Halo concentrations from extended Press–Schechter merger histories

Benson, Andrew; Ludlow, Aaron D.; Cole, Shaun

doi:10.1093/mnras/stz695

Cited by 13 publications

(31 citation statements)

References 43 publications

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“…The energy, E, of a halo (needed to compute the spin parameter under the Peebles (1969) definition) depends on the density profile of the dark matter halo. Throughout this work we assume NFW (Navarro et al 1997) density profiles, and compute their concentrations using the method of Ludlow et al (2016) as specifically implemented by Benson et al (2019).…”

Section: Methodsmentioning

confidence: 99%

“…Millennium Simulation (Springel et al 2005), z = 0 halo masses drawn from a Sheth et al (2001) mass function (with parameters given by Benson et al 2019) and spanning the range 3.53 × 10 11 M to 1.00 × 10 15 M to match the selection used by Bett et al (2007). Bett et al (2007) used a "quasiequilibrium" criterion, based on the virial ratio 2T/U + 1 (with T and U being the kinetic and potential energies of the halo respectively) to remove halos from their sample which were far from virial equilibrium.…”

Section: Constraining Parameters Of the Modelmentioning

confidence: 99%

“…• (A, a, p) in the Sheth et al (2001) mass function, (G 0 , γ 1 , γ 2 ) in the halo merger rate model of Parkinson et al (2008), and ( f , C) in the halo concentration model of Ludlow et al (2016) all as defined by Benson et al (2019), with a multivariate normal prior matched to the posterior distribution found by Benson et al (2019).…”

Section: Constraining Parameters Of the Modelmentioning

confidence: 99%

“…For comparison, we construct a sample of merger trees using the model described in this work using the maximum posterior probability model found by our MCMC simulation, spanning the same range of masses and in a cosmology matched to that of the Millennium Simulation. After computing angular momenta of each halo in these trees we use the model of Benson et al (2019) to add noise to the angular momenta and masses of each halo to represent the effects of particle noise-while this is generally a small effect for halos containing 30,000 particles or more as in this sample we nevertheless account for the effects of this noise 7 . Finally, we compute the spin parameters of these halos under the Bullock et al (2001) definition and compute correlations in spin magnitude and direction in the same way as for the Millennium Simulation halos.…”

Section: Correlationsmentioning

confidence: 99%

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A random-walk model for dark matter halo spins

Benson,

Behrens,

2020

Preprint

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We extend the random-walk model of Vitvitska et al. for predicting the spins of dark matter halos from their merger histories. Using updated merger rates, orbital parameter distributions, and N-body constraints we show that this model can accurately reproduce the distribution of spin parameters measured in N-body simulations when we include a weak correlation between the spins of halos and the angular momenta of infalling subhalos. We further show that this model is in approximate agreement with the correlation of the spin magnitude over time as determined from N-body simulations, while it slightly underpredicts the correlation in the direction of the spin vector measured from the same simulations. This model is useful for predicting spins from merger histories derived from non-N-body sources, thereby circumventing the need for very high resolution simulations to permit accurate measurements of spins. It may be particularly relevant to modeling systems which accumulate angular momentum from halos over time (such as galactic disks)-we show that this model makes small but significant changes in the distribution of galactic disk sizes computed using the Galacticus semi-analytic galaxy formation model.

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Section: Methodsmentioning

confidence: 99%

Section: Constraining Parameters Of the Modelmentioning

confidence: 99%

Section: Constraining Parameters Of the Modelmentioning

confidence: 99%

Section: Correlationsmentioning

confidence: 99%

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A random-walk model for dark matter halo spins

Benson,

Behrens,

2020

Preprint

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“…A prescription for the link between formation history and halo concentration can therefore be used alongside such a theoretical framework to predict the distribution of expected halo concentrations (e.g. Benson, Ludlow & Cole 2019 ).…”

Section: O P T I M a L W I N D Ow F U N C T I O N Smentioning

confidence: 99%

Towards a universal model for the density profiles of dark matter haloes

Brown

McCarthy

Stafford

et al. 2021

Monthly Notices of the Royal Astronomical Society

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It is well established from cosmological simulations that dark matter haloes are not precisely self-similar and an additional parameter, beyond their concentration, is required to accurately describe their spherically-averaged mass density profiles. We present, for the first time, a model to consistently predict both halo concentration, c, and this additional ‘shape’ parameter, α, for a halo of given mass and redshift for a specified cosmology. Following recent studies, we recast the dependency on mass, redshift, and cosmology to a dependence on ‘peak height’. We show that, when adopting the standard definition of peak height, which employs the so-called spherical top hat (STH) window function, the concentration–peak height relation has a strong residual dependence on cosmology (i.e., it is not uniquely determined by peak height), whereas the α–peak height relation is approximately universal when employing the STH window function. Given the freedom in the choice of window function, we explore a simple modification of the STH function, constraining its form so that it produces universal relations for concentration and α as a function of peak height using a large suite of cosmological simulations. It is found that universal relations for the two density profile parameters can indeed be derived and that these parameters are set by the linear power spectrum, P(k), filtered on different scales. We show that the results of this work generalise to any (reasonable) combination of P(k) and background expansion history, H(z), resulting in accurate predictions of the density profiles of dark matter haloes for a wide range of cosmologies.

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A random-walk model for dark matter halo spins

Benson

Behrens

2020

Monthly Notices of the Royal Astronomical Society

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ABSTRACT We extend the random-walk model of Vitvitska et al. for predicting the spins of dark matter haloes from their merger histories. Using updated merger rates, orbital parameter distributions, and N-body constraints, we show that this model can accurately reproduce the distribution of spin parameters measured in N-body simulations when we include a weak correlation between the spins of haloes and the angular momenta of infalling subhaloes. We further show that this model is in approximate agreement with the correlation of the spin magnitude over time as determined from N-body simulations, while it slightly underpredicts the correlation in the direction of the spin vector measured from the same simulations. This model is useful for predicting spins from merger histories derived from non-N-body sources, thereby circumventing the need for very high resolution simulations to permit accurate measurements of spins. It may be particularly relevant to modelling systems that accumulate angular momentum from haloes over time (such as galactic discs) – we show that this model makes small but significant changes in the distribution of galactic disc sizes computed using the galacticus semi-analytic galaxy formation model.

show abstract

Halo concentrations from extended Press–Schechter merger histories

Cited by 13 publications

References 43 publications

A random-walk model for dark matter halo spins

A random-walk model for dark matter halo spins

Towards a universal model for the density profiles of dark matter haloes

A random-walk model for dark matter halo spins

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