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The chemical enrichment of clusters of galaxies

The chemical enrichment of clusters of galaxies. Jelle S. Kaastra Collaborators: Norbert Werner, Jelle de Plaa, Aurora Simionescu, Yan Grange. Outline. Importance clusters Observational challenges Enrichment by supernovae Enrichment by winds Conclusions.

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The chemical enrichment of clusters of galaxies

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  1. The chemical enrichment of clusters of galaxies Jelle S. Kaastra Collaborators: Norbert Werner, Jelle de Plaa, Aurora Simionescu, Yan Grange

  2. Outline • Importance clusters • Observational challenges • Enrichment by supernovae • Enrichment by winds • Conclusions

  3. 1. Importance clusters for abundance studies • Largest bound structures • Deep potential wells, retains most of the gas • Hot gas: no significant “hiding” of metals in dust • Spatial extent allows mapping

  4. 2. Observational challenges • Fe bias • Non-thermal components • Complex temperature structure

  5. The Fe bias Multi-T 1T • 1T models sometimes too simple: e.g. in cool cores • Using 1T gives biased abundances (“Fe-bias, Buote 2000) • Example: core M87 (Molendi & Gastaldello 2001)

  6. Non-thermal components • Example: Sérsic 159-03 • Strong soft excess, modeled by non-thermal component • Implications on abundances (De Plaa et al. 2006)

  7. Complex temperature structure I(de Plaa et al. 2006) • Sérsic 159-3, central 4 arcmin • Better fits 1Twdemgdem • Implication for Fe: 0.360.350.24 • Implication for O: 0.360.300.19

  8. Inverse iron bias: how does it work? • Simulation: 2 comp, T=2 & T=4 keV, equal emission measure • Best fit 1-T gives T=2.68 keV • Fitted Fe abundance 11 % too high • Due to different emissivity for Fe-L, Fe-K

  9. Temperature maps(Hydra A, Simionescu et al. 2008)

  10. Complex temperature structure II(Simionescu et al. 2008) • Example: Hydra A • Central 3 arcmin: • Full spectrum: Gaussian in log T (σ=0.2) • 1T fits individual regions: also Gaussian • Confirmed by DEM analysis (blue & purple)

  11. Implications for Fe abundance(Simionescu et al. 2008) Central 3 arcmin Hydra A, 1T models: (errors on Fe 0.01 to 0.02)

  12. Fitting bias: continua ok?(Werner et al. 2006) • Some features subtle • Example: 2A0335+096, 130 ks XMM-Newton • To determine Cr abundance (0.5±0.2 solar) needs carefull analysis local continuum

  13. Fitting bias: calibration uncertainties(de Plaa et al. 2007) • Some lines (Si) weaker than calibration uncertainty instruments • Important to estimate systematic uncertainties (no “blind” χ2 fitting) Diffference pn data & best-fit MOS model Sérsic 159-03

  14. Quantifying systematics(de Plaa et al. 2007) • Correction: fudge MOS area to match pn and vice versa (spline) • Remaining difference systematic: • Mg: too uncertain • Si: 11 % • Ni: 19 % Example: Sérsic 159-03

  15. 3. Enrichment by supernovae

  16. Type Ia, Type II and Solar abundances O O

  17. Supernova yields: core collapse

  18. Supernova yields: Ia

  19. Decomposing abundances into SN types(De Plaa et al. 2006) • Deep exposure XMM-Newton Sérsic 159-3 • Data include RGS • ~50 % SN Ia by number • Ca problem

  20. Another case: 2A 0335+096(Werner et al. 2006) • Use here WDD model • Central 3 arcmin: • Sn Ia: 25 % • Increases to 37 % in 3-9 arcmin annulus • Ni: W7 model predicts more • Also here Ca problem

  21. Analysis of a large sample (De Plaa et al. 2007) • 22 clusters, 685 ks net exposure • Taken from HIFLUGCS sample (Reiprich & Böhringer 2002) • All spectra extracted from within 0.2 R500 • Use wdem model

  22. Solution to the Ca problem(De Plaa et al. 2007) • Also sample shows Ca excess • Problem solved by adopting SN Ia yields based on Tycho SNR (Badenes et al. 2006) • Best fit Ia/(Ia+cc) number ratio: 0.44±0.05 WDD Tycho

  23. Sample: mean abundance ratios(De Plaa et al. 2007)

  24. A 2052(Grange et al. 2008) • 90 ks exposure (2001, 2007) • Analysis in progress • Abundances O to Fe all consistent with sample De Plaa et al. (2007) • Only Ca more overabundant: Ca/Fe = 1.51±0.10 (compared to 1.03, σ=0.12) • Needs further confirmation

  25. Comparison between clusters(Simionescu et al. 2008) • 6 clusters with deep exposures, taken from literature • Most have 30-40 % contribution Ia • Hard to discriminate between Ia models, but see extremes Hydra A / M87

  26. Radial profiles: example 2A 0335+096(Werner et al. 2006) S Si Ar Fe

  27. Comparison between clusters: radial profiles(Simionescu et al. 2008) • All elements have decreasing abundances • Also valid for O (contrary to earlier suggestions of flat O profile, Tamura et al. 2004)

  28. Abundance ratios constant?(Simionescu et al. 2008) • Si/Fe flat within 0.1 R200, maybe break at 0.05R200 • O/Fe increases, but only slightly: per dex in radius, O/Fe increases by 0.25±0.09 (Fe decreases by 0.72) O/Fe Si/Fe

  29. Consequences of “flat” oxygen profiles(Simionescu et al. 2008) • Flattish O profiles:  not only Ia contribute to core enrichment • Ram pressure stripping works already at Mpc scale (compare to 130 kpc core Hydra A) • Continued cc SN activity over past 1010 year? • Early central enrichment cc SN?

  30. 4. Enrichment by winds

  31. XMM-Newton RGS results • RGS optimal for point sources • But still the best for moderately extended sources: • Δλ (Å) = 0.138 Δθ (arcmin)

  32. RGS results: M 87(Werner et al. 2006) • Exposure time: 169 ks • Lines from O, N, & C • C/Fe: 0.74±0.13 • N/Fe: 1.62±0.21 • O/Fe: 0.59±0.04 • Ne/Fe: 1.25±0.12 • Mg/Fe: 0.60±0.06 • Fe: 1.06±0.03 •  AGB winds for CN! Continuum-subtracted RGS spectrum

  33. Nitrogen with RGS: other cases • M87: N/Fe = 1.62±0.21 • 2A 0335+096 (Werner et al. 2006): 1.3±0.4 • Sérsic 159-3 (De Plaa et al. 2006): 0.0±0.5 • Centaurus (Sanders et al. 2008): 1.5-3 • Need for more deep exposures with RGS

  34. Other case: Centaurus(Sanders et al. 2008) N/Fe=1.5-3

  35. Future: SXC(and of course XEUS etc)

  36. 5. Conclusions • XMM-Newton observations of clusters of galaxies can disentangle contributions different SN types and winds • Need take care of systematics, in particular temperature distribution for reliable results • Best done using deep exposures

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