Conditional Mass Functions and Merger Rates of Dark Matter Halos in the Ellipsoidal Collapse Model (original) (raw)

Conditional mass functions and merger rates of dark matter haloes in the ellipsoidal collapse model

Monthly Notices of The Royal Astronomical Society, 2008

Analytic models based on spherical and ellipsoidal gravitational collapse have been used to derive the mass functions of dark matter haloes and their progenitors (the conditional mass function). The ellipsoidal model generally provides a better match to simulation results, but there has been no simple analytic expression in this model for the conditional mass function that is accurate for small time-steps, a limit that is important for generating halo merger trees and computing halo merger rates. We remedy the situation by deriving accurate analytic formulae for the first-crossing distribution, the conditional mass function and the halo merger rate in the ellipsoidal collapse model in the limit of small look-back times. We show that our formulae provide a closer match to the Millennium simulation results than those in the spherical collapse model and the ellipsoidal model of Sheth and Tormen.

Merger rates of dark matter haloes: a comparison between EPS and N-body results

Astrophysics and Space Science, 2011

We calculate merger rates of dark matter haloes using the Extended Press-Schechter approximation (EPS) for the Spherical Collapse (SC) and the Ellipsoidal Collapse (EC) models. Merger rates have been calculated for masses in the range 1010 M ⊙ h-1 to 1014 M ⊙ h-1 and for redshifts z in the range 0 to 3 and they have been compared with merger rates that have been proposed by other authors as fits to the results of N-body simulations. The detailed comparison presented here shows that the agreement between the analytical models and N-body simulations depends crucially on the mass of the descendant halo. For some range of masses and redshifts either SC or EC models approximate satisfactory the results of N-body simulations but for other cases both models are less satisfactory or even bad approximations. We showed, by studying the parameters of the problem that a disagreement—if it appears—does not depend on the values of the parameters but on the kind of the particular solution used for the distribution of progenitors or on the nature of EPS methods. Further studies could help to improve our understanding about the physical processes during the formation of dark matter haloes.

An improved model for the formation times of dark matter haloes

Monthly Notices of the Royal Astronomical Society, 2007

A dark matter halo is said to have formed when at least half its mass hass been assembled into a single progenitor. With this definition, it is possible to derive a simple but useful analytic estimate of the distribution of halo formation times. The standard estimate of this distribution depends on the shape of the conditional mass functionthe distribution of progenitor masses of a halo as a function of time. If the spherical collapse model is used to estimate the progenitor mass function, then the formation times one infers systematically underestimate those seen in numerical simulations of hierarchical gravitational clustering. We provide estimates of halo formation which may be related to an ellipsoidal collapse model. These estimates provide a substantially better description of the simulations. We also provide an alternative derivation of the formation time distribution which is based on the assumption that haloes increase their mass through binary mergers only. Our results are useful for models which relate halo structure to halo formation.

Primordial black hole merger rate in ellipsoidal-collapse dark matter halo models

Physical Review D, 2021

We have studied the merger rate of primordial black holes (PBHs) in the ellipsoidal-collapse model of halo to explain the dark matter abundance by the PBH merger estimated from the gravitational waves detections via the Advanced LIGO (aLIGO) detectors. We have indicated that the PBH merger rate within each halo for the ellipsoidal models is more significant than for the spherical models. We have specified that the PBH merger rate per unit time and per unit volume for the ellipsoidal-collapse halo models is about one order of magnitude higher than the corresponding spherical models. Moreover, we have calculated the evolution of the PBH total merger rate as a function of redshift. The results indicate that the evolution for the ellipsoidal halo models is more sensitive than spherical halo models, as expected from the models. Finally, we have presented a constraint on the PBH abundance within the context of ellipsoidal and spherical models. By comparing the results with the aLIGO mergers during the third observing run (O3), we have shown that the merger rate in the ellipsoidal-collapse halo models falls within the aLIGO window, while the same result is not valid for the spherical-collapse ones. Furthermore, we have compared the total merger rate of PBHs in terms of their fraction in the ellipsoidal-collapse halo models for several masses of PBHs. The results suggest that the total merger rate of PBHs changes inversely with their masses. We have also estimated the relation between the fraction of PBHs and their masses in the ellipsoidal-collapse halo model and have shown it for a narrow mass distribution of PBHs. The outcome shows that the constraint inferred from the PBH merger rate for the ellipsoidal-collapse halo models can be potentially stronger than the corresponding result obtained for the spherical-collapse ones.

On the reliability of merger-trees and the mass growth histories of dark matter haloes

We have used merger trees realizations to study the formation of dark matter haloes. The construction of merger-trees is based on three different pictures about the formation of structures in the Universe. These pictures include: the spherical collapse (SC), the ellipsoidal collapse (EC) and the non-radial collapse (NR). The reliability of merger-trees has been examined comparing their predictions related to the distribution of the number of progenitors, as well as the distribution of formation times, with the predictions of analytical relations. The comparison yields a very satisfactory agreement. Subsequently, the mass growth histories (MGH) of haloes have been studied and their formation scale factors have been derived. This derivation has been based on two different definitions that are: (a) the scale factor when the halo reaches half its present day mass and (b) the scale factor when the mass growth rate falls below some specific value. Formation scale factors follow approximately power laws of mass. It has also been shown that MGHs are in good agreement with models proposed in the literature that are based on the results of N-body simulations. The agreement is found to be excellent for small haloes but, at the early epochs of the formation of large haloes, MGHs seem to be steeper than those predicted by the models based on N-body simulations. This rapid growth of mass of heavy haloes is likely to be related to a steeper central density profile indicated by the results of some N-body simulations.

