Extending Robust Weak Lensing Masses to z~1. Douglas Applegate, Tim Schrabback & the SPT-Lensing Team

Transcription

1 Extending Robust Weak Lensing Masses to z~1 Douglas Applegate, Tim Schrabback & the SPT-Lensing Team 1

2 SPT Lensing Team Bonn Tim Schrabback Douglas Applegate Fatimah Raihan Chicago Brad Benson Lindsay Bleem John Carlstrom Adam Mantz University of Florida Anthony Gonzalez LMU Munich Joerg Dietrich Dominik Gangkofner I-Non Chiu Joseph Mohr Shantanu Desai Sebastian Bocquet Leiden Henk Hoekstra Stanford Anja von der Linden Steve Allen Harvard Chris Stubbs Berkeley Tijmen de Haan Hawaii Brian Stalder 2

3 Outline Why calibrate scaling relations at z~1 w/ lensing? SPT - HST Lensing Program: Estimating the redshift distribution of lensed galaxies Calibrating NFW halo fits to lensing data HST 2020 Visions: Towards < 5% 3

4 Exploring Beyond-ΛCDM Physics w a a t = 0.5 a t free ΛCDM γ Growth Index Clusters CMB Galaxies GR w σ 8 Mantz et al Looking for subtle redshift-dependent signals 4

5 SZ Surveys Extending Redshift Arm ~2x improvements w/rass+spt Mantz et al Bleem et al

6 Calibrating Scaling Relations with Lensing Planck vs WtG Lensing Planck Cosmology von der Linden et al. 2014b Planck XXIV

7 Calibrating Scaling Relations with Lensing σ Ω m Clusters WMAP Planck+WP WtG4 : counts + fgas Mantz

8 Calibrating Scaling Relations with Lensing WtG, CCCP DES Jee+2011: 25%bias in M-T? Bleem et al

9 SPT Lensing Programs DES-SV: Gangkofner+ in prep Magellan: High+12, Dietrich+ in prep HST: Schrabback+, Applegate+, in prep Bleem et al

10 Outline Why calibrate scaling relations at z~1 w/ lensing? SPT - HST Lensing Program: Estimating the redshift distribution of lensed galaxies Calibrating NFW halo fits to lensing data HST 2020 Visions: Towards < 5% 10

11 SPT-HST Lensing Sample Phase 1: Schrabback et al., in prep 13 clusters 0.6 z 1.1 NASA/ESA HST: 2 x 2 V x I814 VLT: FORS2 B + I + z imaging 11 w/ Chandra observations ~15% mass calibration Phase 2: PI: Schrabback A. Tudorica 45 clusters : 1 x V606 SNAP Acquiring Gemini-South GMOS colors ~9% mass calibration 11 Gemini Observatory/AURA

12 Systematic Uncertainties: From Shear to Mass Shear Profile Redshift Distribution Mass Model

13 Redshift Distribution Challenge: Solution: Select background galaxies Match in ref. field Remove cluster galaxies Minimize cosmic variance CANDELS 3photo-zs (3D HST: Skelton et al. 2014) 5 independent fields Similar filters, depths Processed with SPT-HST lensing pipeline Selecting same galaxy population Averaging out Cosmic Variance 13

14 Redshift Distribution Target Balmer/4000Å Break Average over CANDELS: β β < 2% VLT zp off 0.1mag: β β 5% Redshift Distribution Clusters Star-forming galaxies Lensing Efficiency β ~94% suppression 14 Schrabback et al., in prep.

15 Contamination by Cluster Galaxies f500 < 4.3% (95% UL) f500 < 11.5% (95% UL) V606 Magnitude Radius wrt R500 Includes magnification! 15 Schrabback et al., in prep.

