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Knebe, Alexander; Little, Brett; Islam, Ranty R.; Devriendt, Julien; Mahmood, Asim; Silk, Joseph

doi:10.1023/a:1024021908845

Cited by 6 publications

(10 citation statements)

References 10 publications

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“…As noted by a number of authors, there are different disadvantages to these two types of halo finders (e.g. Bett et al 2007; Tinker et al 2008b; Knebe et al 2011). In particular, SO halo finders tend to impose a more spherical geometry on the resulting systems.…”

Section: Resultsmentioning

confidence: 99%

“…In addition, FOF halo finders define a halo centre as the centre of mass, while most other algorithms (including ours) define the centre as the centre of the density profile (i.e. the most bound particle; Knebe et al 2011). These differences with FOF halo finders may explain the disagreement about correlations between the spin axis and major or minor axes of haloes.…”

Section: Resultsmentioning

confidence: 99%

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Properties of dark matter haloes and their correlations: the lesson from principal component analysis

Skibba

Macciò

2011

Monthly Notices of the Royal Astronomical Society

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We study the correlations between the structural parameters of dark matter haloes using principal component analysis. We consider a set of eight parameters, six of which are commonly used to characterize dark matter halo properties: mass, concentration, spin, shape, overdensity and the angle (ΦL) between the major axis and the angular momentum vector. Two additional parameters (xoff and ρrms) are used to describe the degree of ‘relaxedness’ of the halo. We find that we can account for much of the variance of these properties with halo mass and concentration, on the one hand, and halo relaxedness on the other. None the less, three principal components are usually required to account for most of the variance. We argue that halo mass is not as dominant as expected, which is a challenge for halo occupation models and semi‐analytic models that assume that mass determines other halo (and galaxy) properties. In addition, we find that the angle ΦL is not significantly correlated with other halo parameters, which may present a difficulty for models in which galaxy discs are oriented in haloes in a particular way. Finally, at fixed mass, we find that a halo’s environment (quantified by the large‐scale overdensity) is relatively unimportant.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Properties of dark matter haloes and their correlations: the lesson from principal component analysis

Skibba

Macciò

2011

Monthly Notices of the Royal Astronomical Society

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“…In galaxy clusters, more structure indicates a less relaxed, younger system (e.g., Bird & Beers 1993;Knebe & Müller 2000;C14;Cohen et al 2015). Such clusters are more likely to live in superclusters with richer inner structure where group mergers occur more easily than in superclusters with simple inner structure.…”

Section: Discussionmentioning

confidence: 99%

“…The effects of galaxy cluster mergers on star formation (SF) have begun to be better understood in recent years, adding depth to the relationships found in relaxed clusters between SF and clustercentric distance and local density (e.g., Dressler 1980;Cohen et al 2014, hereafter C14;Cohen et al 2015; and many others). While some studies find no relationship between cluster merger activity and SF in specific clusters (e.g., Metevier et al 2000;Ferrari et al 2005;Braglia et al 2009;Hwang & Lee 2009;Kleiner et al 2014), many others report such a relationship (e.g., Knebe & Müller 2000;Cortese et al 2004;Ferrari et al 2005;Johnston-Hollitt et al 2008;Bravo-Alfaro et al 2009;Braglia et al 2009;Hwang & Lee 2009;Ma et al 2010;Wegner 2011;Wegner et al 2015;Sobral et al 2015;Girardi et al 2015;Stroe et al 2015). Indeed, C14 and Cohen et al (2015) found that SF is statistically correlated to cluster substructure in studies of large numbers of clusters: in general, clusters with more substructure exhibit greater levels of SF.…”

