Insights on galaxy evolution from the dark matter content of massive early-type galaxies Crescenzo Tortora ITP Zurich
What is fun with dark matter (DM)?
DARK MATTER DC comics Futurama
come back to talk about science!
Cosmology Clusters Flat rotation curves Cosmic structures
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
Alternatives: MOND Extended theories of gravity (f(r), etc.)..but DM remains the best, most tested and simpler way to reproduce observations!
Overall DM content few hundred kiloparsecs Shankar et al. 2006 Dark matter is 10-20 times more than stars
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.)
The physics behind
baryons (SF efficiency) -1 = M cold M star Initial mass function (IMF) adiabatic contraction dark matter potential wells
Why central (<R eff ) dark matter fractions?
- Star formation efficiency - IMF and stellar population parameters - DM distribution and halo contraction - Infall processes - (Supernovae or AGN) feedback phenomena - Shock heating - Merging
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
Data and procedures
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
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)
Dark matter vs mass (size) and Fundamental Plane
Fundamental Plane Observed Virial Dressler et al. 1987 Non-homologies Dark matter Stellar populations
Typically, DM fraction is calculated at a homogeneous scale radius, the effective radius (enclosing one-half of the total stellar mass) Taylor et al. 2010 Cappellari et al. 2006 Graves et al. 2010 Grillo et al. 2010 Hyde & Bernardi 2009 Auger et al. 2010
~ 400 local galaxies from Prugniel & Simien (1996) Tortora et al. 2009 Central DM fraction is an increasing function of luminosity/mass Bolton et al. 2007, Hyde & Bernardi 2009, La Barbera et al. 2010,
Similar trends are found if IMF or the galaxy model are changed Cardone et al. 2009 Phenomenological model with variable M/L Cardone & Tortora 2010 NFW or Burkert for DM profile Cardone et al. 2011 Semianalytical model
Napolitano, Romanowsky & Tortora 2010 The effective radius is the primary driver of DM fractions
Sample of intermediate-redshift gravitational lenses (SLACS survey) Tortora et al. 2010
A definitive analysis on dark matter!
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. 2010 (SPIDER I)
SIS Constant M/L profile M dyn > M star SIS Constant M/L Mass follows light (modelled as a Sérsic profile)
DM plane
Environment field satellites centrals
vs simulations Ruszkowski & Springel 2009 Non-contracted halo Contracted halo Onorbe et al. 2007 High gas conversion efficiency Low gas conversion efficiency
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
Dark matter density and cuspiness
Napolitano, Romanowsky & Tortora 2010 ETGs Non-contracted NFW DwEs Contracted NFW LTGs Evidence of cuspiness
Sample of intermediate-redshift gravitational lenses (SLACS survey) SLACS lenses LTGs
Dark matter vs formation epoch
Sample of intermediate-redshift gravitational lenses (SLACS survey)
Older galaxies are more compact
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
Halo contraction Kroupa IMF Standard CDM Salpeter IMF IMF-AC degeneracy Halo contraction Standard CDM
0.2 0.15 m 0.1 0.05 0 0 1 2 3 4 5 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
What behind this correlation?
Size-age (e.g., Khochfar & Silk 2006)
Size-age (e.g., Khochfar & Silk 2006) SF variation (e.g., Conroy & Wechsler 2009) low SF high SF
AC Size-age (e.g., Khochfar & Silk 2006) SF variation (e.g., Conroy & Wechsler 2009) no-ac AC variation younger systems showing AC
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
Work in progress on the DM-age correlation SPIDER SAURON...promising tool to test galaxy evolution processes
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
VST
Grazie