Abstract:We present the measurements and modelling of the projected and redshift-space clustering of CMASS galaxies in the Sloan Digital Sky Survey-III Baryon Oscillation Spectroscopic Survey Data Release 11. For a volume-limited luminous red galaxy sample in the redshift range of 0.48 < z < 0.55, we perform halo occupation distribution modelling of the smalland intermediate-scale (0.1-60 h −1 Mpc) projected and redshift-space two-point correlation functions, with an accurate model built on high resolution N -body simu… Show more
“…Since we assume that the central galaxy and the host halo are located at the same spatial position (potential minimum), a central velocity bias naturally leads to a small offset between the position of the central galaxy and the halo potential minimum, as discussed in detail in Guo et al (2015a).…”
Section: Conclusion and Discussionmentioning
confidence: 99%
“…When trying to compare the velocity bias measurements in the hydrodynamical simulation to the result obtained from HOD modeling of observed SDSS galaxy samples (Guo et al 2015a,c), we need to take into account the impact of baryon that is ignored in the HOD models based on the DMO simulations. We show in Figure 11 the 3D velocity dispersions of the dark matter particles in halos of different masses for the DMO (solid line) and hydrodynamical simulations (dotted line).…”
Section: Conclusion and Discussionmentioning
confidence: 99%
“…For example, the halo velocity in the ROCKSTAR halo finder (Behroozi et al 2013) is defined as the average velocity of the dark matter particles within the innermost 10% of the halo radius, which would be less affected by the disturbance in the outer part of the halo during merger events. Guo et al (2015a) define the halo velocity as the bulk velocity of the inner 25% of the particles (as also used in Li et al 2012). To investigate the effect of the different halo velocity definitions, we compare the effect on the galaxy velocity bias between our fiducial model and three other halo velocity definitions, the average core velocities of the innermost 25% and 10% of the dark matter particles, and also those within the central galaxy radius (twice the stellar half-mass radius).…”
Section: Dependence On Halo Velocity Definitionmentioning
We use the hydrodynamical galaxy formation simulations from the Illustris suite to study the origin and properties of galaxy velocity bias, i.e., the difference between the velocity distributions of galaxies and dark matter inside halos. We find that galaxy velocity bias is a decreasing function of the ratio of galaxy stellar mass to host halo mass. In general, central galaxies are not at rest with respect to dark matter halos or the core of halos, with a velocity dispersion above 0.04 times that of the dark matter. The central galaxy velocity bias is found to be mostly caused by the close interactions between the central and satellite galaxies. For satellite galaxies, the velocity bias is related to their dynamical and tidal evolution history after being accreted onto the host halos. It depends on the time after the accretion and their distances from the halo centers, with massive satellites generally moving more slowly than the dark matter. The results are in broad agreements with those inferred from modeling small-scale redshift-space galaxy clustering data, and the study can help improve models of redshift-space galaxy clustering.
“…Since we assume that the central galaxy and the host halo are located at the same spatial position (potential minimum), a central velocity bias naturally leads to a small offset between the position of the central galaxy and the halo potential minimum, as discussed in detail in Guo et al (2015a).…”
Section: Conclusion and Discussionmentioning
confidence: 99%
“…When trying to compare the velocity bias measurements in the hydrodynamical simulation to the result obtained from HOD modeling of observed SDSS galaxy samples (Guo et al 2015a,c), we need to take into account the impact of baryon that is ignored in the HOD models based on the DMO simulations. We show in Figure 11 the 3D velocity dispersions of the dark matter particles in halos of different masses for the DMO (solid line) and hydrodynamical simulations (dotted line).…”
Section: Conclusion and Discussionmentioning
confidence: 99%
“…For example, the halo velocity in the ROCKSTAR halo finder (Behroozi et al 2013) is defined as the average velocity of the dark matter particles within the innermost 10% of the halo radius, which would be less affected by the disturbance in the outer part of the halo during merger events. Guo et al (2015a) define the halo velocity as the bulk velocity of the inner 25% of the particles (as also used in Li et al 2012). To investigate the effect of the different halo velocity definitions, we compare the effect on the galaxy velocity bias between our fiducial model and three other halo velocity definitions, the average core velocities of the innermost 25% and 10% of the dark matter particles, and also those within the central galaxy radius (twice the stellar half-mass radius).…”
Section: Dependence On Halo Velocity Definitionmentioning
We use the hydrodynamical galaxy formation simulations from the Illustris suite to study the origin and properties of galaxy velocity bias, i.e., the difference between the velocity distributions of galaxies and dark matter inside halos. We find that galaxy velocity bias is a decreasing function of the ratio of galaxy stellar mass to host halo mass. In general, central galaxies are not at rest with respect to dark matter halos or the core of halos, with a velocity dispersion above 0.04 times that of the dark matter. The central galaxy velocity bias is found to be mostly caused by the close interactions between the central and satellite galaxies. For satellite galaxies, the velocity bias is related to their dynamical and tidal evolution history after being accreted onto the host halos. It depends on the time after the accretion and their distances from the halo centers, with massive satellites generally moving more slowly than the dark matter. The results are in broad agreements with those inferred from modeling small-scale redshift-space galaxy clustering data, and the study can help improve models of redshift-space galaxy clustering.
