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Mass Profiles of Galaxy Clusters

Mass Profiles of Galaxy Clusters. Drew Newman. Newman et al. 2009, “The Distribution of Dark Matter Over Three Decades in Radius in the Lensing Cluster Abell 611,” astro-ph/0909.3527 , accepted to ApJ.

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Mass Profiles of Galaxy Clusters

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  1. Mass Profiles of Galaxy Clusters Drew Newman Newman et al. 2009, “The Distribution of Dark Matter Over Three Decades in Radius in the Lensing Cluster Abell 611,” astro-ph/0909.3527, accepted to ApJ

  2. Purpose: Observational measures of cluster mass distribution (dark and baryonic) to make precise comparison with simulations (both N-body and those including baryons) • Need data over wide range of scales to break degeneracies inherent to individual probes • Weak lensing (~100 kpc – 3 Mpc scales) • Strong lensing (~30 kpc – 100 kpc) • Stellar dynamics (~3 – 20 kpc)

  3. Mass Model Motivation • Focus on inner (log) density slope of dark matter • Component #1: NFW / gNFW dark halo • Component #2: Stars in the central galaxy

  4. Weak Lensing – Abell 611 Subaru/ SuprimeCam ~10% of area shown BVRI filters for photo-z’s 1 Mpc = 3.8’

  5. Weak Lensing – Abell 611  Radial shear profile  2D mass reconstruction

  6. Strong Lensing – Abell 611 HST/ACS image 3 multiply images sources 2 of these with spectroscopic redshifts

  7. Stellar VelocityDispersions – Abell 611

  8. From Data to Mass Distributions • Draw sample models (MCMC) consisting of • Elliptical NFW or gNFW dark halo, • Stellar mass in cD galaxy, • Galaxies that may perturb image positions • Compare to data: • Compute shear at locations of background galaxies, • Ray-tracing of multiply-imaged sources to other locations in image plane, • Compute velocity dispersion profile (including observational effects: seeing, binning) • Can we discriminate between NFW and gNFW DM halos? If so, what is the inner slope allowed to be?

  9. Results • Definitely prefer a variable inner slope • Bayesian evidence larger by factor (2.2 ± 1.0) x 104 • Logarithmic inner slope β < 0.3 (68%), i.e. quite shallow

  10. Results • Also, neither model reproduces the flat velocity dispersion profile • How to match flat dispersion and lensing constraints at ~30-100 kpc?

  11. DM-only simulations • More modern cluster-scale simulations converge down to about 15 kpc/h • Hints that slope become progressively more shallow • But only on very small scales Navarro et al 2004

  12. Attempts to Include Baryons • Adiabatic contraction • Cooling baryons contract and “pinch” DM halo, steepening the cusp • e.g. Gnedin et al. 2004, Gustafsson et al. 2007, Abadi et al. 2009, Pedrosa et al. 2009, etc. • Cosmological N-body+gas dynamical simulations, with radiative cooling and attempts to include feedback processes • Dynamical friction • Infalling baryon clumps “heat” DM cusp, flattening it • e.g. El-Zant et al. 2001, Romano-Diaz et al. 2008, Nipoti et al. 2004 • Frequent simplifications: • Infallingsubhalos as purely baryonic • Sometimes as unstrippable point masses • Need to maintain clumps over sufficient timescales without fragmenting, forming stars

  13. Future • Find density profile that is more observationally acceptable • Not a lot of theoretical motivation because baryonic physics is not well enough understood • Extend to sample of ~10 clusters • All data collected for about half • For the rest, lack only velocity dispersions

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