Section: Introductionmentioning

confidence: 99%

Star Formation and Supercluster Environment of 107 Nearby Galaxy Clusters

Cohen

Hickox

Wegner

et al. 2017

ApJ

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We analyze the relationship between star formation (SF), substructure, and supercluster environment in a sample of 107 nearby galaxy clusters using data from the Sloan Digital Sky Survey. Previous works have investigated the relationships between SF and cluster substructure, and cluster substructure and supercluster environment, but definitive conclusions relating all three of these variables has remained elusive. We find an inverse relationship between cluster SF fraction (f SF ) and supercluster environment density, calculated using the galaxy luminosity density field at a smoothing length of 8 h −1 Mpc (D8). The slope of f SF vs. D8 is −0.008 ± 0.002. The f SF of clusters located in low-density large-scale environments, 0.244 ± 0.011, is higher than for clusters located in high-density supercluster cores, 0.202 ± 0.014. We also divide superclusters, according to their morphology, into filament-and spider-type systems. The inverse relationship between cluster f SF and large-scale density is dominated by filament-rather than spider-type superclusters. In high-density cores of superclusters, we find a higher f SF in spider-type superclusters, 0.229 ± 0.016, than in filamenttype superclusters, 0.166 ± 0.019. Using principal component analysis, we confirm these results and the direct correlation between cluster substructure and SF. These results indicate that cluster SF is affected by both the dynamical age of the cluster (younger systems exhibit higher amounts of SF); the large-scale density of the supercluster environment (high-density core regions exhibit lower amounts of SF); and supercluster morphology (spider-type superclusters exhibit higher amounts of SF at high densities).

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“…For identifying particle groups within our numerical simulations we used the standard friends-of-friends (FOF) algorithm (Davis et al 1985) with the linking lengths ll ¼ 0:2 for the SCDM, and ll ¼ 0:17 for the OCDM model, respectively (cf. Knebe & Müller 1999).…”

Section: The N -B O D Y S I M U L At I O N Smentioning

confidence: 99%

Bumpy power spectra and galaxy clusters

Knebe¹,

Islam²,

Silk³

2001

Monthly Notices of the Royal Astronomical Society

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The evolution of the abundance of galaxy clusters is not a reliable measure of Ω if there are features on scales of a few Mpc in the primordial power spectrum. Conversely, if we know the cosmological model parameters from other measurements, the cluster abundance evolution permits us to probe features in the power spectrum that are in the non‐linear regime at the present epoch, and hence difficult to discern directly from current epoch measurements. We have investigated the influence of an artificially introduced Gaussian feature on an otherwise unperturbed SCDM power spectrum on scales corresponding to k∼0.4–0.8 h Mpc−1. Using these modified spectra as an input to cosmological N‐body simulations, we are able to show that in terms of the cluster abundance evolution a SCDM model displays characteristics similar to an OCDM model. However, strong modifications would also be visible at a redshift of z=0 in the dark matter power spectrum whereas minor alterations to the usual SCDM spectrum are washed away by non‐linear evolution effects. We show that alterations to the dark matter power spectrum like those presented in this paper do not leave any imprint in the present density fluctuation spectrum and the velocity distribution of galaxy clusters; nearly all models agree with each other and do not coincide with our fiducial OCDM model, respectively. We therefore conclude that features with characteristics such as those discussed here might not be detectable using observations of the galaxy power spectrum, the local cluster abundance or the large‐scale velocity field as measured by the velocity distribution of galaxy clusters. The only quantity that shows a pronounced difference, at the present epoch between our models under investigation, is the halo–halo correlation function which appears to be strongly biased with respect to an unmodified SCDM model. This is due to a lack of power on certain scales which subsequently modifies the relative amplitude of high‐ and low‐k waves. Apart from observations of the evolution of cluster abundance, measurements of the Lyman α forest at high redshift could put constraints on possible features in the power spectrum, too.

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Untitled

Cited by 6 publications

References 10 publications

Properties of dark matter haloes and their correlations: the lesson from principal component analysis

Properties of dark matter haloes and their correlations: the lesson from principal component analysis

Star Formation and Supercluster Environment of 107 Nearby Galaxy Clusters

Bumpy power spectra and galaxy clusters

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