Weak lensing measurements of Dark Matter Halos around galaxies

Transcription

1 Weak lensing measurements of Dark Matter Halos around galaxies Rachel Mandelbaum Carnegie Mellon University 1

2 Image credits: NASA, ESA, S. Beckwith (STScI), the HUDF Team 2

3 Image credit: ESA/Planck 3

4 The underlying reality (1d version) Density Galaxies Halo Position 4

5 Galaxy formation What dark matter, if any, is associated with this galaxy? What is the relationship between the visible and dark components? What about special galaxy types? What are the relevant processes in its formation and evolution? Picture credit: Sloan Digital Sky Survey data release 6 5

6 Galaxy formation What dark matter, if any, is associated with this galaxy? What is the relationship between the visible and dark components?? What about special galaxy types? What are the relevant processes in its formation and evolution? Picture credit: Sloan Digital Sky Survey data release 6 6

7 Gravitational lensing Sensitive to all matter along line of sight, including dark matter! 7

8 Weak lensing! Very small deflection angles! Coherent statistical distortion (shear, γ) of galaxy shapes! Does not require chance superposition like strong lensing Picture credit: LSST Science Book 8

9 Weak lensing Lensing depends on: Enclosed mass Distance from that mass Lensing kernel : distances to lens and source Picture credit: LSST Science Book 9

10 Galaxy- galaxy lensing! Cross- correlation: Lens galaxy positions versus source galaxy shapes! Reveals total matter distribution around lens galaxies or clusters (galaxy- mass correlation): Matter surface density Σ (a projection of 3d cross- correlation ξ gm ) 10

11 Galaxy- galaxy lensing! Cross- correlation: Lens galaxy positions versus source galaxy shapes Stack MANY of these systems:! Reveals total matter distribution around lens galaxies (galaxy- mass correlation): Matter surface density Σ (a projection of 3d cross- correlation ξ gm ) 11

12 Observed quantity Σ: surface density, i.e. ρ dχ (projected along line of sight) We actually observe ΔΣ(R) = <Σ(<R)> - Σ(R) Sensitive at R to all scales below R 12

13 After making a measurement We must interpret it in light of stacking and satellite effects! Some popular options:! Halo modeling (from 2 to 10+ parameters)! Restriction to isolated galaxies and small scales! Direct comparison with simulations / mock catalogs 13

14 What is a halo model? Velander et al. (2013) 14

15 Early results (SDSS) Sheldon et al. (2004): ~10 5 lenses, ~10 7 sources Luminosity trends Color 15

16 Mass modeling of lensing by isolated galaxies in RCS Hoekstra et al. (2005): Fit signals to NFW profiles M ~ L 1.5 Assumption: no scatter between mass and observables Early vs. late types (color): M halo /M * higher by factor of ~2 for early types; efficiencies of ~33%, 14% 16

17 SDSS (RM et al. 2006) Milky Way! Lensing signal vs. M * (split by morphology)! Small scales: M halo increases with M* ΔΣ! Simple halo model Early types Late types R [kpc/h] R [kpc/h] 17

18 Implications Errors: 68% CL! Stellar mass traces halo mass for M * <~ M sun M halo / (10 11 M sun /h)! At higher mass: similar results as η = M stellar M halo f b Hoekstra et al (2005)! Baryon conversion efficiencies peak around 30-40% M stellar / (10 10 M sun ) 18

19 GEMS: a different regime Heymans et al. (2006)! First study with a good redshift baseline! High stellar- mass galaxies! No mass scatter or halo modeling! η = 0.10 ±

20 COSMOS (Leauthaud et al. 2011) Self- consistent halo modeling of lensing, galaxy clustering, abundance No early vs. late type split Evolution with redshift for parameterized M halo /M* relation 20

21 RCS, CFHTLenS SDSS COSMOS CFHTLenS RCS! Significant decrease in lensing errors at low mass compared to previous studies! High- mass discrepancy with COSMOS:! Cosmic variance?! Stellar mass estimates?! Stellar mass function?! Different halo models?! Note: not as bad as it looks Figure from Velander et al. 21

22 Conditional luminosity function! 9- parameter model for ɸ(L M) + N- body van den Bosch et al. (2013)! Cacciato et al. (2014) showed ability of model to describe many galaxy samples in SDSS, RCS2! Constant σ logl ~ 0.146±0.11 (variable σ logm ) 22

23 GAMA (J. Han et al. 2014)! Mostly groups, but a few plots go to N gal =1! No split by type! Reasonable consistency with previous results, slight (~5-10%) possible offset in mean relation! Dependence on scatter in halo mass at fixed stellar mass log(mh[m /h]) GAMA(this work) SDSS late SDSS early CFHT blue CFHT red COSMOS M [M /h 2 ] 23

24 Special galaxy types! Radio- loud AGN (RM et al. 2009)! Surely there s more we can do here. R. Mandelbaum 2.5 disk galaxies (this work) late-types (Mandelbaum et al. 2006) late-types (Dutton et al. 2010) all galaxies (Leauthaud et al. 2011) 2.0 log (M200c/M )! Spiral galaxies chosen for ability to measure kinematics (Reyes et al. 2012, Dutton et al. 2010) Disk 5% 10% % 50% log M (M ) 100% 11.0 Figure 17. Constraints on the HSMR from simultaneous fits to the lensing signals for three stellar mass bins. The thick solid curve and dark and light grey shaded regions show the24 median relation and its 1 and 2 error envelopes. Best-

25 The future 25

26 Challenges What we want: M halo (M * or L, type) 26

27 Challenges What we want: M halo (M * or L, type) Morphology? Spectra? (limited availability) Colors from imaging data (tied up in photo- z estimate) Hudson et al. (2013) vs. Velander et al. (2013): Color vs. spectral type Luminosity vs. stellar mass (Some differences in modeling methods too) 27

28 Challenges What we want: M halo (M * or L, type) Spectra? (limited availability) Observed colors (tied up in photo- z estimate) Special issues for stellar mass: IMF Other, such as SPS model, form of SFH, dust attenuation (huge!! Leauthaud et al. 2012) Systematic uncertainties complicate comparison dn/dlogm * [Mpc -3 dex -1 ] Non IMF-systematic error margin COSMOS, this work, z~0.37 COSMOS, Drory et al. 2009, z~0.3 SDSS, Li et al SDSS, Baldry et al SDSS, Panter et al log 10 ( M * [M O ]) 28

29 Challenges What we want: M halo (M * or L, type) Isolated vs. not: is this okay? Halo modeling: Role of assembly bias? Use of N- body based halo mass function and other quantities. Baryonic effects? Simple vs. complicated, importance of assumptions Combination with other measurements Li et al. (2008) Figure 4. Age dependence of halo bias. Formation t solid lines are for youngest 20% halos; the thick gray l Poisson error. any halo masses, the strength of the age dependen 29 eral decreases with increasing halo mass. For h

30 Conclusions! WL measurements have already taught us a lot about the relationship between galaxy optical properties and their underlying halos! Upcoming large surveys will take us into interesting new regimes: higher redshift, lower stellar mass, more about special galaxy types! Data are high S/N, so modeling issues and galaxy selection are becoming important 30