1 / 28

An XMM-Newton spatially resolved study of metal abundance evolution in distant galaxy clusters

An XMM-Newton spatially resolved study of metal abundance evolution in distant galaxy clusters. Alessandro Baldi Astronomy Dept. - University of Bologna INAF - OABO. In collaboration with:

thalia
Download Presentation

An XMM-Newton spatially resolved study of metal abundance evolution in distant galaxy clusters

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. An XMM-Newton spatially resolved study of metal abundance evolutionin distant galaxy clusters Alessandro Baldi Astronomy Dept. - University of Bologna INAF - OABO In collaboration with: S. Ettori(INAF-OABO), S. Molendi (INAF-IASF MI), I. Balestra(MPE-Garghing), F. Gastaldello (INAF-IASF MI), P. Tozzi (INAF-OATS)

  2. Talk Outline Introduction to galaxy clusters and metal abundance studies Data reduction and analysis of the XMM-Newton cluster sample Spectral fitting strategy & global X-ray properties of the sample Results on abundance evolution & comparison with previous works Further work in progress and a glimpse to the future…

  3. Why clusters of galaxies? Clusters of galaxies are the largest virialized structures in the Universe, arising from gravitational collapse of high peaks of primordial density perturbations. They represents unique signposts in the Universe, where the physical properties of the cosmic diffuse baryons can be used to trace the past history of cosmic structure formation (e.g. Peebles 1993; Rosati et al. 2002; Voit 2005). The hot thin gas permeating the cluster gravitational potential tipically reaches T≈107-108 K and emits in the X-rays via thermal bremsstrahlung. Jenkins et al. (1998) A 1689 Peng et al. (2008)

  4. Why clusters of galaxies? • X-ray studies of galaxy clusters provide: • an efficient way of mapping the overall structure and evolution of the Universe; • an invaluable means of understanding their internal structure and the overall history of cosmic baryons. • The hot gas is chemically enriched by SN explosions, whose signatures are visible in the X-ray spectra as emission lines (e.g. Werner+ 2006, 2007) • The distribution of metals in the ICM, as well as their evolution as a function of z are the ‘footprint’ of cosmic star formation history and crucial to trace the effect of SN feedback on the ICM in different cosmic epochs (e.g. Ettori 2005; Borgani+ 2008) 2A 0335+096 Sersic 159-03 Werner+ 2006, 2007

  5. Metal distribution in clusters:ROSAT, ASCA & BeppoSAX • Several studies have been presented in the literature on the radial distribution of Z in galaxy clusters • ROSAT & ASCA: Finoguenov, David & Ponman (2000) derived the radial distribution of Fe, Si, Ne and S on 11 relaxed CC clusters, where they found that: • the total Fe abundance decreases with radius • the Si, Ne and S abundances are either flat or decrease less rapidly • BeppoSAX: De Grandi & Molendi (2001) on 17 nearby clusters (9 CC & 8 NCC at z < 0.1) found: • a strong enhancement in the abundance in the central regions of the CC clusters • a flatter Z profile in the NCC clusters • the metallicity in CC clusters is higher than in NCC clusters at every R • similar results where also found by Irwin & Bregman (2001) on 12 clusters at 0.03 ≤ z ≤ 0.2 CC De Grandi & Molendi (2001) NCC

  6. Metal distribution in clusters:XMM-Newton & Chandra • XMM-Newton: • Leccardi & Molendi (2008), using XMM-Newton data on 50 clusters, found that <Z>≈0.45 Z in the center and decreases out to ≈0.2 r180; beyond 0.2r180 the profile is consistent with being flat at Z≈0.25 Z. • Chandra: • Vikhlinin et al. (2005) on a sample of 11 low redshift CC clusters observed a negative gradient in the distribution of Z, peaked toward the center. • Baldi et al. (2007) on a sample of 7 CC and 5 NCC clusters observed a negative gradient in both CC and NCC clusters, steeper in CC and flatter in NCC. Leccardi & Molendi 2008

