Galaxy Bias and from Counts in Cells from the SDSS Main Sample
arXiv:2006.01146 · doi:10.1093/mnrasl/slaa139
Abstract
The counts-in-cells (CIC) galaxy probability distribution depends on both the dark matter clustering amplitude and the galaxy bias . We present a theory for the CIC distribution based on a previous prescription of the underlying dark matter distribution and a linear volume transformation to redshift space. We show that, unlike the power spectrum, the CIC distribution breaks the degeneracy between and on scales large enough that both bias and redshift distortions are still linear; thus we obtain a simultaneous fit for both parameters. We first validate the technique on the Millennium Simulation and then apply it to the SDSS Main Galaxy Sample. We find and , consistent with previous complementary results from redshift distortions and from Planck.
5 pages, 3 figures; submitted to MNRAS
References in corpus (5)
- The Clustering of the SDSS DR7 Main Galaxy Sample I: A 4 per cent Distance Measure at z=0.15
- The Clustering of the SDSS Main Galaxy Sample II: Mock galaxy catalogues and a measurement of the growth of structure from Redshift Space Distortions at
- The recycling of gas and metals in galaxy formation: predictions of a dynamical feedback model
- A question of separation: disentangling tracer bias and gravitational nonlinearity with counts-in-cells statistics
- Empirical Validation of the Ising Galaxy Bias Model