Shankar Agarwal

The effect of massive neutrinos on the matter power spectrum

We investigate the impact of massive neutrinos on the distribution of matter in the semi-non-linear regime (0:1 < k < 0:6hMpc 1 ). We present a suite of large-scale N body simulations quantifying the scale dependent suppression of the total matter power spectrum, resulting from the free-streaming of massive neutrinos out of highdensity regions. Our simulations show a power suppression of 3:5 90 per cent at k 0:6hMpc 1 for total neutrino mass, m = 0:05 1:9 eV respectively. We also discuss the precision levels that future cosmological datasets would have to achieve in order to distinguish the normal and inverted neutrino mass hierarchies.

Power spectrum estimation from peculiar velocity catalogues

The peculiar velocities of galaxies are an inherently valuable cosmological probe, pro- viding an unbiased estimate of the distribution of matter on scales much larger than the depth of the survey. Much research interest has been motivated by the high dipole moment of our local peculiar velocity field, which suggests a large scale excess in the matter power spectrum, and can appear to be in some tension with theCDM model. We use a composite catalogue of 4,537 peculiar velocity measurements with a characteristic depth of 33 h 1 Mpc to estimate the matter power spectrum. We compare the constraints with this method, directly studying the full peculiar velocity catalogue, to results from Macaulay et al. (2011), studying minimum variance mo- ments of the velocity field, as calculated by Watkins, Feldman & Hudson (2009) and Feldman, Watkins & Hudson (2010). We find good agreement with theCDM model on scales of k > 0.01 h Mpc 1 . We find an excess of power on scales of k < 0.01 h Mpc 1 , although with a 1σ uncertainty which includes theCDM model. We find that the uncertainty in the excess at these scales is larger than an alternative result studying only moments of the velocity field, which is due to the minimum variance weights used to calculate the moments. At small scales, we are able to clearly discrimi- nate between linear and nonlinear clustering in simulated peculiar velocity catalogues, and find some evidence (although less clear) for linear clustering in the real peculiar velocity data.

Constraints on dark matter scenarios from measurements of the galaxy luminosity function at high redshifts

We use state-of-the-art measurements of the galaxy luminosity function (LF) at z=6, 7, and 8 to derive constraints on warm dark matter (WDM), late-forming dark matter, and ultralight axion dark matter models alternative to the cold dark matter (CDM) paradigm. To this purpose, we have run a suite of high-resolution N-body simulations to accurately characterize the low-mass end of the halo mass function and derive dark matter (DM) model predictions of the high-z luminosity function. In order to convert halo masses into UV magnitudes, we introduce an empirical approach based on halo abundance matching, which allows us to model the LF in terms of the amplitude and scatter of the ensemble average star formation rate halo mass relation, ⟨SFR(Mh,z)⟩, of each DM model. We find that, independent of the DM scenario, the average SFR at fixed halo mass increases from z=6 to 8, while the scatter remains constant. At halo mass Mh≳1012 M⊙  h−1, the average SFR as a function of halo mass follows a double power law trend that is common to all models, while differences occur at smaller masses. In particular, we find that models with a suppressed low-mass halo abundance exhibit higher SFR compared to the CDM results. Thus, different DM models predict a different faint-end slope of the LF which causes the goodness of fit to vary within each DM scenario for different model parameters. Using deviance statistics, we obtain a lower limit on the WDM thermal relic particle mass, mWDM≳1.5  keV at 2σ. In the case of LFDM models, the phase transition redshift parameter is bounded to zt≳8×105 at 2σ. We find ultralight axion dark matter best-fit models with axion mass ma≳1.6×10-22  eV to be well within 2σ of the deviance statistics. We remark that measurements at z=6 slightly favor a flattening of the LF at faint UV magnitudes. This tends to prefer some of the non-CDM models in our simulation suite, although not at a statistically significant level to distinguish them from CDM.

pkann – II. A non-linear matter power spectrum interpolator developed using artificial neural networks

This is the published version. Copyright

Testing the minimum variance method for estimating large-scale velocity moments

The estimation and analysis of large-scale bulk flow moments of peculiar velocity surveys is complicated by non-spherical survey geometry, the non-uniform sampling of the matter velocity field by the survey objects and the typically large measurement errors of the measured line-of-sight velocities. Previously, we have developed an optimal ‘minimum variance’ (MV) weighting scheme for using peculiar velocity data to estimate bulk flow moments for idealized, dense and isotropic surveys with Gaussian radial distributions, that avoids many of these complications. These moments are designed to be easy to interpret and are comparable between surveys. In this paper, we test the robustness of our MV estimators using numerical simulations. Using MV weights, we estimate the bulk flow moments for various mock catalogues extracted from the LasDamas and the Horizon Run numerical simulations and compare these estimates to the moments calculated directly from the simulation boxes. We show that the MV estimators are unbiased and negligibly affected by non-linear flows.

Structural properties of artificial halos in nonstandard dark matter simulations

Artificial fragmentation of the matter density field causes the formation of spurious groups of particles in N-body simulations of non-standard Dark Matter (DM) models which are characterized by a small scale cut-off in the linear matter power spectrum. These spurious halos alter the prediction of the mass function in a range of masses where differences among DM models are most relevant to observational tests. Using a suite of high resolution simulations we show that the contamination of artificial groups of particles significantly affect the statistics of halo spin, shape and virial state parameters. We find that spurious halos have systematically larger spin values, are highly elliptical or prolate and significantly deviate from virial equilibrium. These characteristics allow us to detect the presence of spurious halos even in non-standard DM models for which the low-mass end of the mass function remains well behaved. We show that selecting halos near the virial equilibrium provides a simple and effective method to remove the bulk of spurious halos from numerical halo catalogs and consistently recover the halo mass function at low masses.

The cosmic Mach number: comparison from observations, numerical simulations and non-linear predictions

We calculate the cosmic Mach number M – the ratio of the bulk flow of the velocity field on scale R to the velocity dispersion within regions of scale R. M is effectively a measure of the ratio of large-scale to small-scale power and can be a useful tool to constrain the cosmological parameter space. Using a compilation of existing peculiar velocity surveys, we calculate M and compare it to that estimated from mock catalogues extracted from the Large Suite of Dark