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Cosmology with the XMM Cluster Survey (XCS)
Martin Sahlén, University of Sussex with Pedro Viana (Porto), Andrew Liddle, Kathy Romer (PI) and others (XCS Consortium) COSMO ’07, University of Sussex, 22 August 2007
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M. Sahlén - Cosmology with the XCS
Outline Why Galaxy Clusters? From Theory to Predictions: Simulation and Observation The XMM Cluster Survey Forecasts Status and Conclusions M. Sahlén - Cosmology with the XCS
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M. Sahlén - Cosmology with the XCS
Why Galaxy Clusters? Galaxy clusters: largest grav. bound objects, hot intracluster gas – bremsstrahlung (X-ray) Cluster abundance exponentially sensitive to σ8 and ΩM → good constraining power Probe structure formation; constraints complementary to CMB, SNIa, etc. Knop et al. 2003 Allen et al. 2004 M. Sahlén - Cosmology with the XCS
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Why Galaxy Clusters Again?
Explain different scenarios. Getting L-T evolution and/or scatter wrong -> get constraints completely wrong WHY TWO CONSTRAINTS GET OMEGA_M SO GOOD??? M. Sahlén - Cosmology with the XCS
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Theoretical Components
n(M, z) – comoving number density of clusters M(O, z) – relation between halo mass and direct observable dV/dz – cosmic volume evolution fsel(O,z) – probability of detecting a given cluster Uncertainties in observables and relations Define O_lim, number density w redshift M. Sahlén - Cosmology with the XCS
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Dynamics of Cluster Science
THEORY SIMULATIONS FITTING FORMULAE IC’s Particle physics Gravita-tional theory Cosmo-dynamics Cluster dynamics Mass function Jenkins et al. 2001 Bias Sheth & Tormen 1999 Halo conc. Neto et al. 2007 e.g. Virgo Hubble Volume e.g. XCS Mass-observable relations Muanwong et al. 2006 OBSERVATIONS
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M. Sahlén - Cosmology with the XCS
Mass Function Jenkins mass function; Jenkins et al. 2001 Pδ(k) - PS of density contrast; depends on primordial PS, transfer function and perturbation growth suppression factor Primordial spectrum specified, transfer function and growth factor determined by cosmology Here: parameterisation for σ(R); Viana & Liddle 1996 M. Sahlén - Cosmology with the XCS
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Mass-Observable/Scaling Relations
Luminosity-Temperature Mass-Temperature Evolution (γ, δ, η, ν) Self-similar γ = 1/2, η = 1/3 Scatter (σlogL, σlogT) Self-calibration and follow-up Explain L-T: local L-T and a redshift dependence. Self-sim case, power-law case, scatter in local. Same for M-T The scaling relation parameters can be constrained simultaneously with cosmological params: self-calibration – cluster surveys have this capability. Follow-up direct observations too. e.g. Levine et al. 2002, Lima & Hu 2004, 2005, Majumdar & Mohr 2004 M. Sahlén - Cosmology with the XCS
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XMM Cluster Survey (XCS)
Mining XMM-Newton images X-ray temperature, flux, redshift 2 keV < T < 8 keV, zmax = 1.45 500 □˚ Important ‘pathfinder’ survey for e.g. SPT, E-ROSITA, and DES (XCS collaboration) M. Sahlén - Cosmology with the XCS
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M. Sahlén - Cosmology with the XCS
Selection Function Calculated using cluster detection pipeline with mock clusters - numerically very intensive to compute (months) Dependencies include: Halo model X-ray spectrum Detector characteristics Cosmology M. Sahlén - Cosmology with the XCS
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Detecting Mock Clusters
Mock cluster added to image Original XMM-Newton image Original source detection Mock source detection M. Sahlén - Cosmology with the XCS
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From Theory to Predictions
N-body/hydrodynamic simulations - full non-linear treatment, necessary! Mass function, mass-observable relations, etc. calibrated to simulations/observations Selection function: simulations using the detection pipeline Used along with cosmology to make predictions M. Sahlén - Cosmology with the XCS
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Expected Number Counts
Full XCS; ΩM = 0.3 ΩΛ = 0.7 σ8 = 0.8 Self-sim M-T Scatter: σlogL = 0.3 σlogT = 0.1 Explain axes. Self-sim M-T. Just self-sim does not add that much, Scatter adds significantly. M. Sahlén - Cosmology with the XCS
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Expected Constraints, Full XCS
Fiducial: ΩM = 0.3 ΩΛ = 0.7 σ8 = 0.8 Self-similar M-T No scatter 500 □˚ 2 keV < T < 8 keV 0.1 < z < 1 Flat universe Flat universe – folding in WMAP. No scatter. Self-sim M-T good description of data. Two evolution cases. Linear excellent fit to self-similar. XCS SCAL REL Spt: also need smthg like xcs for calibration Erosetta approved xray survey, not as sensitive or spatial res as xcs, kind of xcs full sky, xcs pathfinder, can NOT meas temperature! Need to calibrate scal rel to pther data. planck all sky same no, higher mass, low z, calibration to xmm survey (can’t use xcs) des quarter-half sky clusters, optical, mass-optical relation is problem – xcs ppl helping with des for this – if calibration ok, can do DE evoln. Requires xcs! M. Sahlén - Cosmology with the XCS
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M. Sahlén - Cosmology with the XCS
Systematic Biases Explain different scenarios. Getting L-T evolution and/or scatter wrong -> get constraints completely wrong WHY TWO CONSTRAINTS GET OMEGA_M SO GOOD??? Does not appear to be coincidence but we are looking into how general these results are. M. Sahlén - Cosmology with the XCS
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M. Sahlén - Cosmology with the XCS
Status XCS DR1 168 □˚ Exp. ~ clusters with >500 photons and T > 2 keV 166 candidates, 119 confirmed with redshift, BUT clusters with T < 2 keV not excluded yet Results expected late 2008 Full XCS 500 □˚ Exp. ~ clusters with >500 photons and T > 2 keV Results expected 2010 M. Sahlén - Cosmology with the XCS
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M. Sahlén - Cosmology with the XCS
Conclusions Cluster cosmology can be modeled using N-body/hydrodynamic simulation results tuned to observations A comprehensive MCMC forecasting and data analysis code has been developed M. Sahlén - Cosmology with the XCS
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M. Sahlén - Cosmology with the XCS
Conclusions XCS DR1 (2008): σ8 to 15%, ΩM to 25% (~WMAP3) Full XCS (2010): σ8 and ΩM to 5% Knowledge of L-T scatter and evolution necessary (self-calibration/follow-up) XCS is a key step for cluster surveys Allowing curvature reduces by about 5-10 percentage points. M. Sahlén - Cosmology with the XCS
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M. Sahlén - Cosmology with the XCS
Ongoing Work Self-calibration Temperature & redshift errors Future/reference surveys M. Sahlén - Cosmology with the XCS
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