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In the Halo Model, galaxies are hosted by dark matter halos, while the halos themselves are biased tracers of the underlying matter distribution. Measurements of galaxy correlation functions include contributions both from galaxies in different halos, and from galaxies in the same halo (the so-called 1-halo terms). We show that, for highly biased tracers, the 1-halo term of the power spectrum obeys a steep scaling relation in terms of bias. We also show that the 1-halo term of the trispectrum has a steep scaling with bias. The steepness of these scaling relations is such that the 1-halo terms can become key contributions to the $n$-point correlation functions, even at large scales. We interpret these results through analytical arguments and semi-analytical calculations in terms of the statistical properties of halos., Comment: Matches version published on MNRAS. 12 pages, 8 figures

The Javalambre-Physics of the Accelerated Universe Astrophysical Survey (J-PAS) is a narrow band, very wide field Cosmological Survey to be carried out from the Javalambre Observatory in Spain with a purpose-built, dedicated 2.5m telescope and a 4.7 sq.deg. camera with 1.2Gpix. Starting in late 2015, J-PAS will observe 8500sq.deg. of Northern Sky and measure $0.003(1+z)$ photo-z for $9\times10^7$ LRG and ELG galaxies plus several million QSOs, sampling an effective volume of $\sim 14$ Gpc$^3$ up to $z=1.3$ and becoming the first radial BAO experiment to reach Stage IV. J-PAS will detect $7\times 10^5$ galaxy clusters and groups, setting constrains on Dark Energy which rival those obtained from its BAO measurements. Thanks to the superb characteristics of the site (seeing ~0.7 arcsec), J-PAS is expected to obtain a deep, sub-arcsec image of the Northern sky, which combined with its unique photo-z precision will produce one of the most powerful cosmological lensing surveys before the arrival of Euclid. J-PAS unprecedented spectral time domain information will enable a self-contained SN survey that, without the need for external spectroscopic follow-up, will detect, classify and measure $\sigma_z\sim 0.5\%$ redshifts for $\sim 4000$ SNeIa and $\sim 900$ core-collapse SNe. The key to the J-PAS potential is its innovative approach: a contiguous system of 54 filters with $145\AA$ width, placed $100\AA$ apart over a multi-degree FoV is a powerful "redshift machine", with the survey speed of a 4000 multiplexing low resolution spectrograph, but many times cheaper and much faster to build. The J-PAS camera is equivalent to a 4.7 sq.deg. "IFU" and it will produce a time-resolved, 3D image of the Northern Sky with a very wide range of Astrophysical applications in Galaxy Evolution, the nearby Universe and the study of resolved stellar populations., Comment: 215 pages, 70 figures. J-PAS "Red Book", containing a description of the technical aspects of the Survey and its main scientific goals

We investigate the non-linear evolution of Baryon Acoustic Oscillations (BAO) in the low-redshift matter power spectrum from the DEUS-FUR $\Lambda$CDM model simulation. This is the first cosmological N-body simulation encompassing the full observable cosmic volume, thus allowing cosmic variance limited predictions at BAO scales. We control the effect of numerical systematic errors using a series of large volume high-resolution simulations. The combined analysis allows us to measure the matter power spectrum between $z=0$ and $1$ to 1% over the entire BAO range, $0.03

We study the imprint of Dark Energy on the density profile of Dark Matter halos using a set of high-resolution large volume cosmological N-body simulations from the Dark Energy Universe Simulation Series (DEUSS). We first focus on the analysis of the goodness-of-fit of the Navarro-Frenk-White (NFW) profile which we find to vary with halo mass and redshift. We also find that the fraction of halos ill-fitted by NFW varies with cosmology, thus indicating that the mass assembly of halos with perturbed density profiles carries a characteristic signature of Dark Energy. To access this information independently of any parametric profile, we introduce a new observable quantity: the halo sparsity $s_\Delta$. This is defined as the mass ratio $M_{200}/M_\Delta$, i.e. the ratio of mass inside a sphere of radius $r_{200}$ to that contained within a radius $r_\Delta$, enclosing 200 and $\Delta$ times the mean matter density respectively. We find the average sparsity to be nearly independent of the total halo mass, while its value can be inferred to better than a few percent from the ratio of the integrated halo mass functions at overdensities $\Delta$ and 200 respectively. This provides a consistency relation that can validate observational measurements of the halo sparsity. Most importantly, the sparsity significantly varies with the underlying Dark Energy model, thus providing an alternative cosmological probe., Comment: 12 pages, 16 figures. accepted by MNRAS