The merger rates and mass assembly histories of dark matter haloes in the two Millennium simulations

Monthly Notices of The Royal Astronomical Society, 2010

We construct merger trees of dark matter haloes and quantify their merger rates and mass growth rates using the joint dataset from the Millennium and Millennium-II simulations. The finer resolution of the Millennium-II Simulation has allowed us to extend our earlier analysis of halo merger statistics to an unprecedentedly wide range of descendant halo mass (10^10 < M0 < 10^15 Msun), progenitor mass ratio (10^-5 < xi < 1), and redshift (0 < z < 15). We update our earlier fitting form for the mean merger rate per halo as a function of M_0, xi, and z. The overall behavior of this quantity is unchanged: the rate per unit redshift is nearly independent of z out to z~15; the dependence on halo mass is weak (M0^0.13); and it is nearly a power law in the progenitor mass ratio (xi^-2). We also present a simple and accurate fitting formula for the mean mass growth rate of haloes as a function of mass and redshift. This mean rate is 46 Msun/yr for 10^12 Msun haloes at z=0, and it increases with mass as M^{1.1} and with redshift as (1+z)^2.5 (for z > 1). When the fit for the mean mass growth rate is integrated over a halo's history, we find excellent match to the mean mass assembly histories of the simulated haloes. By combining merger rates and mass assembly histories, we present results for the number of mergers over a halo's history and the statistics of the redshift of the last major merger.

Merger rates of dark matter haloes from merger trees in the extended Press-Schechter theory

Eprint Arxiv 0905 0793, 2009

We construct merger trees based on the extended Press-Schechter theory (EPS) in order to study the merger rates of dark matter haloes over a range of present day mass ($10^{10}M_{\sun}\leq M_0 \leq10^{15}M_{\sun}$), progenitor mass (5times10−3leqxileq1(5\times10^{-3}\leq \xi \leq1(5times10−3leqxileq1) and redshift ($0\leq z\leq 3$). We used the first crossing distribution of a moving barrier of the form B(S,z)=p(z)+q(z)SgammaB(S,z)=p(z)+q(z)S^{\gamma}B(S,z)=p(z)+q(z)Sgamma, proposed by Sheth & Tormen, to take into account the ellipsoidal nature of collapse. We find that the mean merger rate per halo Bm/nB_m/nBm/n depends on the halo mass MMM as M0.2M^{0.2}M0.2 and on the redshift as (mathrmddeltac(z)/mathrmdz)1.1(\mathrm{d}\delta_c(z)/\mathrm{d}z)^{1.1}(mathrmddeltac(z)/mathrmdz)1.1. Our results are in agreement with the predictions of N-body simulations and this shows the ability of merger-trees based on EPS theory to follow with a satisfactory agreement the results of N-body simulations and the evolution of structures in a hierarchical Universe.

Merger history trees of dark matter haloes in moving barrier models

Monthly Notices of the Royal Astronomical Society, 2008

We present an algorithm for generating merger histories of dark matter haloes. The algorithm is based on the excursion set approach with moving barriers whose shape is motivated by the ellipsoidal collapse model of halo formation. In contrast to most other merger-tree algorithms, ours takes discrete steps in mass rather than time. This allows us to quantify effects which arise from the fact that outputs from numerical simulations are usually in discrete time bins. In addition, it suggests a natural set of scaling variables for describing the abundance of halo progenitors; this scaling is not as general as that associated with a spherical collapse. We test our algorithm by comparing its predictions with measurements in numerical simulations. The progenitor mass fractions and mass functions are in good agreement, as is the predicted scaling law. We also test the formation-redshift distribution, the mass distribution at formation, and the redshift distribution of the most recent major merger; all are in reasonable agreement with N-body simulation data, over a broad range of masses and redshifts. Finally, we study the effects of sampling in discrete time snapshots. In all cases, the improvement over algorithms based on the spherical collapse assumption is significant.

Predicting the Number, Spatial Distribution, and Merging History of Dark Matter Halos

The Astrophysical Journal, 2002

We present a new algorithm (PINOCCHIO, PINpointing Orbit-Crossing Collapsed HIerarchical objects) to predict accurately the formation and evolution of individual dark matter haloes in a given realization of an initial linear density field. Compared with the halo population formed in a large (360 3 particles) collisionless simulation of a CDM universe, our method is able to predict to better than 10 per cent statistical quantities such as the mass function, two-point correlation function and progenitor mass function of the haloes. Masses of individual haloes are estimated accurately as well, with errors typically of order 30 per cent in the mass range well resolved by the numerical simulation. These results show that the hierarchical formation of dark matter haloes can be accurately predicted using local approximations to the dynamics when the correlations in the initial density field are properly taken into account. The approach allows one to automatically generate a large ensemble of accurate merging histories of haloes with complete knowledge of their spatial distribution. The construction of the full merger tree for a 256 3 realisation requires a few hours of CPU-time on a personal computer, orders of magnitude faster than the corresponding N -body simulation would take, and without needing any extensive post-processing. The technique can be efficiently used, for instance, for generating the input for galaxy formation modeling.