Aims. Using the VIMOS Public Extragalactic Redshift Survey (VIPERS) we aim to jointly estimate the key parameters that describe the galaxy density field and its spatial correlations in redshift space. Methods. We use the Bayesian formalism to jointly
reconstruct the redshift-space galaxy density field, power spectrum, galaxy bias and galaxy luminosity function given the observations and survey selection function. The high-dimensional posterior distribution is explored using the Wiener filter within a Gibbs sampler. We validate the analysis using simulated catalogues and apply it to VIPERS data taking into consideration the inhomogeneous selection function. Results. We present joint constraints on the anisotropic power spectrum as well as the bias and number density of red and blue galaxy classes in luminosity and redshift bins as well as the measurement covariances of these quantities. We find that the inferred galaxy bias and number density parameters are strongly correlated although these are only weakly correlated with the galaxy power spectrum. The power spectrum and redshift-space distortion parameters are in agreement with previous VIPERS results with the value of the growth rate $fsigma_8 = 0.38$ with 18% uncertainty at redshift 0.7.
We compare three methods to measure the count-in-cell probability density function of galaxies in a spectroscopic redshift survey. From this comparison we found that when the sampling is low (the average number of object per cell is around unity) it
is necessary to use a parametric method to model the galaxy distribution. We used a set of mock catalogues of VIPERS, in order to verify if we were able to reconstruct the cell-count probability distribution once the observational strategy is applied. We find that in the simulated catalogues, the probability distribution of galaxies is better represented by a Gamma expansion than a Skewed Log-Normal. Finally, we correct the cell-count probability distribution function from the angular selection effect of the VIMOS instrument and study the redshift and absolute magnitude dependency of the underlying galaxy density function in VIPERS from redshift $0.5$ to $1.1$. We found very weak evolution of the probability density distribution function and that it is well approximated, independently from the chosen tracers, by a Gamma distribution.
[Abridged] Non-uniform sampling and gaps in sky coverage are common in galaxy redshift surveys, but these effects can degrade galaxy counts-in-cells and density estimates. We carry out a comparison of methods that aim to fill the gaps to correct for
the systematic effects. Our study is motivated by the analysis of the VIMOS Extragalactic Redshift Survey (VIPERS), a flux-limited survey (i<22.5) based on one-pass observations with VIMOS, with gaps covering 25% of the surveyed area and a mean sampling rate of 35%. Our findings are applicable to other surveys with similar observing strategies. We compare 1) two algorithms based on photometric redshift, that assign redshifts to galaxies based on the spectroscopic redshifts of the nearest neighbours, 2) two Bayesian methods, the Wiener filter and the Poisson-Lognormal filter. Using galaxy mock catalogues we quantify the accuracy of the counts-in-cells measurements on scales of R=5 and 8 Mpc/h after applying each of these methods. We also study how they perform to account for spectroscopic redshift error and inhomogeneous and sparse sampling rate. We find that in VIPERS the errors in counts-in-cells measurements on R<10 Mpc/h scales are dominated by the sparseness of the sample. All methods underpredict by 20-35% the counts at high densities. This systematic bias is of the same order as random errors. No method outperforms the others. Random and systematic errors decrease for larger cells. We show that it is possible to separate the lowest and highest densities on scales of 5 Mpc/h at redshifts 0.5<z<1.1, over a large volume such as in VIPERS survey. This is vital for the characterisation of cosmic variance and rare populations (e.g, brightest galaxies) in environmental studies at these redshifts.
We investigate the dependence of galaxy clustering on luminosity and stellar mass in the redshift range 0.5<z<1.1, using the first ~55000 redshifts from the VIMOS Public Extragalactic Redshift Survey (VIPERS). We measured the redshift-space two-point
correlation functions (2PCF), and the projected correlation function, in samples covering different ranges of B-band absolute magnitudes and stellar masses. We considered both threshold and binned galaxy samples, with median B-band absolute magnitudes -21.6<MB-5log(h)<-19.5 and median stellar masses 9.8<log(M*[Msun/h^2])<10.7. We assessed the real-space clustering in the data from the projected correlation function, which we model as a power law in the range 0.2<r_p[Mpc/h]<20. Finally, we estimated the galaxy bias as a function of luminosity, stellar mass, and redshift, assuming a flat LCDM model to derive the dark matter 2PCF. We provide the best-fit parameters of the power-law model assumed for the real-space 2PCF -- the correlation length and the slope -- as well as the linear bias parameter, as a function of the B-band absolute magnitude, stellar mass, and redshift. We confirm and provide the tightest constraints on the dependence of clustering on luminosity at 0.5<z<1.1. We prove the complexity of comparing the clustering dependence on stellar mass from samples that are originally flux-limited and discuss the possible origin of the observed discrepancies. Overall, our measurements provide stronger constraints on galaxy formation models, which are now required to match, in addition to local observations, the clustering evolution measured by VIPERS galaxies between z=0.5 and z=1.1 for a broad range of luminosities and stellar masses.
