On the equivalence between the effective cosmology and excursion set treatments of environment

Abstract

In studies of the environmental dependence of structure formation, the large scale environment is often thought of as providing an effective background cosmology: e.g. the formation of structure in voids is expected to be just like that in a less dense universe with appropriately modified Hubble and cosmological constants. However, in the excursion set description of structure formation which is commonly used to model this effect, no explicit mention is made of the effective cosmology. Rather, this approach uses the spherical evolution model to compute an effective linear theory growth factor, which is then used to predict the growth and evolution of nonlinear structures. We show that these approaches are, in fact, equivalent: a consequence of Birkhoff's theorem. We speculate that this equivalence will not survive in models where the gravitational force law is modified from an inverse square, potentially making the environmental dependence of clustering a good test of such models.

4 pages, 0 figures, accepted to MNRAS

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Cited by in corpus (17)

• Large-Scale Galaxy Bias
• Large scale bias and the inaccuracy of the peak-background split
• The Local Bias Model in the Large Scale Halo Distribution
• A halo bias function measured deeply into voids without stochasticity
• Separate Universe Consistency Relation and Calibration of Halo Bias
• Mapping stellar content to dark matter halos - III.Environmental dependence and conformity of galaxy colours
• Halo abundances within the cosmic web
• Measurement of the thermal Sunyaev-Zel'dovich effect around cosmic voids
• Cosmological N-Body Simulations with a Large-Scale Tidal Field
• Measuring the Tidal Response of Structure Formation: Anisotropic Separate Universe Simulations using TreePM
• Comparing halo bias from abundance and clustering
• Local Primordial Non-Gaussianities and Super-Sample Variance
• Halo abundances and shear in void models
• Baryon Acoustic Oscillations analyses with Density-Split Statistics
• Super sample covariance and the volume scaling of galaxy survey covariance matrices
• The Mass Function of Dark Halos in Superclusters and Voids
• Indicator Functions: Distilling the Information from Gaussian Random Fields