Search arXiv⌕ Search
Home/Archive/arXiv

arXiv · 1108.4247

Mass assembly of galaxies: Smooth accretion versus mergers

Benjamin L'Huillier·Francoise Combes·Benoit Semelin
View original source ↗Read source document ↗Export metadata ↓

Abstract

Galaxies accrete their mass by means of both smooth accretion from the cosmic web, and the mergers of smaller entities. We wish to quantify the respective role of these two modes of accretion, which could determine the morphological types of galaxies observed today. Multi-zoom cosmological simulations are used to estimate as a function of time the evolution of mass in bound systems, for dark matter as well as baryons. The baryonic contents of dark matter haloes are studied. Merger histories are followed as a function of external density, and the different ways in which mass is assembled in galaxies and the stellar component accumulated are quantified. We find that most galaxies assemble their mass through smooth accretion, and only the most massive galaxies also grow significantly through mergers. The mean fraction of mass assembled by accretion is 77 %, and by mergers 23 %. We present typical accretion histories of hundreds of galaxies: masses of the most massive galaxies increase monotonically in time, mainly through accretion, many intermediate-mass objects also experience mass-loss events such as tidal stripping and evaporation. However, our simulations suffer from the overcooling of massive galaxies caused by the neglect of active galaxy nuclei (AGN) feedback. The time by which half of the galay mass has assembled, both in dark matter and baryons, is a decreasing function of mass, which is compatible with the observations of a so-called downsizing. At every epoch in the universe, there are low-mass galaxies actively forming stars, while more massive galaxies form their stars over a shorter period of time within half the age of the universe.

Explore related subjects

astro-ph.CO

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Benjamin L'Huillier, Francoise Combes, Benoit Semelin. 2012-06-22. Mass assembly of galaxies: Smooth accretion versus mergers. https://doi.org/10.1051/0004-6361%2F201117924

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

KEEP EXPLORING

Related papers

arXiv2026

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↗
arXiv2026

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↗
arXiv2026

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↗