A UNIVERSAL MODEL FOR HALO CONCENTRATIONS

By B. Diemer, Andrey V. Kravtsov. 2014

258 citations recorded by the source corpus.

We present a numerical study of dark matter halo concentrations in ΛCDM and self-similar cosmologies. We show that the relation between concentration, c, and peak height, ν, exhibits the smallest deviations from universality if halo masses are defined with respect to the critical density of the universe. These deviations can be explained by the residual dependence of concentration on the local slope of the matter power spectrum, n, which affects both the normalization and shape of the c–ν relation. In particular, there is no well-defined floor in the concentration values. Instead, the minimum concentration depends on redshift: at fixed ν, halos at higher z experience steeper slopes n, and thus have lower minimum concentrations. We show that the concentrations in our simulations can be accurately described by a universal seven-parameter function of only ν and n. This model matches our ΛCDM results to ≲ 5% accuracy up to z = 6, and matches scale-free Ωm = 1 models to ≲ 15%. The model also reproduces the low concentration values of Earth–mass halos at z ≈ 30, and thus correctly extrapolates over 16 orders of magnitude in halo mass. The predictions of our model differ significantly from all models previously proposed in the literature at high masses and redshifts. Our model is in excellent agreement with recent lensing measurements of cluster concentrations.

Subfields: Astronomy and Astrophysics, Instrumentation

View Paper: https://www.semanticscholar.org/paper/e8c0c805661568b6e92d2790aa0a50b7ca3679bc

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Citations in the corpus

What does the Bullet Cluster tell us about Self-Interacting Dark Matter? (2016, background): “Given the redshift of the system at z = 0.296, the masses of the two haloes are then M200 ≈ 1.5 ×1015 M for the main cluster and M200 ≈ 1.5 ×1014 M for the bullet cluster.4 The concentration of the main halo derived from weak lensing would place this halo well below the concentration–mass relation d”
UniverseMachine: The correlation between galaxy growth and dark matter halo assembly from z = 0−10 (2018, background): “Similar to autocorrelation functions, the lensing signal decreases from z = 0 to z = 1, partially due to lower satellite fractions, and partially due to lower halo concentrations (Diemer et al. 2013; Diemer & Kravtsov 2015; Rodríguez-Puebla et al. 2016b).”
The accretion history of dark matter haloes - III. A physical model for the concentration-mass relation (2015, methodology): “Several recent studies (Klypin et al. 2011; Prada et al. 2012; Dutton & Macciò 2014; Diemer & Kravtsov 2015) have found that the c–”
The cosmic baryon cycle and galaxy mass assembly in the FIRE simulations (2016, methodology): “We compute the scale radius Rs ≡ Rvir/cvir (where cvir is the concentration parameter) using the halo-concentration model of Diemer & Kravtsov (2015), implemented in Colossus6.”
Halo and subhalo demographics with Planck cosmological parameters: Bolshoi–Planck and MultiDark–Planck simulations (2016, background): “Recently More, Diemer & Kravtsov (2015) proposed that the best physically-based definition of halo radius is the “splashback radius” Rsp ≈ 2R200m, where there is typically a sharp drop in the density.”
COLOSSUS: A Python Toolkit for Cosmology, Large-scale Structure, and Dark Matter Halos (2017, unknown): “…and c200m for 2 × 1012 < M < 2 × 1015 h−1 M , 0 < z < 2, WMAP7 dutton14 Dutton & Macciò 2014 Power-law fit, c200c and cvir for M > 1010 h−1 M , 0 < z < 5, planck13 cosmology diemer15 Diemer & Kravtsov 2015 Universal model, c200c for any mass, redshift, or cosmology klypin16 m Klypin et al.…”
Cosmology from cosmic shear power spectra with Subaru Hyper Suprime-Cam first-year data (2018, methodology): “We adopt the concentrationmass relation by Diemer & Kravtsov (2015).”
Growth and activity of black holes in galaxy mergers with varying mass ratios (2014, background): “4 for the range of masses considered in this paper; e.g. Dutton & Macciò 2014; Diemer & Kravtsov 2014).”
Weak Lensing Measurement of the Mass--Richness Relation of SDSS redMaPPer Clusters (2016, methodology): “4, we show how our fitted mass–concentration relation compares to two theoretical models, Bhattacharya et al. (2013) and Diemer & Kravtsov (2015).”
Small-Scale Challenges to the ΛCDM Paradigm (2017, background): “…simulations have progressed to the point that we now have a fairly robust understanding of the structure of ΛCDM halos and the important factors that govern halo-to-halo variance (e.g., Navarro et al. 2010; Diemer & Kravtsov 2015; Klypin et al. 2016), at least for dark-matter-only simulations.”
CLASH: JOINT ANALYSIS OF STRONG-LENSING, WEAK-LENSING SHEAR, AND MAGNIFICATION DATA FOR 20 GALAXY CLUSTERS (2015, methodology): “M relations from Bhattacharya et al. (2013), Dutton & Macciò (2014), Meneghetti et al. (2014), and Diemer & Kravtsov (2015) are in satisfactory agreement with the data.”
THE SPLASHBACK RADIUS AS A PHYSICAL HALO BOUNDARY AND THE GROWTH OF HALO MASS (2015, methodology): “For example, for a Milky Way sized halo of mass M h M10vir 12 1= - (R h207 kpcvir 1= - ) and a typical concentration at that mass, c 9vir » (e.g., Zhao et al. 2009; Diemer & Kravtsov 2015), r h4 92 kpcs 1» - , and M h M5.”
The mass–concentration–redshift relation of cold and warm dark matter haloes (2016, methodology): “This particular parametrization, however, does not lend itself to simple interpretation and predictions of their model were not borne out by more recent simulations (e.g. Gao et al. 2008; Diemer & Kravtsov 2015).”
Dark Energy Survey Year 1 results: weak lensing mass calibration of redMaPPer galaxy clusters (2018, methodology): “(ii) For each cluster, assign a concentration (including scatter) based on Diemer & Kravtsov (2015).”