The scale-dependence of halo assembly bias

Sunayama, Tomomi; Hearin, Andrew P.; Padmanabhan, Nikhil; Leauthaud, Alexie

doi:10.1093/mnras/stw332

Cited by 64 publications

(71 citation statements)

References 72 publications

(86 reference statements)

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“…Additionally, these studies have not demonstrated the physical origin of the remaining assembly bias signal. Our results differ from those of Sunayama et al (2016), which find that splashback subhaloes have little effect on the MCF at large distances (R 10 h −1 Mpc). Sunayama et al (2016) used the same simulation and underlying halo catalogues as this paper, so this difference is likely due to the fact that their samples are defined by M vir (see section 4.2) and their use of halo bias ratios to measure assembly bias.…”

Section: Comparison With Previous Workcontrasting

confidence: 99%

“…The figure shows that splashback subhaloes cannot account for the entirety of assembly bias, although they contribute about two thirds of the signal. This is consistent with conclusions of the previous studies (Wang et al 2009;Sunayama et al 2016). The novel feature of this analysis is that we find a similar effect for two independent definitions of the splashback haloes: using evolutionary trajectories ( §2.3.1) and using non-spherical 3D splashback shells identified using the SHELLFISH code ( §2.3.2).…”

Section: Subhalo Definitionsupporting

confidence: 91%

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The three causes of low-mass assembly bias

Mansfield

Kravtsov

2020

Monthly Notices of the Royal Astronomical Society

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We present a detailed analysis of the physical processes that cause halo assembly bias -the dependence of halo clustering on proxies of halo formation time. We focus on the origin of assembly bias in the mass range corresponding to the hosts of typical galaxies and use halo concentration as our chief proxy of halo formation time. We also repeat our key analyses across a broad range of halo masses and for alternative formation time definitions. We show that splashback subhaloes are responsible for two thirds of the assembly bias signal, but do not account for the entire effect. After splashback subhaloes have been removed, we find that the remaining assembly bias signal is due to a relatively small fraction ( 10%) of haloes in dense regions. We test a number of additional physical processes thought to contribute to assembly bias and demonstrate that the two key processes are the slowing of mass growth by largescale tidal fields and by the high velocities of ambient matter in sheets and filaments. We also rule out several other proposed physical causes of halo assembly bias. Based on our results, we argue that there are three processes that contribute to assembly bias of low-mass halos: large-scale tidal fields, gravitational heating due to the collapse of large-scale structures, and splashback subhaloes located outside the virial radius.

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Section: Comparison With Previous Workcontrasting

confidence: 99%

Section: Subhalo Definitionsupporting

confidence: 91%

The three causes of low-mass assembly bias

Mansfield

Kravtsov

2020

Monthly Notices of the Royal Astronomical Society

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“…As with CIC, the annuli have a depth in the redshift dimension of 10 h −1 Mpc, corresponding to a velocity difference of ∆v = 1000 km s −1 . As with CIC, this geometry is chosen in order to probe the immediate environments of haloes, particularly on scales where assembly bias has already been shown to induce a feature in galaxy clustering (e.g., Hearin et al 2016;Sunayama et al 2016). We have experimented with moderately different annular dimensions and obtained qualitatively similar results in all cases.…”

Section: Counts-in-annuli (Cia) Statistic P(n Cia )mentioning

confidence: 88%

“…For the primary results that we present in this paper, we use r CIC = 2h −1 Mpc and a maximum relative velocity of ∆v = 1000 km s −1 , corresponding to a half-length of L = 10h −1 Mpc, assuming velocities are only due to the Hubble flow. We choose cylinders of a transverse radius r CIC on the order of a few h −1 Mpc in order to include galaxy companions separated by a scale on which assembly bias is known to introduce a distinct feature in halo clustering Zentner et al 2019;Sunayama et al 2016). We have experimented with a variety of alternative cylinder radii and depths, finding that our results remain qualitatively similar.…”

