arXiv admin
note: text overlap with arXiv:1407.712
Fine-Grained Car Detection for Visual Census Estimation
Targeted socioeconomic policies require an accurate understanding of a
country's demographic makeup. To that end, the United States spends more than 1
billion dollars a year gathering census data such as race, gender, education,
occupation and unemployment rates. Compared to the traditional method of
collecting surveys across many years which is costly and labor intensive,
data-driven, machine learning driven approaches are cheaper and faster--with
the potential ability to detect trends in close to real time. In this work, we
leverage the ubiquity of Google Street View images and develop a computer
vision pipeline to predict income, per capita carbon emission, crime rates and
other city attributes from a single source of publicly available visual data.
We first detect cars in 50 million images across 200 of the largest US cities
and train a model to predict demographic attributes using the detected cars. To
facilitate our work, we have collected the largest and most challenging
fine-grained dataset reported to date consisting of over 2600 classes of cars
comprised of images from Google Street View and other web sources, classified
by car experts to account for even the most subtle of visual differences. We
use this data to construct the largest scale fine-grained detection system
reported to date. Our prediction results correlate well with ground truth
income data (r=0.82), Massachusetts department of vehicle registration, and
sources investigating crime rates, income segregation, per capita carbon
emission, and other market research. Finally, we learn interesting
relationships between cars and neighborhoods allowing us to perform the first
large scale sociological analysis of cities using computer vision techniques.Comment: AAAI 201
Naphthocage: A Flexible yet Extremely Strong Binder to Organic Cations with Naphthalene Walls
Macrocyclic receptors are key elements in the foundation and development of supramolecular chemistry, because they not only provide binding cavities that are capable of trapping guest molecules and can be chemically modified to bear functional groups for their novel binding properties, but also reveal their nature of intermolecular interactions to know how to instruct supramolecular self-assembly and the applications of functional materials. Since 1967, either the old or the emergence of new ones, a wide range of applications (such as supramolecular assemblies, supramolecular polymers, supramolecular gelators, supramolecular catalysis, molecular machines and devices, and other kinds of novel materials) were intensively explored. Therefore, the design and synthesis of novel macrocyclic molecules and the investigation of their molecular recognition properties play a vital role in supramolecular chemistry.大环受体分子是超分子化学得主要研究对象。因为大环主体分子不仅能够提供键合受体分子得空腔,还可以通过化学反应修饰官能团来提升键合性质,更为重要的是可以通过研究弱相互作用力来发展超分子自组装以及功能材料应用。自从1967年以来,对于超分子大环的研究出现了一股热潮。主要是基于超分子自组装,超分子聚合物,超分子凝胶,超分子催化和分子机器等。因此,设计和合成大环分子以及研究分子识别在超分子化学领域具有很重要的作用
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