1. THE PROPERTIES OF X-RAY BRIGHT GALAXY GROUPS F. GASTALDELLO Università di Bologna e California Irvine NGC 5044 Buote et al. 2002

2. Focus on observations of X-ray bright groups: the high mass end of the distribution, collapsed and evolved Mass properties Entropy profiles and non gravitational heating Metal abundances in groups and metal enrichment AGN feedback (briefly) OUTLINE OF THE LESSON

3. Properties of groups Constitutes the most common galaxy association, at least 50% of all galaxies at the present day are in groups (e.g Tully 1987)

4. Properties of groups I will not treat spiral only groups, like the Local Group or groups with very faint X- ray emission. Thet are still important though and there is active search to look for diffuse gas (through X-ray/UV absortion) in the Local Group, for example.

5. Structure formation: galaxies groups clusters Problems in the optical (small statistic) overcomed by the discovery of X- ray emission (hints from Einstein, main leap with ROSAT and ASCA): ~50% of all nearby groups have an hot X-ray emitting IGM Extended, usually centered on the brightest elliptical. Similar in many respects to the cool core clusters Properties of groups ROSAT X-RAY CONTOURS ON DSS IMAGES MULCHAEY 2003

6. Properties of groups and clusters BHACALL 1999 CLUSTERS GROUPS/POOR CLUSTERS L X (erg/s) 10 43 - 10 45 10 41.5 - 10 43 kT X (keV) 2 – 15 ≤ 2 N gal 100-1000 5 – 100 σ v (km/s) 500-1200 (median 750) 200 – 500 M tot (< 1.5 Mpc) 10 14 – 5 x 10 15 10 12.5 - 2 x 10 14 Number Density 10 -5 – 10 -6 Mpc -3 10 -3 – 10 -5 Mpc -3 Groups and poor clusters provide a natural and continuous extension to lower mass, size, luminosity and richness of rich, massive and rare clusters

7. Wealth of emission lines: O, Fe, Si, S allows investigation of supernova enrichment But groups are not scaled down versions of clusters Properties of groups 1.Different galaxy evolution: galaxy-galaxy interaction rather than ram-pressure stripping, because of lower velocity dispersions 2.Not closed box: non-gravitational processes, given the small potential well, have a bigger impact NGC 5044 CORE XMM

8. Compare apples with apples … MULCHAEY 2003 X-ray groups are fainter and they can be observed only to smaller radii compared to clusters: something to bear in mind when doing comparisons

9. Surface Brightness profiles HELSDON & PONMAN 2000 Central excess over the frequently adopted  model, as in cool core, relaxed clusters

10. T profiles BUOTE 2000

11. T profiles BUOTE 2000 Already with ROSAT data, evidence of a characteristic temperature profile

12. X-RAY MASS DETERMINATION Spectra averaged within circular annuli Normalization / shape of spectrum gives gas density / temperature

13. X-RAY MASS DETERMINATION 1. Assume spherical symmetry 2. Fit spectra with coronal plasma models and obtain (deprojected) spectral quantities 3. Fit parameterized functions to radial profiles of gas density and temperature 4. Assume hydrostatic equilibrium 5. Calculate the radial mass profile

14. DATA ANALYSYS Fit gas density and temperature simultaneously assuming only parameterizations for temperature and mass.Fit gas density and temperature simultaneously assuming only parameterizations for temperature and mass.Advantages: better constraints on Mbetter constraints on M easy to interpret goodness of fiteasy to interpret goodness of fit

15. DATA ANALYSYS “Parametric mass method” is the principal approach of the study: we assume parameterizations for the temperature and mass profiles to calculate the gas density assuming HE Gas density solution We considered also the temperature solution

16. DATA ANALYSIS NGC 1550 Projection of the 3D ρ and T thus obtained to the results from spectral analysis, including the radial variation of the plasma emissivity  (T,Z Fe ). Using an onion peeling deprojection (e.g., Fabian et al. 1981) gives consistent results with the above method Spectroscopic like T problem (e.g., Vikhlinin et al. 2005). Folding through responses : no change in the case of NGC 5044

17. BKG SUBTRACTION Bkg subtraction is crucial. Usual methods like simple use of bkg templates or double subtraction (Arnaud et al. 2002) have some flaws We completely model the various bkg components (Lumb et al. 2002), exploiting the fact that the source component, mainly characterized by the Fe-L shell, is clearly spectrally separated from the other bkg components

18. BKG MODELLING NGC 5044 offset Buote et al. 2004

19. BKG MODELLING MKW 4

20. SCALED TEMPERATURE PROFILES

21. A SPECIAL ERA IN X-RAY ASTRONOMY ChandraXMM-Newton 1 arcsec resolution High sensitivity due to high effective area, i.e. more photons

