Search arXivSearch

arXiv · 0906.1196

Dark Matter Halo Growth II: Diffuse Accretion and its Environmental Dependence

Abstract

Dark matter haloes in Lambda CDM simulations grow by mergers with other haloes as well as accretion of "diffuse" non-halo material. We quantify the mass growth rates via these two processes, dM_mer/dt and dM_dif/dt, and their dependence on halo environment using the ~500,000 haloes in the Millennium simulation. Adopting a local mass density parameter as a measure of halo environment, we find the two rates show strong but opposite environmental dependence, with mergers playing an increasingly important role for halo growths in overdense regions and diffuse accretion dominating growth in voids. This behaviour is independent of the mass cuts used to define haloes vs non-haloes. For galaxy-scale haloes, these two opposite correlations largely cancel out, but a weak environmental dependence remains that results in a slightly lower mean total growth rate, and hence an earlier mean formation redshift, for haloes in denser regions. The mean formation redshift of the ~5000 cluster-mass haloes, on the other hand, appears to have no correlation with halo environment. The origin of the positive correlation of dM_mer/dt with local density can be traced to the surrounding mass reservoir outside the haloes, where more progenitor haloes are available in denser regions. The negative correlation of dM_dif/dt with density, however, is not explained by the available diffuse mass in the reservoir, which is in fact larger in denser regions. The non-halo component may therefore be partially comprised of truly diffuse dark matter particles that are dynamically hotter and are accreted at a suppressed rate in denser regions. We also discuss the implications of these results for how to modify the Extended Press-Schechter model of halo growth, which in its original form does not predict environmental dependence.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Onsi Fakhouri, Chung-Pei Ma. 2009-10-19. Dark Matter Halo Growth II: Diffuse Accretion and its Environmental Dependence. https://doi.org/10.1111/j.1365-2966.2009.15844.x

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

Constraints on the Thomson optical depth to the CMB from the Lyman-$α$ forest

We present the first constraints on the electron optical depth to reionization, $τ_{\mathrm{e}}$, from the Lyman-$α$ forest alone for physically motivated reionization models that match the reionization's end-point, $z_{\rm{end}}$, required by the same astrophysical probe, and for symmetric reionization models with fixed duration, $Δz$, commonly adopted in CMB reionization analyses. Compared to traditional estimates from the latter, the Lyman-$α$ forest traces the ionization state of the IGM through its coupling with the thermal state. We find an explicit mapping between the two solving the chemistry and temperature evolution equations for hydrogen and helium. Our results yield $τ_{\mathrm{e}}$=$0.040^{+0.042}_{-0.018}$ (95\% C.L) and $τ_{\mathrm{e}}$=$0.041^{+0.028}_{-0.017}$ for reionization models with $z_{\rm{end}}$ and $Δz$-fixed, respectively. With mock Lyman-$α$ forest data that mimics the precision of future larger quasar sample datasets, we would potentially obtain tighter $τ_{\mathrm{e}}$ constraints, paving the way for CMB-independent constraints on the epoch of reionization from a large-scale structure probe.

astro-ph.CO

Non-minimally Coupled Running Curvaton for DESI-motivated Dynamical Dark Energy

Recent DESI BAO data combined with CMB and supernova measurements suggest a dynamical dark energy that can cross the phantom divide. We show that introducing a non-minimal coupling $ξχ^2R$ to the running-curvaton framework allows a single field to drive early-universe curvature perturbations and late-time phantom-crossing cosmic acceleration without ghost instabilities. Using MCMC background likelihoods with DESI DR2 BAO, Pantheon+ SNe, and a reduced CMB prior, we constrain the cosmological parameters: $H_0 = 67.88^{+0.53}_{-0.61}\,{\rm km\,s^{-1}\,Mpc^{-1}}$, $Ω_m = 0.3072^{+0.0059}_{-0.0054}$, $w_0 = -0.922^{+0.055}_{-0.063}$, and $w_a = -0.205^{+0.173}_{-0.182}$. Parameter degeneracies leave the coupling constants weakly constrained, highlighting the need for full perturbation-level analysis using CMB spectra and lensing.

astro-ph.CO

On the Relation Between Field-Level Posteriors, Correlators, and their Likelihoods

We develop a field-level posterior for cosmological data by marginalizing over initial conditions and noise in a general forward model. While our focus is on large-scale structure data, the results generalize to any weakly non-Gaussian observable. Moreover, the construction is non-perturbative with respect to the forward model and applies equally well to perturbative calculations, simulation-based predictions, and more general effective descriptions. Expanding the FLP around its Gaussian limit, we derive a general expression for the Fisher matrix and reorganize the field-level information into contributions associated with the connected correlators of the evolved field. This makes explicit which terms are captured by likelihood analyses based on the power spectrum, the bispectrum, or finite sets of summary statistics, and which are lost under compression. We recover the standard Gaussian-covariance result for the power spectrum, show that the Gaussian bispectrum likelihood reproduces the corresponding field-level contribution, and show how cross-covariances among summaries progressively reconstruct more of the full field-level information. As an application to the BAO scale, we show how the field contains all the information required for its optimal reconstruction in the presence of noise, and identify the contributions in the FLP needed to attain this limit. We also show that the reconstruction of the initial field arises naturally as a byproduct of our approach, yielding the optimal estimate of the initial conditions given the data and the noise. Our results provide a unified framework to compare field-level and correlator-based inference, to quantify the information loss induced by compression, and to explore the role of stochasticity.

astro-ph.CO