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The bias of dark matter tracers: assessing the accuracy of mapping techniques

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 Added by Marcos Pellejero
 Publication date 2019
  fields Physics
and research's language is English




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We present a comparison between approximated methods for the construction of mock catalogs based on the halo-bias mapping technique. To this end, we use as reference a high resolution $N$-body simulation of 3840$^3$ dark matter particles on a 400$h^{-1}rm{Mpc}$ cube box from the Multidark suite. In particular, we explore parametric versus non-parametric bias mapping approaches and compare them at reproducing the halo distribution in terms of the two and three point statistics down to $sim 10^8,{rm M}_{odot},h^{-1}$ halo masses. Our findings demonstrate that the parametric approach remains inaccurate even including complex deterministic and stochastic components. On the contrary, the non-parametric one is indistinguishable from the reference $N$-body calculation in the power-spectrum beyond $k=1,h,{rm Mpc}^{-1}$, and in the bispectrum for typical configurations relevant to baryon acoustic oscillation analysis. We conclude, that approaches which extract the full bias information from $N$-body simulations in a non-parametric fashion are ready for the analysis of the new generation of large scale structure surveys.

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62 - G. Pollina , N. Hamaus , K. Paech 2018
Luminous tracers of large-scale structure are not entirely representative of the distribution of mass in our Universe. As they arise from the highest peaks in the matter density field, the spatial distribution of luminous objects is biased towards those peaks. On large scales, where density fluctuations are mild, this bias simply amounts to a constant offset in the clustering amplitude of the tracer, known as linear bias. In this work we focus on the relative bias between galaxies and galaxy clusters that are located inside and in the vicinity of cosmic voids, extended regions of relatively low density in the large-scale structure of the Universe. With the help of hydro-dynamical simulations we verify that the relation between galaxy and cluster overdensity around voids remains linear. Hence, the void-centric density profiles of different tracers can be linked by a single multiplicative constant. This amounts to the same value as the relative linear bias between tracers for the largest voids in the sample. For voids of small sizes, which typically arise in higher density regions, this constant has a higher value, possibly showing an environmental dependence similar to that observed for the linear bias itself. We confirm our findings by analysing mocks and data obtained during the first year of observations by the Dark Energy Survey. As a side product, we present the first catalogue of three-dimensional voids extracted from a photometric survey with a controlled photo-z uncertainty. Our results will be relevant in forthcoming analyses that attempt to use voids as cosmological probes.
130 - J. Billard 2011
There is a worldwide effort toward the development of a large TPC (Time Projection Chamber) devoted to directional Dark Matter detection. All current projects are being designed to fulfill a unique goal : identifying weakly interacting massive particle (WIMP) as such by taking advantage of the expected direction dependence of WIMP-induced events toward the constellation Cygnus. However such proof of discovery requires a careful statistical data treatment. In this paper, the discovery potential of forthcoming directional detectors is adressed by using a frequentist approach based on the profile likelihood ratio test statistic. This allows us to estimate the expected significance of a Dark Matter detection. Moreover, using this powerful test statistic, it is possible to propagate astrophysical and experimental uncertainties in the determination of the discovery potential of a given directional detection experiment. This way, we found that a 30 kg.year CF$_4$ directional experiment could reach a 3$sigma$ sensitivity at 90% C.L. down to $10^{-5}$ pb and $3.10^{-4}$ pb for the WIMP-proton axial cross section in the most optimistic and pessimistic scenario respectively.
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