THE LARGE-SCALE BIAS OF DARK MATTER HALOS: NUMERICAL CALIBRATION AND MODEL TESTS
University of California, Berkeley · California Institute of Technology · +5 more institutions
Abstract
We measure the clustering of dark matter halos in a large set of collisionless cosmological simulations of the flat \nΛCDM cosmology. Halos are identified using the spherical overdensity algorithm, which finds the mass around \nisolated peaks in the density field such that the mean density is Δ times the background. We calibrate fitting functions \nfor the large-scale bias that are adaptable to any value of Δ we examine. We find a ~6% scatter about our best-fit \nbias relation. Our fitting functions couple to the halo mass functions of Tinker et al. such that the bias of all dark \nmatter is normalized to unity. We demonstrate that the bias of massive, rare halos is higher than that…
Citation impact
- FWCI
- 21.48
- Percentile
- 100%
- References
- 68
Authors
7- JLJeremy L. TinkerCorresponding
University of California, Berkeley
- BEBrant E. Robertson
California Institute of Technology
- AVAndrey V. Kravtsov
Fermi National Accelerator Laboratory, University of Chicago
- AKAnatoly Klypin
New Mexico State University
- MSMichael S. Warren
Los Alamos National Laboratory
Topics & keywords
- Halo
- Dark matter
- Halo effect
- Measure (data warehouse)
- Dark matter halo
- Cluster analysis
- Function (biology)
- Field (mathematics)