The chemical enrichment of clusters of galaxies

Jelle S. KaastraCollaborators:

Norbert Werner, Jelle de Plaa, Aurora Simionescu, Yan Grange

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Outline

1. Importance clusters

2. Observational challenges

3. Enrichment by supernovae

4. Enrichment by winds

5. Conclusions

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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

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2. Observational challenges

1. Fe bias

2. Non-thermal components

3. Complex temperature structure

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The Fe bias

• 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)

Multi-T 1T

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Non-thermal components

• Example: Sérsic 159-03

• Strong soft excess, modeled by non-thermal component

• Implications on abundances (De Plaa et al. 2006)

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Complex temperature structure I(de Plaa et al. 2006)

• Sérsic 159-3, central 4 arcmin

• Better fits 1Twdemgdem

• Implication for Fe: 0.360.350.24

• Implication for O: 0.360.300.19

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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

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

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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)

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Implications for Fe abundance(Simionescu et al. 2008)

Central 3 arcmin Hydra A, 1T models:

(errors on Fe 0.01 to 0.02)

Band (keV) kT (keV) Fe

Full (0.35-10) 3.4 0.50

Low (Fe-L) 0.35-2 2.8 0.37

High (Fe-K) 2-7 3.9 0.41

Gdem 3.4, σ=0.2 0.45

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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

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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

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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

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3. Enrichment by supernovae

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Type Ia, Type II and Solar abundances

O

O

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Supernova yields: core collapse

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Supernova yields: Ia

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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

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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

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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

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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

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

RatioWeighted mean

(Lodders scale)σint

Si/Fe 0.66 ± 0.13 0.17 ± 0.05

S/Fe 0.60 ± 0.06 0.18 ± 0.06

Ar/Fe 0.40 ± 0.03 0.11 ± 0.05

Ca/Fe 1.03 ± 0.04 0.12 ± 0.08

Ni/Fe 1.41 ± 0.31 0.2 ± 0.2

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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

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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

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Radial profiles: example 2A 0335+096(Werner et al. 2006)

Si

FeAr

S

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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)

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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

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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?

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4. Enrichment by winds

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XMM-Newton RGS results

• RGS optimal for point sources

• But still the best for moderately extended sources:

• Δλ (Å) = 0.138 Δθ (arcmin)

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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

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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

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Other case: Centaurus(Sanders et al. 2008)

N/Fe=1.5-3

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Future: SXC(and of course XEUS etc)

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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