  7. Measures of metal content at high z • Balestra et al. (2007) obtained single emission-weighted estimates of 56 clusters (at 0.3 < z < 1.3) from Chandra and XMM-Newton • Measuring Fe abundance within (0.15-0.3) Rvirthey found a negative evolution of Z(Fe) withz: • Z(Fe) ≈ 0.4 Z at 0.3 ≤ z ≤ 0.5 • Z(Fe) ≈ 0.25 Z at z ≥ 0.5 • This result has been confirmed by Maughan et al. (2008) on a sample of 116 Chandra clusters at 0.1 < z < 1.3, where Z drop by 50% between z=0.1 and z≈1 • This evolution is not simply driven by the appearance or disappearance of the cool cores Maughan et al. (2008)

  8. XMM-Newton high redshift cluster sample • We selected a sample of 39 galaxy clusters at 0.4 < z < 1.4 from the XMM-Newton archive, with sufficient S/N to perform a spatially resolved spectral analysis (2-3 bins). • Taking advantage of EPIC XMM-Newton high throughput and effective area, we performed a spatially resolved spectral analysis of the clusters in the sample. • The aim of this work is to determine if the decrease of Z with redshift observed by Balestra et al. & Maughan et al. is due entirely to physical processes associated with the production and release of Fe into the ICM, or partially associated with a redistribution of metals connected to the evolution of cool cores.

  9. XMM-Newton high redshift cluster sample Baldi et al. 2011 (A&A submitted)

  10. XMM-Newton data reduction and analysis Observation Data Files (ODF) processed to produce calibrated event files using the XMM-Newton SAS v9.0.0 Intervals of very high background removed using a double subtraction method (fixed ct-rate threshold + 3clipping algorithm) and visually inspecting the light-curves. MOS1 & MOS2 background treated using spectral modeling instead of direct spectral subtraction, following the recipe of Leccardi & Molendi (2008). PN data used only in the imaging analysis (i.e. to subtract point sources) because of problems in background characterization and inconsistencies with MOS temperature and abundance measure

  11. MOS background modeling • Leccardi & Molendi (2008) analyzed a large compilation of “blank field” MOS1 and MOS2 observations, to characterize the following components of the background: • X-ray background from the Galaxy Halo (HALO) • Cosmic X-ray background (CXB) • Quiescent soft protons (QSP) • Cosmic ray induced continuum (NXB) • Fluorescence emission lines • The background parameters were estimated fitting the background model in a 10’-12’ ring and then rescaled appropriately for the cluster spectra.

  12. Spectral analysis strategy • We determined r500 iteratively applying the formula derived by Vikhlinin (2006) to the 0.15-0.6 r500 annulus: • Spectra in the following spatial bins were extracted and fitted with XSPEC v12.5.1 using Cash statistics: 0-0.15 r5000-0.6 r500 0.15-0.4 r5000.15-0.6 r500 >0.4 r500 • We used a 1-T thermal mekal model where kT, Z and normalizations were left free to vary, fixing Galactic absorption and redshift.

  13. X-ray global properties Baldi et al. 2011 (A&A submitted) The <T> distribution ranges from 1.5 to 11 keV, with a peak around 4 keV The abundance <Z> measured in the 0.15-0.6 r500 range is always < 0.5 Z

  14. Integrated abundance evolution Baldi et al. 2011 (A&A submitted) • No clear evolution with redshift is observed considering the emission from the whole cluster (0-0.6r500) and excising the core (0.15-0.6r500) • Fitting the data points with a power-law Z  (1+z)- we obtain: • 0-0.6 r500 :  = 0.80.5 • 0.15-0.6 r500 :  = 0.60.7 The most significant deviation from = 0 is observed in the 0-0.6 r500 sample, where  = 0.750.74 at a 90% c.l.

  15. Spatially resolved abundance evolution Baldi et al. 2011 (A&A submitted) • No evidence of correlation between redshift and metal abundance is observed also spatially resolving the cluster emission. • Fitting the z vs. Z distribution with a power-law we have: • 0-0.15r500 : = 0.20.7 • 0.15-0.4r500 : = 0.40.7 • >0.4 r500 : = 1.71.9 The lack of evolution is confirmed also by a Spearman’s rank  analysis which shows a high probability of no correlation (p>0.5)

  16. Temperature-abundance correlation Baldi et al. 2011 (A&A submitted) • A correlation between the temperature and the abundance measured in galaxy clusters has been previously reported (e.g. Baumgartner et al. 2005, Balestra et al. 2007) • Considering the integrated emission from the whole cluster, we fit a powerlaw Z  kT- obtaining: • 0-0.6 r500 :  = -0.10.1 • 0.15-0.6 r500 :  = -0.10.2 Although the abundance shows a higher spread in its values in lower temperature clusters (kT < 5 keV), no obvious trend between kT and Z is observed