Bayesian model selection methods provide a self-consistent probabilistic framework to test the validity of competing scenarios given a set of data. We present a case study application to strong gravitational lens parametric models. Our goal is to select a homogeneous lens subsample suitable for cosmological parameter inference. To this end we apply a Bayes factor analysis to a synthetic catalog of 500 lenses with power-law potential and external shear. For simplicity we focus on double-image lenses (the largest fraction of lens in the simulated sample) and select a subsample for which astrometry and time-delays provide strong evidence for a simple power-law model description. Through a likelihood analysis we recover the input value of the Hubble constant to within 3\sigma statistical uncertainty. We apply this methodology to a sample of double image lensed quasars. In the case of B1600+434, SBS 1520+530 and SDSS J1650+4251 the Bayes' factor analysis favors a simple power-law model description with high statistical significance. Assuming a flat \LambdaCDM cosmology, the combined likelihood data analysis of such systems gives the Hubble constant H_0=76+15-5 km/s/Mpc having marginalized over the lens model parameters, the cosmic matter density and consistently propagated the observational errors on the angular position of the images. The next generation of cosmic structure surveys will provide larger lens datasets and the method described here can be particularly useful to select homogeneous lens subsamples adapted to perform unbiased cosmological parameter inference, Comment: 13 pages; 13 figures; includes Bayesian analysis of a synthetic lens catalog generated with GRAVLENS, several additional results; matches MNRAS accepted version

We have performed the first-ever numerical N- body simulation of the full observable universe (DEUS "Dark Energy Universe Simulation" FUR "Full Universe Run"). This has evolved 550 billion particles on an Adaptive Mesh Refinement grid with more than two trillion computing points along the entire evolutionary history of the universe and across 6 order of magnitudes length scales, from the size of the Milky Way to that of the whole observable universe. To date, this is the largest and most advanced cosmological simulation ever run. It provides unique information on the formation and evolution of the largest structure in the universe and an exceptional support to future observational programs dedicated to mapping the distribution of matter and galaxies in the universe. The simulation has run on 4752 (of 5040) thin nodes of BULL supercomputer CURIE, using more than 300 TB of memory for 10 million hours of computing time. About 50 PBytes of data were generated throughout the run. Using an advanced and innovative reduction workflow the amount of useful stored data has been reduced to 500 TBytes., Comment: 12 pages, 15 figures, paper submitted to the Supercomputing 2012 Conference (Salt Lake City, November 10-16, 2012)

Over the past decade advancements in the understanding of several astrophysical phenomena have allowed us to infer a concordance cosmological model that successfully accounts for most of the observations of our universe. This has opened up the way to studies that aim to better determine the constants of the model and confront its predictions with those of competing scenarios. Here, we use strong gravitational lenses as cosmological probes. Strong lensing, as opposed to weak lensing, produces multiple images of a single source. Extracting cosmologically relevant information requires accurate modeling of the lens mass distribution, the latter being a galaxy or a cluster. To this purpose a variety of models are available, but it is hard to distinguish between them, as the choice is mostly guided by the quality of the fit to the data without accounting for the number of additional parameters introduced. However, this is a model selection problem rather than one of parameter fitting that we address in the Bayesian framework. Using simple test cases, we show that the assumption of more complicate lens models may not be justified given the level of accuracy of the data., Comment: 4 pages, proceeding for the SF2A conference

Strong gravitational lenses are unique cosmological probes. These produce multiple images of a single source. Whether a single galaxy, a group or a cluster, extracting cosmologically relevant information requires an accurate modeling of the lens mass distribution. A variety of models are available to this purpose, nevertheless discrimination between them as primarely relied on the quality of fit without accounting for the size of the prior model parameter space. This is a problem of model selection that we address in the Bayesian statistics framework by evaluating Bayes' factors. Using simple test cases, we show that the assumption of more complicate lens models may not be justified given the level of accuracy of the available data., Comment: Proceeding of the Statistical Challenges in Modern Astronomy V conference