We assess the possibility to detect and characterize the physical state of the missing baryons at low redshift by analyzing the X-ray absorption spectra of the Gamma Ray Burst [GRB] afterglows, measured by a micro calorimeters-based detector with 3 e
V resolution and 1000 cm2 effective area and capable of fast re-pointing, similar to that on board of the recently proposed X-ray satellites EDGE and XENIA. For this purpose we have analyzed mock absorption spectra extracted from different hydrodynamical simulations used to model the properties of the Warm Hot Intergalactic Medium [WHIM]. These models predict the correct abundance of OVI absorption lines observed in UV and satisfy current X-ray constraints. According to these models space missions like EDGE and XENIA should be able to detect about 60 WHIM absorbers per year through the OVII line. About 45 % of these have at least two more detectable lines in addition to OVII that can be used to determine the density and the temperature of the gas. Systematic errors in the estimates of the gas density and temperature can be corrected for in a robust, largely model-independent fashion. The analysis of the GRB absorption spectra collected in three years would also allow to measure the cosmic mass density of the WHIM with about 15 % accuracy, although this estimate depends on the WHIM model. Our results suggest that GRBs represent a valid, if not preferable, alternative to Active Galactic Nuclei to study the WHIM in absorption. The analysis of the absorption spectra nicely complements the study of the WHIM in emission that the spectrometer proposed for EDGE and XENIA would be able to carry out thanks to its high sensitivity and large field of view.
We present results from the first high-resolution hydrodynamical simulations of non-Gaussian cosmological models. We focus on the statistical properties of the transmitted Lyman-alpha flux in the high redshift intergalactic medium. Imprints of non-Ga
ussianity are present and are larger at high redshifts. Differences larger than 20 % at z>3 in the flux probability distribution function for high transmissivity regions (voids) are expected for values of the non linearity parameter f_NL=pm 100 when compared to a standard LCDM cosmology with f_NL=0. We investigate also the one-dimensional flux bispectrum: at the largest scales (corresponding to tens of Mpc) we expect deviations in the flux bispectrum up to 20% at z~4 (for f_NL=pm 100), significantly larger than deviations of ~ 3% in the flux power spectrum. We briefly discuss possible systematic errors that can contaminate the signal. Although challenging, a detection of non-Gaussianities in the interesting regime of scales and redshifts probed by the Lyman-alpha forest, could be possible with future data sets.
We model the cosmological co-evolution of galaxies and their central supermassive black holes (BHs) within a semi-analytical framework developed on the outputs of the Millennium Simulation (Croton et al., 2006; De Lucia & Blaizot, 2007). In this work
, we analyze the model BH scaling relations, fundamental plane and mass function, and compare them with the most recent observational data. Furthermore, we extend the original code developed by Croton et al. (2006) to follow the evolution of the BH mass accretion and its conversion into radiation, and compare the derived AGN bolometric luminosity function with the observed one. We find, for the most part, a very good agreement between predicted and observed BH properties. Moreover, the model is in good agreement with the observed AGN number density in 0<z<5, provided it is assumed that the cold gas fraction accreted by BHs at high redshifts is larger than at low redshifts (Marulli et al., 2008).
In this work we study the properties of the mass density field in the non-Gaussian world models simulated by Grossi et al. 2007. In particular we focus on the one-point density probability distribution function of the mass density field in non-Gausia
n models with quadratic non-linearities quantified by the usual parameter f_NL. We find that the imprints of primordial non-Gaussianity are well preserved in the negative tail of the probability function during the evolution of the density perturbation. The effect is already noticeable at redshifts as large as 4 and can be detected out to the present epoch. At z=0 we find that the fraction of the volume occupied by regions with underdensity delta < -0.9, typical of voids, is about 1.3 per cent in the Gaussian case and increases to ~2.2 per cent if f_NL=-1000 while decreases to ~0.5 per cent if f_NL=+1000. This result suggests that void-based statistics may provide a powerful method to detect non-Gaussianity even at low redshifts which is complementary to the measurements of the higher-order moments of the probability distribution function like the skewness or the kurtosis for which deviations from the Gaussian case are detected at the 25-50 per cent level.
Upcoming $gamma$-ray satellites will search for Dark Matter annihilations in Milky Way substructures (or clumps). The prospects for detecting these objects strongly depend on the assumptions made on the distribution of Dark Matter in substructures, a
nd on the distribution of substructures in the Milky Way halo. By adopting simplified, yet rather extreme, prescriptions for these quantities, we compute the number of sources that can be detected with upcoming experiments such as GLAST, and show that, for the most optimistic particle physics setup ($m_chi=40$ GeV and annihilation cross section $sigma v = 3 times 10^{-26}$ cm$^3$ s$^{-1}$), the result ranges from zero to $sim$ hundred sources, all with mass above $10^{5}Modot$. However, for a fiducial DM candidate with mass $m_chi=100$ GeV and $sigma v = 10^{-26}$ cm$^3$ s$^{-1}$, at most a handful of large mass substructures can be detected at $5 sigma$, with a 1-year exposure time, by a GLAST-like experiment. Scenarios where micro-clumps (i.e. clumps with mass as small as $10^{-6}Modot$) can be detected are severely constrained by the diffuse $gamma$-ray background detected by EGRET.
We have performed high-resolution cosmological N-body simulations of a concordance LCDM model to study the evolution of virialized, dark matter haloes in the presence of primordial non-Gaussianity. Following a standard procedure, departures from Gaus
sianity are modeled through a quadratic Gaussian term in the primordial gravitational potential, characterized by a dimensionless non-linearity strength parameter f_NL. We find that the halo mass function and its redshift evolution closely follow the analytic predictions of Matarrese et al.(2000). The existence of precise analytic predictions makes the observation of rare, massive objects at large redshift an even more attractive test to detect primordial non-Gaussian features in the large scale structure of the universe.