22. GASTALDELLO ET AL. 2007

23. RESULTS FOR MASS After accounting for the mass of the hot gas, NFW + stars is the best fit model MKW 4 NGC 533

24. RESULTS FOR MASS No detection of stellar mass due to poor sampling in the inner 20 kpc or localized AGN disturbance NGC 5044 Buote et al. 2002

25. NFW a good fit to the mass profile Pointecouteau et al. 2005 Clusters X-ray results

26. MASS SUMMARY NFW is a good fit also for massive groups DM collapse seems to be understood also at these scales, less massive than rich clusters

27. Breaking of self-similarity and entropy “floor” In the widely accepted hierarchical cosmic structure formation predicted by cold dark matter models and in the absence of radiative cooling and supernova/AGN heating, the thermodynamic properties of the hot gas are determined only by gravitational processes, such adiabatic compression during collapse and shock heating by supersonic gas accretion (Kaiser 1986) clusters and group of galaxies should follow similar scaling relations, for example if emission is bremsstrahlung and gas is in hydrostatic equilibrium L  T 2 and if we define as “entropy” K = T/n 2/3, then K  T (so S=k lnK + s 0, it’s also called adiabat because P = K ρ γ )

28. The L-T relation Mulchaey 2000 It has been clear for many years that the cluster L-T relation does not follow the L  T 2 slope expected for self-similar systems. In practice, L  T 3 for clusters (Edge & Stewart 1991), with possible further steepening to L  T 4 in group regime (Helsdon & Ponman 2000)

29. X-ray surface brightness Ponman, Cannon & Navarro 1999 Overlay of scaled X-ray surface brightness profiles shows that emissivity (hence  gas ) is suppressed and flattened in cool (T<4 keV) systems, relative to hot ones.

30. Entropy in the IGM Entropy floor Self-similar scaling Ponman et al. (1999) & Lloyd-Davies et al (2000) studied ROSAT and ASCA data for a sample of clusters  core entropy appeared to show a “floor” at ~100-150 keV cm 2 at r=0.1 r 200.

31. Entropy in the IGM A larger study, of 66 systems by Ponman et al. (2003), now indicates that there is not a “floor” but a “ramp”, with K(0.1r 200 ) scaling as K  T 2/3, rather than the self- similar scaling of K  T. KTKT

32. PROPOSED EXPLANATIONS 1.EXTERNAL PREHEATING MODELS: the IGM was heated prior to the formation of groups and clusters (e.g. Tozzi & Norman 2001) results in isoentropic cores 2.INTERNAL HEATING MODELS: the gas is heated inside the bound system by supernovae or AGN (e.g. Loewenstein 2000) 3.COOLING MODELS: low entropy gas removed from the system, producing an effect similar to heating (e.g. Voit & Bryan 2001) All three models can reproduce the L-T relation and excess entropy but with some problems: 1 requires too large amount of energy at high redshift 2 requires 100% efficiency from supernovae or fine tuning for AGN 3 overpredicts the amount of stars in groups and clusters More realistic scenarios with both heating and cooling are required (e.g. Borgani et al. 2002)

33. External preheating models with different levels of heating. Large isoentropic cores are produced Internal heating with rising entropy profiles BRIGHENTI & MATHEWS 2001

34. Entropy in the intracluster medium Voit, Kay & Bryan 2004 Non-radiative simulations produce clusters with self- similar entropy profiles K(r)=aT (r/r 200 ) 1.1

35. Entropy in the IGM Higher quality data from XMM and Chandra shows the lack of isentropic cores (e.g. Pratt & Arnaud 2002, Sun et al. 2004). The K  T 2/3 scaling is confirmed, but there is more scatter in entropy for groups. Sun et al 2004

36. Entropy in the IGM This scatter is shown in this small sample by Mushotzky et al. 2003. Reflects the relative history of the object, when and where the heat was produced relative to the collapse epoch of the object ? Mushotzky et al. 2003

37. COMPARISON WITH MASSIVE CLUSTERS AND GRAVITATIONAL SIMULATIONS PRATT ET AL. 2006

38. ENTROPY PROFILES

39. GASTALDELLO ET AL. 2008, IN PREP.

40. ENTROPY PROFILES GASTALDELLO ET AL. 2008, IN PREP.

41. COMPARISON WITH MASSIVE CLUSTERS AND GRAVITATIONAL SIMULATIONS GASTALDELLO ET AL. 2008, IN PREP.

42. COMPARISON WITH MASSIVE CLUSTERS AND GRAVITATIONAL SIMULATIONS GASTALDELLO ET AL. 2008, IN PREP.

43. GAS FRACTIONS GASTALDELLO ET AL. 2007

44. ENTROPY SUMMARY BROKEN POWER LAW ENTROPY PROFILES FOR GROUPS WITH STEEPER INNER SLOPES AND FLATTER OUTER SLOPES SEEM TO POINT TO HIGHER IMPORTANCE OF FEEDBACK PROCESSES WITH RESPECT TO MASSIVE CLUSTERS LOWER GAS FRACTIONS ARE ANOTHER EVIDENCE OF THIS FACT

