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Michael Blanton

Publications and source records attributed to Michael Blanton.

42 records · Page 3Linked to original sources

How Stochastic is the Relative Bias Between Galaxy Types?

Examining the nature of the relative clustering of different galaxy types can help tell us how galaxies formed. To measure this relative clustering, I perform a joint counts-in-cells analysis of galaxies of different spectral types in the Las Campanas Redshift Survey (LCRS). I develop a maximum-likelihood technique to fit for the relationship between the density fields of early- and late-type galaxies. This technique can directly measure nonlinearity and stochasticity in the biasing relation. At high significance, a small amount of stochasticity is measured, corresponding to a correlation coefficient of about 0.87 on scales corresponding to 15 Mpc/h spheres. A large proportion of this signal appears to derive from errors in the selection function, and a more realistic estimate finds a correlation coefficient of about 0.95. These selection function errors probably account for the large stochasticity measured by Tegmark & Bromley (1999), and may have affected measurements of very large-scale structure in the LCRS. Analysis of the data and of mock catalogs shows that the peculiar geometry, variable flux limits, and central surface-brightness selection effects of the LCRS do not seem to cause the effect.

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Nonlinear and Stochastic Morphological Segregation

I perform a joint counts-in-cells analysis of galaxies of different spectral types using the Las Campanas Redshift Survey (LCRS). Using a maximum-likelihood technique to fit for the relationship between the density fields of early- and late-type galaxies, I find a relative linear bias of $b=0.76\pm 0.02$. This technique can probe the nonlinearity and stochasticity of the relationship as well. However, the degree to which nonlinear and stochastic fits improve upon the linear fit turns out to depend on the redshift range in question. In particular, there seems to be a systematic difference between the high- and low-redshift halves of the data (respectively, further than and closer than $cz\approx 36,000$ km/s); all of the signal of stochasticity and nonlinearity comes from the low-redshift portion. Analysis of mock catalogs shows that the peculiar geometry and variable flux limits of the LCRS do not cause this effect. I speculate that the central surface brightness selection criteria of the LCRS may be responsible.

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The Physical Origin of Scale Dependent Bias in Cosmological Simulations

Using large-scale hydrodynamic simulations with heuristic criteria for galaxy formation, we investigate how the galaxy field is related to the mass density and the gas temperature. We find that the bias b(R) = sigma_g(R)/sigma(R), where sigma_g(R) is the variance of galaxy counts in spheres of radius R and sigma(R) is the same for mass, varies from 2.6 at 1 h^{-1} Mpc to 1.2 at 30 h^{-1} Mpc. Including the dependence of the galaxy density on local gas temperature as well as on local mass density can fully account for this scale dependence. Galaxy density depends on temperature because gas which is too hot cannot cool to form galaxies; this causes scale dependence of b(R) because local gas temperature is related to the gravitational potential, and thus contains information about the large scale density field. We show that temperature dependence generally causes b(R) to vary on quasilinear and nonlinear scales, indicating that scale dependence of bias may be a generic effect in realistic galaxy formation scenarios. We find that the relationship between the galaxy and mass density fields is also a function of galaxy age. On large scales, the older galaxies are highly biased (b ~ 1.7) and highly correlated (r ~ 1.0) with the mass density field; younger galaxies are not biased (b ~ 0.8) and are poorly correlated (r ~ 0.5) with the mass. We argue that linear bias is inadequate to describe the relationship between galaxies and mass. (Abridged)

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Time Evolution of Galaxy Formation and Bias in Cosmological Simulations

The clustering of galaxies relative to the mass distribution declines with time because: first, nonlinear peaks become less rare events; second, the densest regions stop forming new galaxies because gas there becomes too hot to cool and collapse; third, after galaxies form, they are gravitationally ``debiased'' because their velocity field is the same as the dark matter. To show these effects, we perform a hydrodynamic cosmological simulation and examine the density field of recently formed galaxies as a function of redshift. We find the bias b_* of recently formed galaxies (the ratio of the rms fluctuations of these galaxies and mass), evolves from 4.5 at z=3 to around 1 at z=0, on 8 h^{-1} Mpc comoving scales. The correlation coefficient r_* between recently formed galaxies and mass evolves from 0.9 at z=3 to 0.25 at z=0. As gas in the universe heats up and prevents star formation, star-forming galaxies become poorer tracers of the mass density field. After galaxies form, the linear continuity equation is a good approximation to the gravitational debiasing, even on nonlinear scales. The most interesting observational consequence of the simulations is that the linear regression of the star-formation density field on the galaxy density field evolves from about 0.9 at z=1 to 0.35 at z=0. These effects also provide a possible explanation for the Butcher-Oemler effect, the excess of blue galaxies in clusters at redshift z ~ 0.5. Finally, we examine cluster mass-to-light ratio estimates of Omega, finding that while Omega(z) increases with z, one's estimate Omega_est(z) decreases. (Abridged)

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Large-Scale Flows As A Cosmological Probe

We review the use of peculiar velocities of galaxies as a probe of cosmological models. We put particular emphasis on comparison of the peculiar velocity and density fields, focussing on the discrepancies between various recent analyses. We discuss the limitations of the commonly used linear bias model, which may lie at the heart of some of the current controversies in the field.

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Constraining the Dark Matter Distribution With Large-Scale Structure Observations

We discuss the use of galaxies to trace the large-scale structure of the universe and thereby to make cosmological inferences. We put special emphasis on our lack of knowledge about the relative distribution of galaxies and the dynamically important dark matter. We end with a discussion of the increasing importance of infrared astronomy to large-scale structure studies.

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