اشترك بالحزمة الذهبية واحصل على وصول غير محدود شمرا أكاديميا
تسجيل مستخدم جديدData Analysis and Phenomenological Cosmology
47
0
0.0
(
0
)
اسأل ChatGPT حول البحث
ﻻ يوجد ملخص باللغة العربية
In the era of precision cosmology, even percentage level effects are significant on cosmological observables. The recent tension between the local and global values of $H_0$ is much more significant than this, and any possible solution might rely on us going beyond the standard $Lambda$CDM cosmological model. For much smaller, yet potentially significant effects, spatial curvature from averaging and cosmological backreaction on observational predictions could play a role. This is especially true with the higher precision of new observational data and improved statistical techniques. In this paper, we discuss the observational viability of a class of physically motivated cosmologies which can be parametrized by a phenomenological two-scale backreaction model with decoupled spatial curvature parameters and two Hubble scales. Using the latest JLA Supernovae data together with some of the latest BAO data, we perform a Bayesian model selection analysis and find that the phenomenological models are not favoured over the standard $Lambda$CDM cosmological model. Although there is still a preference for non-zero and unequal dynamic and geometric spatial curvatures, there is little evidence for differing Hubble scales within these phenomenological template models.
قيم البحث
اقرأ أيضاً
We define an optimal basis system into which cosmological observables can be decomposed. The basis system can be optimised for a specific cosmological model or for an ensemble of models, even if based on drastically different physical assumptions. Th
e projection coefficients derived from this basis system, the so-called features, provide a common parameterisation for studying and comparing different cosmological models independently of their physical construction. They can be used to directly compare different cosmologies and study their degeneracies in terms of a simple metric separation. This is a very convenient approach, since only very few realisations have to be computed, in contrast to Markov-Chain Monte Carlo methods. Finally, the proposed basis system can be applied to reconstruct the Hubble expansion rate from supernova luminosity distance data with the advantage of being sensitive to possible unexpected features in the data set. We test the method both on mock catalogues and on the SuperNova Legacy Survey data set.
We present an investigation of the horizon and its effect on global 21-cm observations and analysis. We find that the horizon cannot be ignored when modeling low frequency observations. Even if the sky and antenna beam are known exactly, forward mode
ls cannot fully describe the beam-weighted foreground component without accurate knowledge of the horizon. When fitting data to extract the 21-cm signal, a single time-averaged spectrum or independent multi-spectrum fits may be able to compensate for the bias imposed by the horizon. However, these types of fits lack constraining power on the 21-cm signal, leading to large uncertainties on the signal extraction, in some cases larger in magnitude than the 21-cm signal itself. A significant decrease in signal uncertainty can be achieved by performing multi-spectrum fits in which the spectra are modeled simultaneously with common parameters. The cost of this greatly increased constraining power, however, is that the time dependence of the horizons effect, which is more complex than its spectral dependence, must be precisely modeled to achieve a good fit. To aid in modeling the horizon, we present an algorithm and Python package for calculating the horizon profile from a given observation site using elevation data. We also address several practical concerns such as pixelization error, uncertainty in the horizon profile, and foreground obstructions such as surrounding buildings and vegetation. We demonstrate that our training set-based analysis pipeline can account for all of these factors to model the horizon well enough to precisely extract the 21-cm signal from simulated observations.
Two recent large data releases for the Atacama Cosmology Telescope (ACT), called DR4 and DR5, are available for public access. These data include temperature and polarization maps that cover nearly half the sky at arcminute resolution in three freque
ncy bands; lensing maps and component-separated maps covering ~ 2,100 deg^2 of sky; derived power spectra and cosmological likelihoods; a catalog of over 4,000 galaxy clusters; and supporting ancillary products including beam functions and masks. The data and products are described in a suite of ACT papers; here we provide a summary. In order to facilitate ease of access to these data we present a set of Jupyter IPython notebooks developed to introduce users to DR4, DR5, and the tools needed to analyze these data. The data products (excluding simulations) and the set of notebooks are publicly available on the NASA Legacy Archive for Microwave Background Data Analysis (LAMBDA); simulation products are available on the National Energy Research Scientific Computing Center (NERSC).
The Blanco Cosmology Survey (BCS) is a 60 night imaging survey of $sim$80 deg$^2$ of the southern sky located in two fields: ($alpha$,$delta$)= (5 hr, $-55^{circ}$) and (23 hr, $-55^{circ}$). The survey was carried out between 2005 and 2008 in $griz$
bands with the Mosaic2 imager on the Blanco 4m telescope. The primary aim of the BCS survey is to provide the data required to optically confirm and measure photometric redshifts for Sunyaev-Zeldovich effect selected galaxy clusters from the South Pole Telescope and the Atacama Cosmology Telescope. We process and calibrate the BCS data, carrying out PSF corrected model fitting photometry for all detected objects. The median 10$sigma$ galaxy (point source) depths over the survey in $griz$ are approximately 23.3 (23.9), 23.4 (24.0), 23.0 (23.6) and 21.3 (22.1), respectively. The astrometric accuracy relative to the USNO-B survey is $sim45$ milli-arcsec. We calibrate our absolute photometry using the stellar locus in $grizJ$ bands, and thus our absolute photometric scale derives from 2MASS which has $sim2$% accuracy. The scatter of stars about the stellar locus indicates a systematics floor in the relative stellar photometric scatter in $griz$ that is $sim$1.9%, $sim$2.2%, $sim$2.7% and$sim$2.7%, respectively. A simple cut in the AstrOmatic star-galaxy classifier {tt spread_model} produces a star sample with good spatial uniformity. We use the resulting photometric catalogs to calibrate photometric redshifts for the survey and demonstrate scatter $delta z/(1+z)=0.054$ with an outlier fraction $eta<5$% to $zsim1$. We highlight some selected science results to date and provide a full description of the released data products.
The X-ray regime, where the most massive visible component of galaxy clusters, the intra cluster medium (ICM), is visible, offers directly measured quantities, like the luminosity, and derived quantities, like the total mass, to characterize these ob
jects. The aim of this project is to analyze a complete sample of galaxy clusters in detail and constrain cosmological parameters, like the matter density, OmegaM, or the amplitude of initial density fluctuations, sigma8. The purely X-ray flux-limited sample (HIFLUGCS) consists of the 64 X-ray brightest galaxy clusters, which are excellent targets to study the systematic effects, that can bias results. We analyzed in total 196 Chandra observations of the 64 HIFLUGCS clusters, with a total exposure time of 7.7 Ms. Here we present our data analysis procedure (including an automated substructure detection and an energy band optimization for surface brightness profile analysis) which gives individually determined, robust total mass estimates. These masses are tested against dynamical and Planck Sunyaev-Zeldovich (SZ) derived masses of the same clusters, where good overall agreement is found with the dynamical masses. The Planck SZ masses seem to show a mass dependent bias to our hydrostatic masses; possible biases in this mass-mass comparison are discussed including the Planck selection function. Furthermore, we show the results for the 0.1-2.4-keV-luminosity vs. mass scaling-relation. The overall slope of the sample (1.34) is in agreement with expectations and values from literature. Splitting the sample into galaxy groups and clusters reveals, even after a selection bias correction, that galaxy groups exhibit a significantly steeper slope (1.88) compared to clusters (1.06).
سجل دخول لتتمكن من نشر تعليقات
التعليقات
جاري جلب التعليقات
سجل دخول لتتمكن من متابعة معايير البحث التي قمت باختيارها
