Clustering of dark matter tracers: generalizing bias for the coming era of precision LSS

By P. Mcdonald, A. Roy. 2009

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On very large scales, density fluctuations in the Universe are small, suggesting a perturbative model for large-scale clustering of galaxies (or other dark matter tracers), in which the galaxy density is written as a Taylor series in the local mass density, δ, with the unknown coefficients in the series treated as free ``bias'' parameters. We extend this model to include dependence of the galaxy density on the local values of ∇i∇j and ∇ivj, where is the potential and v is the peculiar velocity. We show that only two new free parameters are needed to model the power spectrum and bispectrum up to 4th order in the initial density perturbations, once symmetry considerations and equivalences between possible terms are accounted for. One of the new parameters is a bias multiplying sijsji, where sij = [∇i∇j∇−2−(1/3)δKij]δ. The other multiplies sijtji, where tij = [∇i∇j∇−2−(1/3)δKij](θ−δ), with θ = −(a H dln D/dln a)−1∇v. (There are other, observationally equivalent, ways to write the two terms, e.g., using θ−δ instead of sijsji.) We show how short-range (non-gravitational) non-locality can be included through a controlled series of higher derivative terms, starting with R2∇2δ, where R is the scale of non-locality (this term will be a small correction as long as k2R2 is small, where k is the observed wavenumber). We suggest that there will be much more information in future huge redshift surveys in the range of scales where beyond-linear perturbation theory is both necessary and sufficient than in the fully linear regime.

Subfields: Astronomy and Astrophysics, Nuclear and High Energy Physics

View Paper: https://www.semanticscholar.org/paper/ec2e628580e385a6be980bfe3b6f7025a9a6f52f

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In Astronomy and Astrophysics

  1. D. Schneider
  2. Daniel J. Eisenstein
  3. M. White
  4. Will J. Percival
  5. J. Brinkmann
  6. Simon D. M. White
  7. D. Weinberg
  8. L. Hernquist

In Nuclear and High Energy Physics

  1. L. Senatore
  2. M. White
  3. Daniel J. Eisenstein
  4. D. Baumann
  5. Will J. Percival
  6. K. Koyama
  7. M. Zaldarriaga
  8. D. Weinberg

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