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Register a new userMeasuring equality horizon with the zero-crossing of the galaxy correlation function
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The size of the horizon at the matter-radiation equality is a key scale of the Big Bang cosmology that is directly related to the energy-matter content of the Universe. In this letter, we argue that this scale can be accurately measured from the observed clustering of galaxies in new large scale surveys. We demonstrate that the zero-crossing, r_c, of the 2-point galaxy correlation function is closely related to the horizon size at matter-radiation equality for a large variety of flat LCDM models. Using large-volume cosmological simulations, we also show that the pristine zero-crossing is unaltered by non-linear evolution of density fluctuations, redshift distortions and galaxy biases. This makes r_c a very powerful standard ruler that can be accurately measured, at a percent level, in upcoming experiments that will collect redshifts of millions of galaxies and quasars.
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The growth history of large-scale structure in the Universe is a powerful probe of the cosmological model, including the nature of dark energy. We study the growth rate of cosmic structure to redshift $z = 0.9$ using more than $162{,}000$ galaxy redshifts from the WiggleZ Dark Energy Survey. We divide the data into four redshift slices with effective redshifts $z = [0.2,0.4,0.6,0.76]$ and in each of the samples measure and model the 2-point galaxy correlation function in parallel and transverse directions to the line-of-sight. After simultaneously fitting for the galaxy bias factor we recover values for the cosmic growth rate which are consistent with our assumed $Lambda$CDM input cosmological model, with an accuracy of around 20% in each redshift slice. We investigate the sensitivity of our results to the details of the assumed model and the range of physical scales fitted, making close comparison with a set of N-body simulations for calibration. Our measurements are consistent with an independent power-spectrum analysis of a similar dataset, demonstrating that the results are not driven by systematic errors. We determine the pairwise velocity dispersion of the sample in a non-parametric manner, showing that it systematically increases with decreasing redshift, and investigate the Alcock-Paczynski effects of changing the assumed fiducial model on the results. Our techniques should prove useful for current and future galaxy surveys mapping the growth rate of structure using the 2-dimensional correlation function.
How much does the curvature perturbation change after it leaves the horizon, and when should one evaluate the power spectrum? To answer these questions we study single field inflation models numerically, and compare the evolution of different curvature perturbations from horizon crossing to the end of inflation. We find that e.g. in chaotic inflation, the amplitude of the comoving and the curvature perturbation on uniform density hypersurfaces differ by up to 180 % at horizon crossing assuming the same amplitude at the end of inflation, and that it takes approximately 3 efolds for the curvature perturbation to be within 1 % of its value at the end of inflation.
Supernova Ia magnitude surveys measure the dimensionless luminosity distance $H_{0}D_{L}$. However, from the distances alone one cannot obtain quantities like $H(z)$ or the dark energy equation of state, unless further cosmological assumptions are imposed. Here we show that by measuring the power spectrum of density contrast and of peculiar velocities of supernovae one can estimate also $H(z)/H_{0}$ regardless of background or linearly perturbed cosmology and of galaxy-matter bias. This method, dubbed Clustering of Standard Candles (CSC) also yields the redshift distortion parameter $beta(k,z)$ and the biased matter power spectrum in a model-independent way. We forecast that an optimistic (pessimistic) LSST may be able to constrain $H(z)/H_{0}$ to 5-13% (9-40%) in redshift bins of $Delta z=0.1$ up to at least $z=0.6$.
Supernovae arise from progenitor stars occupying the upper end of the initial mass function. Their extreme brightness allows individual massive stars to be detected at cosmic distances, lending supernovae great potential as tracers of the upper end of the IMF and its evolution. Exploiting this potential requires progress in many areas of supernova science. These include understanding the progenitor masses that produce various types of supernovae and accurately characterizing the supernova outburst and the environment in which it was produced. I present some preliminary work identifying the environmental conditions that produce the most luminous supernovae, believed to arise from stars with masses greater than 100 M_sun. I illustrate that the presence of these extreme supernovae in small star-forming dwarfs can be used to test our understanding of the upper end of the IMF.
Galaxy redshift surveys are one of the pillars of the current standard cosmological model and remain a key tool in the experimental effort to understand the origin of cosmic acceleration. To this end, the next generation of surveys aim at achieving sub-percent precision in the measurement of the equation of state of dark energy $w(z)$ and the growth rate of structure $f(z)$. This however requires comparable control over systematic errors, stressing the need for improved modelling methods. In this contribution we review at the introductory level some highlights of the work done in this direction by the {it Darklight} project. Supported by an ERC Advanced Grant, {it Darklight} developed novel techniques for clustering analysis, which were tested through numerical simulations before being finally applied to galaxy data as in particular those of the recently completed VIPERS redshift survey. We focus in particular on: (a) advances on estimating the growth rate of structure from redshift-space distortions; (b) parameter estimation through global Bayesian reconstruction of the density field from survey data; (c) impact of massive neutrinos on large-scale structure measurements. Overall, {it Darklight} has contributed to paving the way for forthcoming high-precision experiments, such as {it Euclid}, the next ESA cosmological mission.
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