118374217
Energy conditions bounds and supernovae data
The energy conditions play an important role in the description of some important properties of the Universe, including the current accelerating expansion phase and the possible recent phase of super-acceleration. In a recent work we have provided a detailed study of the energy conditions for the recent past by deriving bounds from energy conditions and by making the confrontation of the bounds with supernovae data. Here, we extend and update these results in two different ways. First, by carrying out a new statistical analysis for q(z) estimates needed for the confrontation between the bounds and supernovae data. Second, by providing a new picture of the energy conditions fulfillment and violation in the light of the recently compiled Union set of 307 type Ia supernovae and by using two different statistical approaches.
119117118
Biases on cosmological parameter estimators from galaxy cluster number counts
Sunyaev-Zel'dovich (SZ) surveys are promising probes of cosmology — in particular for Dark Energy (DE) —, given their ability to find distant clusters and provide estimates for their mass. However, current SZ catalogs contain tens to hundreds of objects and maximum likelihood estimators may present biases for such sample sizes. In this work we study estimators from cluster abundance for some cosmological parameters, in particular the DE equation of state parameter w{sub 0}, the amplitude of density fluctuations σ{sub 8}, and the Dark Matter density parameter Ω{sub c}. We begin by deriving an unbinned likelihood for cluster number counts, showing that it is equivalent to the one commonly used in the literature. We use the Monte Carlo approach to determine the presence of bias using this likelihood and study its behavior with both the area and depth of the survey, and the number of cosmological parameters fitted. Our fiducial models are based on the South Pole Telescope (SPT) SZ survey. Assuming perfect knowledge of mass and redshift some estimators have non-negligible biases. For example, the bias of σ{sub 8} corresponds to about 40% of its statistical error bar when fitted together with Ω{sub c} and w{sub 0}. Including a SZmore » mass-observable relation decreases the relevance of the bias, for the typical sizes of current SZ surveys. Considering a joint likelihood for cluster abundance and the so-called ''distance priors'', we obtain that the biases are negligible compared to the statistical errors. However, we show that the biases from SZ estimators do not go away with increasing sample sizes and they may become the dominant source of error for an all sky survey at the SPT sensitivity. Finally, we compute the confidence regions for the cosmological parameters using Fisher matrix and profile likelihood approaches, showing that they are compatible with the Monte Carlo ones. The results of this work validate the use of the current maximum likelihood methods for present SZ surveys, but highlight the need for further studies for upcoming experiments. To perform the analyses of this work, we developed fast, accurate, and adaptable codes for cluster counts in the framework of the Numerical Cosmology Library.« less
8039374
Photometric Redshift Requirements for Self-Calibration of Cluster Dark Energy Studies
The ability to constrain dark energy from the evolution of galaxy cluster counts is limited by the imperfect knowledge of cluster redshifts. Ongoing and upcoming surveys will mostly rely on redshifts estimated from broadband photometry (photo-z's). For a Gaussian distribution for the cluster photo-z errors and a high cluster yield cosmology defined by the WMAP 1 year results, the photo-z bias, and scatter needs to be known better than 0.003 and 0.03, respectively, in order not to degrade dark energy constrains by more than 10% for a survey with specifications similar to the South Pole Telescope. Smaller surveys and cosmologies with lower cluster yields produce weaker photo-z requirements, though relative to worse baseline constraints. Comparable photo-z requirements are necessary in order to employ self-calibration techniques when solving for dark energy and observable-mass parameters simultaneously. On the other hand, self-calibration in combination with external mass inferences helps reduce photo-z requirements and provides important consistency checks for future cluster surveys. In our fiducial model, training sets with spectroscopic redshifts for ∼5%-15% of the detected clusters are required in order to keep degradations in the dark energy equation of state lower than 20%.
14272822
Nonlinear evolution of f(R) cosmologies. III. Halo statistics
The statistical properties of dark matter halos, the building blocks of cosmological observables associated with structure in the Universe, offer many opportunities to test models for cosmic acceleration, especially those that seek to modify gravitational forces. We study the abundance, bias, and profiles of halos in cosmological simulations for one such model: the modified action f(R) theory. The effects of f(R) modified gravity can be separated into a large- and small-field limit. In the large-field limit, which is accessible to current observations, enhanced gravitational forces raise the abundance of rare massive halos and decrease their bias but leave their (lensing) mass profiles largely unchanged. This regime is well described by scaling relations based on a modification of spherical collapse calculations. In the small-field limit, the enhancement of the gravitational force is suppressed inside halos and the effects on halo properties are substantially reduced for the most massive halos. Nonetheless, the scaling relations still retain limited applicability for the purpose of establishing conservative upper limits on the modification to gravity.
16976292
Self-calibration of cluster dark energy studies: Observable-mass distribution
The exponential sensitivity of cluster number counts to the properties of the dark energy implies a comparable sensitivity to not only the mean but also the actual distribution of an observable-mass proxy given the true cluster mass. For example a 25% scatter in mass can provide a $\ensuremath{\sim}50%$ change in the number counts at $z\ensuremath{\sim}2$ for the upcoming SPT survey. Uncertainty in the scatter of this amount would degrade dark energy constraints to uninteresting levels. Given the shape of the actual mass function, the properties of the distribution may be internally monitored by the shape of the observable mass function. As a proof of principle, for a simple mass-independent Gaussian distribution the scatter may be self-calibrated to allow a measurement of the dark energy equation of state of $\ensuremath{\sigma}(w)\ensuremath{\sim}0.1$. External constraints on the mass variance of the distribution that are more accurate than $\ensuremath{\Delta}{\ensuremath{\sigma}}_{\mathrm{ln}﻿M}^{2}l0.01$ at $z\ensuremath{\sim}1$ can further improve constraints by up to a factor of 2. More generally, cluster counts and their sample variance measured as a function of the observable provide internal consistency checks on the assumed form of the observable-mass distribution that will protect against misinterpretation of the dark energy constraints.