Insights on galaxy evolution from the dark matter content of massive early-type galaxies Crescenzo Tortora

Transcription

1 Insights on galaxy evolution from the dark matter content of massive early-type galaxies Crescenzo Tortora ITP Zurich

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3 What is fun with dark matter (DM)?

4 DARK MATTER DC comics Futurama

5 come back to talk about science!

6 Cosmology Clusters Flat rotation curves Cosmic structures

7 Direct detection of dark matter (CDMS, CRESST, EDELWEISS, EURECA, SIMPLE, PICASSO, ZEPLIN, XENON, DEAP, ArDM, WARP, LUX, DAMA/NaI, DAMA/LIBRA, ) Indirect detection of dark matter (EGRET, MAGIC, PAMELA, AMANDA, IceCube, ANTARES, ) Unfortunately, no strong evidences emerge from these observations

8 Alternatives: MOND Extended theories of gravity (f(r), etc.)..but DM remains the best, most tested and simpler way to reproduce observations!

9 Overall DM content few hundred kiloparsecs Shankar et al Dark matter is times more than stars

10 In this talk DM fraction vs mass and size DM density and cuspiness DM fraction vs formation epoch few kiloparsecs Insights on galactic ingredients (IMF, halo contraction, star formation efficiency, etc.)

11 The physics behind

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14 baryons (SF efficiency) -1 = M cold M star Initial mass function (IMF) adiabatic contraction dark matter potential wells

15 Why central (<R eff ) dark matter fractions?

16 - Star formation efficiency - IMF and stellar population parameters - DM distribution and halo contraction - Infall processes - (Supernovae or AGN) feedback phenomena - Shock heating - Merging

17 Most of the spectro-photometric data are available in the central regions (typically within 1 effective radius, R eff, or few R eff ) More extended data (out to the outskirts of the galaxies) available for few galaxies

18 Data and procedures

19 Multiband photometry Stellar mass and population parameters (age and metallicity) Spectra (slit, IFU, etc) Velocity dispesion Strong gravitational lensing Total mass Mass model (SIS, constant M/L, NFW+light) Toy-models from CDM predictions and simulations

20 We model the total mass profile using a SIS SIS reproduces quite good the total mass profile in massive ETGs (e.g., Koopmans et al. 2006, Gavazzi et al. 2007)

21 Dark matter vs mass (size) and Fundamental Plane

22 Fundamental Plane Observed Virial Dressler et al Non-homologies Dark matter Stellar populations

23 Typically, DM fraction is calculated at a homogeneous scale radius, the effective radius (enclosing one-half of the total stellar mass) Taylor et al Cappellari et al Graves et al Grillo et al Hyde & Bernardi 2009 Auger et al. 2010

24 ~ 400 local galaxies from Prugniel & Simien (1996) Tortora et al Central DM fraction is an increasing function of luminosity/mass Bolton et al. 2007, Hyde & Bernardi 2009, La Barbera et al. 2010,

25 Similar trends are found if IMF or the galaxy model are changed Cardone et al Phenomenological model with variable M/L Cardone & Tortora 2010 NFW or Burkert for DM profile Cardone et al Semianalytical model

26 Napolitano, Romanowsky & Tortora 2010 The effective radius is the primary driver of DM fractions

27 Sample of intermediate-redshift gravitational lenses (SLACS survey) Tortora et al. 2010

28 A definitive analysis on dark matter!

29 SPIDER Spheroids Panchromatic Investigation in Different Environmental Regions SDSS + UKIDSS ~ 5000 massive ETGs with grizyjhk photometry structural parameters in all wavebands (determined using 2DPHOT, La Barbera et al. 2008) stellar masses derived from fitting synthetic models (Bruzual & Charlot 2003) to observed colours recomputed velocity dispersions which allow to probe the total mass different environments La Barbera et al (SPIDER I)

30 SIS Constant M/L profile M dyn > M star SIS Constant M/L Mass follows light (modelled as a Sérsic profile)

31 DM plane

32 Environment field satellites centrals

33 vs simulations Ruszkowski & Springel 2009 Non-contracted halo Contracted halo Onorbe et al High gas conversion efficiency Low gas conversion efficiency

34 CDM toy-model predictions NFW for DM profile with a c-mvir relation Standard profile Adiabatic contraction (AC, Blumenthal et al. 1986, Gnedin et al. 2004) Sersic law for the light distribution Empirical relations among parameters like stellar mass, size, galaxy age, etc. SF is a free parameter or fixed using literature trends (e.g. Conroy & Wechsler 2009) Dynamical mass and DM fraction

35 Dark matter density and cuspiness

36 Napolitano, Romanowsky & Tortora 2010 ETGs Non-contracted NFW DwEs Contracted NFW LTGs Evidence of cuspiness

37 Sample of intermediate-redshift gravitational lenses (SLACS survey) SLACS lenses LTGs

38 Dark matter vs formation epoch

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40 Sample of intermediate-redshift gravitational lenses (SLACS survey)

41 Older galaxies are more compact

42 CDM f DM -age toy-model predictions We divide the sample in stellar mass bins Size-age relation in each mass bin SF is left free f DM -age predictions

43 Halo contraction Kroupa IMF Standard CDM Salpeter IMF IMF-AC degeneracy Halo contraction Standard CDM

44 m m Salpeter IMF (many low mass stars) high stellar M/L Kroupa or Chabrier IMF (less low mass stars) low stellar M/L DM 10-30% 40-60% Toy-models Salpeter + NFW Chabrier+ contracted NFW

45 What behind this correlation?

46 Size-age (e.g., Khochfar & Silk 2006)

47 Size-age (e.g., Khochfar & Silk 2006) SF variation (e.g., Conroy & Wechsler 2009) low SF high SF

48 AC Size-age (e.g., Khochfar & Silk 2006) SF variation (e.g., Conroy & Wechsler 2009) no-ac AC variation younger systems showing AC

49 Size-age (e.g., Khochfar & Silk 2006) SF variation (e.g., Conroy & Wechsler 2009) AC variation younger systems showing AC IMF variation bottom-havier (Salpeter-like) IMF for younger systems

50 Work in progress on the DM-age correlation SPIDER SAURON...promising tool to test galaxy evolution processes

51 Conclusions Central DM driven by mass but mainly by the size (DM plane) First evidences of cuspiness in ETGs IMF halo contraction degeneracy An inverse correlation between DM fraction and formation time has been found It is possibly suggesting variations of star formation efficiency, IMF and halo contraction with age and/or mass Better data-quality and wider samples of galaxies to check the results and improve the physical implications

52 VST

53 Grazie