16 Systematic Uncertainties: From Shear to Mass Shear Profile Redshift Distribution Mass Model

17 Calibrating NFW fits with Simulations MXXL Lensing sims: (S. Hilbert; Angelo et al. 2012) z=0.25, 1.0 snapshots Extends mass calibration to M200 > 2x10 15 M at z=0.25 Effects of Noise, FoV, & Survey:! ~18 gals/sq arcmin (ACS-only) inner 1.5 arc minutes ~5 gals/sq arcmin (ACS+FORS2) σ e = 0.4 2x2 ACS mosaic -> 6 x 6 arcmin 500 kpc Mpc Dec (J2000) Miscentering: SZ selected, <z> ~ h 59 m 54 s 48 s 42 s 0 h 00 m 00 s RA (J2000) 36 s 30 s 24 s Need to exactly mimic observations 17

18 Bias from Radially-Dependent Galaxy Density High galaxy density Typical survey Low galaxy density Exaggerated Space + Ground 18 Applegate et al., in prep

19 Bias From SZ Detection & Centering Dec (J2000) For z=1 cluster 0 h 00 m 0023 s h 59 m 54 s 48 s 42 s 36 s RA (J2000) 30 s 24 s SZ Peak offset from true center Miscentering distributions from hydro sims (Liu, Dolag) 19 Applegate et al., in prep

20 Contrast with Weighing the Giants von der Linden+14, Kelly+14, Applegate+14 WtG SPT-HST Redshift Range # of clusters Lensing Imaging SuprimeCam V,R ACS F606W Red Sequence Blue & Red cluster gal Redshift color cuts color cuts Distribution w/cosmos w/candels cross-cal w/photo-zs Mass Modeling Sim Calibration NFW, X-ray center Mpc Becker & Kravtsov 2011 Mass Scale 8% NFW, X-ray & SZ center Mpc Mocked observations on MXXL ~15% (moving towards ~9%) 20

21 Outline Why calibrate scaling relations at z~1 w/ lensing? SPT - HST Lensing Program: Estimating the redshift distribution of lensed galaxies Calibrating NFW halo fits to lensing data HST 2020 Visions: Towards < 5% 21

22 HST 2020 Vision: Towards < 5% Mass z~1 Low-z calibration improving to < 5% w/ DES, LSST match at high -z High mass, z~1 clusters in common between: SPT-3G (2016), Adv ACTpol (2016) erosita (2016) DES (ongoing), LSST, Euclid Scale existing SPT-HST program ~100 M x M clusters ~4% statistical mass calibration 22

23 HST 2020 Vision: Towards < 5% Mass z~1 100 most massive from extended SPT-SZ 3,750 sq. degrees 0.8 < z < & 4-pointing, single orbit F606 + F814 mosaics ( r 200 ) ~500 orbits w/ existing data + CVZ Optional NIR (eg, F140W) in core for cluster astrophysics & JWST target selection additional ~100 orbits HST better matched: JWST - too small FoV, z=1.5 WFIRST - need bluer filters, z=1.5 Euclid - 1/6 x background sources, no individual masses 23

24 Summary Need precision z=1 to disentangle cosmology from astrophysics SPT - HST Lensing Program: ~15% mass calibration - limited by # clusters CANDELS to estimate redshift distribution Calibration with MXXL simulations HST 2020 Visions: 100 clusters < 5% calibration ~600 orbits: F606 & F814 mosaics + F104 in core 24

25 Backup Slides

26 Simulation Comparison Applegate et al., in prep 26

27 Does Noise Affect Bias? 27

28 Eliminating Cluster Galaxies Ilbert

29 Previous Work at High Redshifts physical Journal, 737:59 (32pp), 2011 August 20 Jee et al clusters z > 0.8 (14 w/ X-ray) M-T norm low by 20-30% But: Jee et al. Heterogenous clusters UDF-only for redshifts Profile centering uncertainty Dynamical velocity dispersion vs. lensing prediction. We use filled present the results for the clusters studied here. Open circles show or the high-z clusters in our previous publications. The solid line he line of equality The linear fit to the result is shown with the dotted Applegate - SnowCluster 2015 e 1σ range of the slope is depicted by the gray region. Figure 25. X-ray temperature vs. lensing mass. As in Figure 24,et filled and2011 open Jee al. circles represent the current clusters studied here and the five clusters in our 29 publications. The slope of the power law α = 1.54 ± 0.23 (M T α ) is previous