61 research outputs found

    DEMNUni: Massive neutrinos and the bispectrum of large scale structures

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    The main effect of massive neutrinos on the large-scale structure consists in a few percent suppression of matter perturbations on all scales below their free-streaming scale. Such effect is of particular importance as it allows to constraint the value of the sum of neutrino masses from measurements of the galaxy power spectrum. In this work, we present the first measurements of the next higher-order correlation function, the bispectrum, from N-body simulations that include massive neutrinos as particles. This is the simplest statistics characterising the non-Gaussian properties of the matter and dark matter halos distributions. We investigate, in the first place, the suppression due to massive neutrinos on the matter bispectrum, comparing our measurements with the simplest perturbation theory predictions, finding the approximation of neutrinos contributing at quadratic order in perturbation theory to provide a good fit to the measurements in the simulations. On the other hand, as expected, a linear approximation for neutrino perturbations would lead to O(fÎœf_{\nu}) errors on the total matter bispectrum at large scales. We then attempt an extension of previous results on the universality of linear halo bias in neutrino cosmologies, to non-linear and non-local corrections finding consistent results with the power spectrum analysis.Comment: 22 pages, 11 figure

    Optimal Redshift Weighting For Redshift Space Distortions

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    The low statistical errors on cosmological parameters promised by future galaxy surveys will only be realised with the development of new, fast, analysis methods that reduce potential systematic problems to low levels. We present an efficient method for measuring the evolution of the growth of structure using Redshift Space Distortions (RSD), that removes the need to make measurements in redshift shells. We provide sets of galaxy-weights that cover a wide range in redshift, but are optimised to provide differential information about cosmological evolution. These are derived to optimally measure the coefficients of a parameterisation of the redshift-dependent matter density, which provides a framework to measure deviations from the concordance Λ\LambdaCDM cosmology, allowing for deviations in both geometric and/or growth. We test the robustness of the weights by comparing with alternative schemes and investigate the impact of galaxy bias. We extend the results to measure the combined anisotropic Baryon Acoustic Oscillation (BAO) and RSD signals.Comment: 10 pages, 5 figures, submitted to MNRA

    Testing modified gravity scenarios with direct peculiar velocities

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    The theoretical basis of dark energy remains unknown and could signify a need to modify the laws of gravity on cosmological scales. In this study we investigate how the clustering and motions of galaxies can be used as probes of modified gravity theories, using galaxy and direct peculiar velocity auto- and cross-correlation functions. We measure and fit these correlation functions in simulations of Λ\LambdaCDM, DGP, and f(R)f(R) cosmologies and, by extracting the characteristic parameters of each model, we show that these theories can be distinguished from General Relativity using these measurements. We present forecasts showing that with sufficiently large data samples, this analysis technique is a competitive probe that can help place limits on allowed deviations from GR. For example, a peculiar velocity survey reaching to z=0.5z=0.5 with 20%20\% distance accuracy would constrain model parameters to 3-σ\sigma confidence limits log⁥10∣fR0∣2.88 c/H0\log_{10}|f_{R0}| 2.88 \, c/H_0 for nDGP, assuming a fiducial GR model.Comment: 13 pages, 12 figures, 3 tables, accepted for publication in MNRA

    Cross-correlating radial peculiar velocities and CMB lensing convergence

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    We study, for the first time, the cross correlation between the angular distribution of radial peculiar velocities (PV) and the lensing convergence of cosmic microwave background (CMB) photons. We derive theoretical expectations for the signal and its covariance and assess its detectability with existing and forthcoming surveys. We find that such cross-correlations are expected to improve constraints on different gravitational models by partially breaking degeneracies with the matter density. We identify in the distance-scaling dispersion of the peculiar velocities the most relevant source of noise in the cross correlation. For this reason, we also study how the above picture changes assuming a redshift-independent scatter for the PV, obtained for example using a reconstruction technique. Our results show that the cross correlation might be detected in the near future combining PV measurements from DESI and the convergence map from CMB-S4. Using realistic direct PV measurements we predict a cumulative signal-to-noise ratio of approximately 3.8σ3.8 \sigma using data on angular scales 3≀ℓ≀2003 \leq \ell \leq 200. For an idealized reconstructed peculiar velocity map extending up to redshift z=0.15z=0.15 and a smoothing scale of 44 Mpc h−1h^{-1} we predict a cumulative signal-to-noise ratio of approximately 27σ 27 \sigma from angular scales 3≀ℓ≀2003 \leq \ell \leq200 . We conclude that currently reconstructed peculiar velocities have more constraining power than directly observed ones, even though they are more cosmological-model dependent.Comment: 20 pages plus references, 5 figures. Comments are welcom

    Redshift-weighted constraints on primordial non-Gaussianity from the clustering of the eBOSS DR14 quasars in Fourier space

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    We present constraints on local primordial non-Gaussianity (PNG), parametrized through fNLlocf^{\rm loc}_{\rm NL}, using the Sloan Digital Sky Survey IV extended Baryon Oscillation Spectroscopic Survey Data Release 14 quasar sample. We measure and analyze the anisotropic clustering of the quasars in Fourier space, testing for the scale-dependent bias introduced by primordial non-Gaussianity on large scales. We derive and employ a power spectrum estimator using optimal weights that account for the redshift evolution of the PNG signal. We find constraints of −51<fNLloc<21-51<f^{\rm loc}_{\rm NL}<21 at 95% confidence level. These are amont the tightest constraints from Large Scale Structure (LSS) data. Our redshift weighting improves the error bar by 15% in comparison to the unweighted case. If quasars have lower response to PNG, the constraint degrades to −81<fNLloc<26-81<f^{\rm loc}_{\rm NL}<26, with a 40% improvement over the standard approach. We forecast that the full eBOSS dataset could reach σfNLloc≃5-8\sigma_{f^{\rm loc}_{\rm NL}}\simeq 5\text{-}8 using optimal methods and full range of scales.Comment: 28 pages, 12 figures. Comments welcome

    The extended Baryon Oscillation Spectroscopic Survey (eBOSS):testing a new approach to measure the evolution of the structure growth

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    International audienceThe extended Baryon Oscillation Spectroscopic Survey (eBOSS) is one of the first of a new generation of galaxy redshift surveys that will cover a large range in redshift with sufficient resolution to measure the baryon acoustic oscillations signal. For surveys covering a large redshift range we can no longer ignore cosmological evolution, meaning that either the redshift shells analysed have to be significantly narrower than the survey, or we have to allow for the averaging over evolving quantities. Both of these have the potential to remove signal: analysing small volumes increases the size of the Fourier window function, reducing the large-scale information, while averaging over evolving quantities can, if not performed carefully, remove differential information. It will be important to measure cosmological evolution from these surveys to explore and discriminate between models. We apply a method to optimally extract this differential information to mock catalogues designed to mimic the eBOSS quasar sample. By applying a set of weights to extract redshift-space distortion measurements as a function of redshift, we demonstrate an analysis that does not invoke the problems discussed above. We show that our estimator gives unbiased constraints
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