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Register a new userMeasuring Dark Matter Substructure with Galaxy-Galaxy Flexion Statistics
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It is of great interest to measure the properties of substructures in dark matter halos at galactic and cluster scales. Here we suggest a method to constrain substructure properties using the variance of weak gravitational flexion in a galaxy-galaxy lensing context. We show the effectiveness of flexion variance in measuring substructures in N-body simulations of dark matter halos, and present the expected galaxy-galaxy lensing signals. We show the insensitivity of the method to the overall galaxy halo mass, and predict the methods signal-to-noise for a space-based all-sky survey, showing that the presence of substructure down to 10^9 M_odot halos can be reliably detected.
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Current theories of structure formation predict specific density profiles of galaxy dark matter haloes, and with weak gravitational lensing we can probe these profiles on several scales. On small scales, higher-order shape distortions known as flexion add significant detail to the weak lensing measurements. We present here the first detection of a galaxy-galaxy flexion signal in space-based data, obtained using a new Shapelets pipeline introduced here. We combine this higher-order lensing signal with shear to constrain the average density profile of the galaxy lenses in the Hubble Space Telescope COSMOS survey. We also show that light from nearby bright objects can significantly affect flexion measurements. After correcting for the influence of lens light, we show that the inclusion of flexion provides tighter constraints on density profiles than does shear alone. Finally we find an average density profile consistent with an isothermal sphere.
We compare subhalo mass and velocity functions obtained from different simulations with different subhalo finders among each other, and with predictions from the new semi-analytical model of Jiang & van den Bosch (2014). We find that subhalo mass functions (SHMFs) obtained using different subhalo finders agree with each other at the level of ~ 20 percent, but only at the low mass end. At the massive end, subhalo finders that identify subhaloes based purely on density in configuration space dramatically underpredict the subhalo abundances by more than an order of magnitude. These problems are much less severe for subhalo velocity functions (SHVFs), indicating that they arise from issues related to assigning masses to the subhaloes, rather than from detecting them. Overall the predictions from the semi-analytical model are in excellent agreement with simulation results obtained using the more advanced subhalo finders that use information in six dimensional phase-space. In particular, the model accurately reproduces the slope and host-mass-dependent normalization of both the subhalo mass and velocity functions. We find that the SHMFs and SHVFs have power-law slopes of 0.82 and 2.6, respectively, significantly shallower than what has been claimed in several studies in the literature.
We use the Copernicus Complexio (COCO) high resolution $N$-body simulations to investigate differences in the properties of small-scale structures in the standard cold dark matter (CDM) model and in a model with a cutoff in the initial power spectrum of density fluctuations consistent with both a thermally produced warm dark matter (WDM) particle or a sterile neutrino with mass 7 keV and leptogenesis parameter $L_6=8.7$. The latter corresponds to the coldest model with this sterile neutrino mass compatible with the identification of the recently detected 3.5 keV X-ray line as resulting from particle decay. CDM and WDM predict very different number densities of subhaloes with mass $leq 10^9,h^{-1},M_odot$ although they predict similar, nearly universal, normalised subhalo radial density distributions. Haloes and subhaloes in both models have cuspy NFW profiles, but WDM subhaloes below the cutoff scale in the power spectrum (corresponding to maximum circular velocities $V_{mathrm{max}}^{z=0} leq50~mathrm{kms}^{-1}$) are less concentrated than their CDM counterparts. We make predictions for observable properties using the GALFORM semi-analytic model of galaxy formation. Both models predict Milky Way satellite luminosity functions consistent with observations, although the WDM model predicts fewer very faint satellites. This model, however, predicts slightly more UV bright galaxies at redshift $z>7$ than CDM, but both are consistent with observations. Gravitational lensing offers the best prospect of distinguishing between the models.
We present a study of unprecedented statistical power regarding the halo-to-halo variance of dark matter substructure. Using a combination of N-body simulations and a semi-analytical model, we investigate the variance in subhalo mass fractions and subhalo occupation numbers, with an emphasis on how these statistics scale with halo formation time. We demonstrate that the subhalo mass fraction, f_sub, is mainly a function of halo formation time, with earlier forming haloes having less substructure. At fixed formation redshift, the average f_sub is virtually independent of halo mass, and the mass dependence of f_sub is therefore mainly a manifestation of more massive haloes assembling later. We compare observational constraints on f_sub from gravitational lensing to our model predictions and simulation results. Although the inferred f_sub are substantially higher than the median LCDM predictions, they fall within the 95th percentile due to halo-to-halo variance. We show that while the halo occupation distribution of subhaloes, P(N|M), is super-Poissonian for large <N>, a well established result, it becomes sub-Poissonian for <N> < 2. Ignoring the non-Poissonity results in systematic errors of the clustering of galaxies of a few percent, and with a complicated scale- and luminosity-dependence. Earlier-formed haloes have P(N|M) closer to a Poisson distribution, suggesting that the dynamical evolution of subhaloes drives the statistics towards Poissonian. Contrary to a recent claim, the non-Poissonity of subhalo occupation statistics does not vanish by selecting haloes with fixed mass and fixed formation redshift. Finally, we use subhalo occupation statistics to put loose constraints on the mass and formation redshift of the Milky Way halo. Using observational constraints on the V_max of the most massive satellites, we infer that 0.25<M_vir/10^12M_sun/h<1.4 and 0.1<z_f<1.4 at 90% confidence.
We develop a statistical method to measure the interaction cross-section of Dark Matter, exploiting the continuous minor merger events in which small substructures fall into galaxy clusters. We find that by taking the ratio of the distances between the galaxies and Dark Matter, and galaxies and gas in accreting sub-halos, we form a quantity that can be statistically averaged over a large sample of systems whilst removing any inherent line-of-sight projections. In order to interpret this ratio as a cross-section of Dark Matter we derive an analytical description of sub-halo infall which encompasses; the force of the main cluster potential, the drag on a gas sub-halo, a model for Dark Matter self-interactions and the resulting sub-halo drag, the force on the gas and galaxies due to the Dark Matter sub-halo potential, and finally the buoyancy on the gas and Dark Matter. We create mock observations from cosmological simulations of structure formation and find that collisionless Dark Matter becomes physically separated from X-ray gas by up to 20h^-1 kpc. Adding realistic levels of noise, we are able to predict achievable constraints from observational data. Current archival data should be able to detect a difference in the dynamical behaviour of Dark Matter and standard model particles at 6 sigma, and measure the total interaction cross-section sigma/m with 68% confidence limits of +/- 1cm2g^-1. We note that this method is not restricted by the limited number of major merging events and is easily extended to large samples of clusters from future surveys which could potentially push statistical errors to 0.1cm^2g^-1.
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