Section: Counts-in-cylinders (Cic) Statistic P(n Cic )mentioning

confidence: 94%

How to optimally constrain galaxy assembly bias: supplement projected correlation functions with count-in-cells statistics

Wang

Mao

Zentner

et al. 2019

Monthly Notices of the Royal Astronomical Society

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Most models for the statistical connection between galaxies and their haloes ignore the possibility that galaxy properties may be correlated with halo properties other than halo mass, a phenomenon known as galaxy assembly bias. And yet, it is known that such correlations can lead to systematic errors in the interpretation of survey data that are analyzed using traditional halo occupation models. At present, the degree to which galaxy assembly bias may be present in the real Universe, and the best strategies for constraining it remain uncertain. We study the ability of several observables to constrain galaxy assembly bias from redshift survey data using the decorated halo occupation distribution (dHOD), an empirical model of the galaxyhalo connection that incorporates assembly bias. We cover an expansive set of observables, including the projected two-point correlation function w p (r p ), the galaxy-galaxy lensing signal ∆Σ(r p ), the void probability function VPF(r), the distributions of counts-in-cylinders P(N CIC ), and counts-in-annuli P(N CIA ), and the distribution of the ratio of counts in cylinders of different sizes P(N 2 /N 5 ). We find that despite the frequent use of the combination w p (r p ) + ∆Σ(r p ) in interpreting galaxy data, the count statistics, P(N CIC ) and P(N CIA ), are generally more efficient in constraining galaxy assembly bias when combined with w p (r p ). Constraints based upon w p (r p ) and ∆Σ(r p ) share common degeneracy directions in the parameter space, while combinations of w p (r p ) with the count statistics are more complementary. Therefore, we strongly suggest that count statistics should be used to complement the canonical observables in future studies of the galaxy-halo connection.

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“…Ultimately, neglecting assembly bias in the modelling can lead to inferences that are systematically and significantly biased (Zentner et al 2014). This effect should be particularly strong for small-scale ∆Σ measurements that probe the dark matter halo structure, but can also have a non-negligible impact on intermediate scales (Sunayama et al 2016).…”

Section: Galaxy Assembly Biasmentioning

confidence: 99%

New perspectives on the BOSS small-scale lensing discrepancy for the Planck ΛCDM cosmology

Lange

Yang

Guo

et al. 2019

Monthly Notices of the Royal Astronomical Society

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We investigate the abundance, small-scale clustering and galaxy-galaxy lensing signal of galaxies in the Baryon Oscillation Spectroscopic Survey (BOSS). To this end, we present new measurements of the redshift and stellar mass dependence of the lensing properties of the galaxy sample. We analyse to what extent models assuming the Planck18 cosmology fit to the number density and clustering can accurately predict the small-scale lensing signal. In qualitative agreement with previous BOSS studies at redshift z ∼ 0.5 and with results from the Sloan Digital Sky Survey, we find that the expected signal at small scales (0.1 < r p < 3 h −1 Mpc) is higher by ∼ 25% than what is measured. Here, we show that this result is persistent over the redshift range 0.1 < z < 0.7 and for galaxies of different stellar masses. If interpreted as evidence for cosmological parameters different from the Planck CMB findings, our results imply S 8 = σ 8 Ω m /0.3 = 0.744 ± 0.015, whereas S 8 = 0.832 ± 0.013 for Planck18. However, in addition to being in tension with CMB results, such a change in cosmology alone does not accurately predict the lensing amplitude at larger scales. Instead, other often neglected systematics like baryonic feedback or assembly bias are likely contributing to the small-scale lensing discrepancy. We show that either effect alone, though, is unlikely to completely resolve the tension. Ultimately, a combination of the two effects in combination with a moderate change in cosmological parameters might be needed.

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The scale-dependence of halo assembly bias

Cited by 64 publications

References 72 publications

The three causes of low-mass assembly bias

The three causes of low-mass assembly bias

How to optimally constrain galaxy assembly bias: supplement projected correlation functions with count-in-cells statistics

New perspectives on the BOSS small-scale lensing discrepancy for the Planck ΛCDM cosmology

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