45. Iron abundance in the ICM is nearly the same for all massive clusters, ~ 0.3-0.4 solar (De Grandi et al. 2003, Tozzi et al., 2004) and the M Fe /L B ~ 0.015 (Loewenstein 2004) uniform enrichment everywhere Groups are different: you can not reproduce the same results of clusters with the same IMF and supernovae yields (e.g Brighenti & Mathews 1999). M Fe /L B much lower in groups: loss of metal rich gas expelled by supernova driven winds when most of the galactic stars formed. Or star formation less efficient (Springel & Hernquist 2003) ? Properties of groups: Abundances RENZINI 2000

46. Chandra inner regions XMM outer regions NGC 533 DATA ANALYSYS

47. The Fe Bias  Fitting multi T spectrum with single temperature models give underestimated abundances (“Fe bias” Buote 2000)  Multiple components may arise from a radially varying single- phase gas or represent real multi-phase gas  Strongest evidence from Xmm observation of M87 (Molendi & Gastaldello 2001, Molendi 2002)

48. DATA ANALYSIS Chandra is crucial in the inner region where a steep temperature gradient is present When data are available, we use Chandra in the core and XMM in the outer regions

49. Relaxed and Not Relaxed Clusters Central abundance gradient,  Flat profile further out similar to unrelaxed clusters CC (relaxed clusters) NCC (not relaxed clusters) ●CC oNCC De Grandi & Molendi (2001)

50. Abundance Gradients in Groups Central abundance gradient, similar to relaxed clusters RASMUSSEN & PONMAN 2007

51. Are abundances in groups lower? A montage of group abundance profiles from Chandra (Helsdon) suggests that they drop to ~0.1 solar outside the core region (cf Buote et al 2004 study of NGC5044).

52. Abundance Gradients in Groups

53. FOSSIL GROUPS Merger timescales for the brightest members in densest groups much less than an Hubble time (Ponman 1993) Fossil groups can form: a single giant elliptical surrounded by dwarf galaxies and with a group-size X-ray halo They have been found in deep X-ray surveys with ROSAT (e.g. Ponman et al. 1994, Vikhlinin et al. 1999) PONMAN ET AL. 1994 Fossil groups are excellent venues to study supernova enrichment: the undisturbed X-ray gas preserves in its radial distribution information about supernovae events from the earliest times, something lost in rich clusters

54. NGC 5044 OFFSET Fe abundance nearly constant beyond 150 kpc at an extremely low value of 0.15 solar. If this offset region is azimuthally representative, then M Fe /L B = 0.007. But the baryon mass fraction is f b ~ 0.14, only slightly less than the WMAP value of 0.16 (Spergel et al. 2003). Some inaccuracies can derive by extrapolation from the observed 327 kpc to the virial radius of 870 kpc. Nevertheless, 15% of the baryons have been ejected containing half of the iron ! BUOTE ET AL. 2004 We can quantify the iron enrichment from dwarfs using an on-the spot approximation. This falls short by a factor of 3-4 and can seriously affect our understanding of enrichment by galactic winds.

55. NGC 5044 OFFSET POSSIBLE EXPLANATIONS: Stars in NGC 5044 does not produce iron with the same efficiency as in clusters, i.e. SNIa in dwarfs are not at the expected rate or fail to enrich the gas Iron selectively ejected from the group High entropy gas enriched and heated by early SNII and SNIa may not have penetrated deeply inside because of its buoyancy The southern offset observation is not representative

56. NGC 5044 OFFSET dE galaxies and gas enter the group via cosmic accretion filaments NSEW Number1682017 L B (10 10 sol.)0.800.0451.451.64 If the Fe abundance is significantly higher in the western offset, this would demonstrate that metals can be very inhomogeneous and strong evidence that matter enter groups along filaments

57. AGN FEEDBACK THE “OLD” MASS SINK PROBLEM IS NOW THE “FEEDBACK PROBLEM” AGN FEEDBACK, PUT ON A FIRMER GROUND BY THE CHANDRA IMAGES, HAS BROADER ASTROPHYSICAL IMPLICATIONS FOR GALAXY FORMATION AND EVOLUTION STILL POORLY INVESTIGATED AT THE GROUP SCALE

58. Fabian et al. 2003

60. NGC 5044 AGAIN …

62. CAON ET AL. 2000

63. DUST IN NGC 5044 TEMI, BRIGHENTI & MATHEWS 2007