“…The halo model has been adopted to the galaxy clustering in redshift space [9,45,46,[55][56][57][58][59]. The halo power spectrum and correlation function were directly measured from N -body simulations in [59,60] and [9], respectively, to fully take into account the nonlinearities of halo clustering in the halo model. However, for analytical approaches linear PT has been used to describe RSD of halos, i.e., the linear Kaiser model [1], to combine with the halo model in previous studies [e.g., 46].…”
Theoretical modeling of the redshift-space power spectrum of galaxies is crucially important to correctly extract cosmological information from galaxy redshift surveys. The task is complicated by the nonlinear biasing and redshift space distortion (RSD) effects, which change with halo mass, and by the wide distribution of halo masses and their occupations by galaxies. One of the main modeling challenges is the existence of satellite galaxies that have both radial distribution inside the halos and large virial velocities inside halos, a phenomenon known as the Finger-of-God (FoG) effect. We present a model for the redshift-space power spectrum of galaxies in which we decompose a given galaxy sample into central and satellite galaxies and relate different contributions to the power spectrum to 1-halo and 2-halo terms in a halo model. Our primary goal is to ensure that any parameters that we introduce have physically meaningful values, and are not just fitting parameters. For the lowest order 2-halo terms we use the previously developed RSD modeling of halos in the context of distribution function and perturbation theory approach. This term needs to be multiplied by the effect of radial distances and velocities of satellites inside the halo. To this one needs to add the 1-halo terms, which are non-perturbative. We show that the real space 1-halo terms can be modeled as almost constant, with the finite extent of the satellites inside the halo inducing a small k 2 R 2 term over the range of scales of interest, where R is related to the size of the halo given by its halo mass. We adopt a similar model for FoG in redshift space, ensuring that FoG velocity dispersion is related to the halo mass. For FoG k 2 type expansions do not work over the range of scales of interest and FoG resummation must be used instead. We test several simple damping functions to model the velocity dispersion FoG effect. Applying the formalism to mock galaxies modeled after the "CMASS" sample of the BOSS survey, we find that our predictions for the redshift-space power spectra are accurate up to k ≃ 0.4 h Mpc −1 within 1% if the halo power spectrum is measured using N -body simulations and within 3% if it is modeled using perturbation theory.
“…The velocity distribution of satellites has been studied by conducting various numerical simulations (e.g., Ghigna et al 2000;Diemand et al 2004;Faltenbacher et al 2005;Wu et al 2013). A non-zero velocity of central galaxies relative to the host halo has been found in several studies (e.g., van den Bosch et al 2005;Guo et al 2015).…”
Nonlinear redshift-space distortion known as the Fingers-of-God (FoG) effect is a major systematic uncertainty in redshift-space distortion studies conducted to test gravity models. The FoG effect has been usually attributed to the random motion of galaxies inside their clusters. When the internal galaxy motion is not well virialized, however, the coherent infalling motion toward the cluster center generates the FoG effect. Here we derive an analytical model of the satellite velocity distribution due to the infall motion combined with the random motion. We show that the velocity distribution becomes far from Maxwellian when the infalling motion is dominant. We use simulated subhalo catalogs to find that the contribution of infall motion is important to massive subhalos and that the velocity distribution has a top-hat like shape as expected from our analytic model. We also study the FoG effect due to infall motion on the redshift-space power spectrum. Using simulated mock samples of luminous red galaxies constructed from halos and massive subhalos in N-body simulations, we show that the redshift-space power spectra can differ from expectations when the infall motion is ignored.
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