4.1 Concepts and definitions of biasing

As discussed above, luminous objects, such as galaxies and quasars, are not direct tracers of the mass in the Universe. In fact, a difference of the spatial distribution between luminous objects and dark matter, or a bias, has been indicated from a variety of observations. Galaxy biasing clearly exists. The fact that galaxies of different types cluster differently (see, e.g., [16Jump To The Next Citation Point]) implies that not all of them are exact tracers of the underlying mass distribution (see also Section 6).

In order to confront theoretical model predictions for the mass distribution against observational data, one needs a relation of density fields of mass and luminous objects. The biasing of density peaks in a Gaussian random field is well formulated [37Jump To The Next Citation Point4Jump To The Next Citation Point], and it provides the first theoretical framework for the origin of galaxy density biasing. In this scheme, the galaxy-galaxy and mass-mass correlation functions are related in the linear regime via

2 ξgg(r) = bξmm (r), (116 )
where the biasing parameter b is a constant independent of scale r. However, a much more specific linear biasing model is often assumed in common applications, in which the local density fluctuation fields of galaxies and mass are assumed to be deterministically related via the relation
δg(x ) = bδm (x). (117 )
Note that Equation (116View Equation) follows from Equation (117View Equation), but the reverse is not true.

The above deterministic linear biasing is not based on a reasonable physical motivation. If b > 1, it must break down in deep voids because values of δg below − 1 are forbidden by definition. Even in the simple case of no evolution in comoving galaxy number density, the linear biasing relation is not preserved during the course of fluctuation growth. Non-linear biasing, where b varies with δm, is inevitable.

Indeed, an analytical model for biasing of halos on the basis of the extended Press–Schechter approximation [59Jump To The Next Citation Point] predicts that the biasing is nonlinear and provides a useful approximation for its behavior as a function of scale, time, and mass threshold. N-body simulations provide a more accurate description of the nonlinearity of the halo biasing confirming the validity of the Mo and White model [35103Jump To The Next Citation Point].

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