  17. Comparison with previous works Considering the emission from the clusters as a whole we could detect only a mild evolution (<2) A comparison with the previous results obtained on the abundance evolution in the literature is possible (Balestra et al. 2007, Maughan et al. 2008, Anderson et al. 2009) can be performed by selecting the clusters at z>0.4 and fitting the z-Z distribution with a power-law

  18. Comparison with previous works All samples are not showing significant evolution (>2) except Maughan’s samples, which shows values of  significantly higher than all the others The high  values in Maughan’s are probably driven by the stringent upper limits on Z measured in a high-z cluster (CLJ1415.1+3612 at z=1.03 with Z<0.04 Z) Baldi et al. 2011 (A&A submitted) Removing the contribution of this cluster from Maughan et al. samples is lowering the values of  (=2.180.74 in the 0-1r500 sample; =-0.151.31 in the 0.15-1r500 sample) This is clearly a caveat about being careful in interpreting results based on small samples

  19. Spatially resolved weighted abundance mean • We computed an error weighted abundance mean for each of the spatially resolved radial regions in three redshift bins: • 0.4  z  0.5 • 0.5  z  0.7 • 0.7  z  1.4 Baldi et al. 2011 (A&A submitted) • The z-Z relation is consistent with no evolution at every radius • Although no significant evolution is present, the trend in the 0.15-0.4 r500 radial bin: • complements nicely the measures of Maughan et al. (2008) • broadly agrees with the predictions of Ettori (2005) model (the slopes are different at 1.5 level)

  20. Radial dependence of the abundance This is the first time that ICM abundance is parametrized as a function of both radius and redshift Direct comparison with models of metal diffusion (e.g. Ettori 2005) and simulations of chemical enrichment (e.g. Fabjan et al. 2010) in the ICM From the error weighted abundance measures, a radial dependence of the abundance on the radius is evident Baldi et al. 2011 (A&A submitted) • The dependence of Z on both r and z could be tested by fitting the relation: • The best fit values of the free parameters are: • Z0 = 0.36  0.03 • a = 0.32  0.07 • = 0.07  0.21 • A significant negative trend of Z with the radius (and no redshift evolution) is present

  21. More interesting science is on the way… • We are using the large dataset built from the XMM-Newton archive galaxy cluster sample to achieve more interesting science results, e.g.: • Temperature profiles of high redshift clusters • Study of the evolution of elements other than Fe • And more is on the way… SLIDES

  22. Temperature profiles at high z We selected a sub-sample made of the 12 brightest clusters (MOS net counts > 3000) to extract a radial temperature profile Baldi et al. 2011a in prep.

  23. Temperature profiles at high z Solid line: Vikhlinin et al. (2006) relation renormalized to our data Dotted line: Best-fit to our data, leaving key parameters in the Vikhlinin et al. relation free to vary Dashed line: Best fit to our data at r > 0.15 r500 Baldi et al. 2011a in prep. Preliminary results are showing a different behavior of the temperature decrease at r > 0.15r500 with respect to the relation of Vikhlinin et al. (2006), derived in local clusters observed by Chandra

  24. Elemental abundances at high z We fitted simultaneously all the spectra divided in 4 different redshift bins to study the evolution with redshift of Mg, Si, S, Ni and Fe Mg, Si, S and Ni Fe Baldi et al. 2011b in prep. Preliminary analysis shows a clear evolution with z only in Fe abundance, although Si is showing hints of evolution at z > 0.7

  25. Abundance evolution studies & the next generation observatories The next generation of X-ray observatories (especially Athena) could improve dramatically our knowledge of abundance evolution in galaxy clusters at high redshift To give an idea of how these future missions could shed new light into the ICM enrichment in the early stages of structure formation in the Universe, we performed 50ksec Athena - XMS spectral simulation for all the galaxy clusters in our sample with XSPEC Each simulated cluster spectrum (with the same spatial bins as in XMM analysis) was fitted with an XSPEC mekal model

  26. Individual elemental abundances The high S/N XMS spectra would allow to investigate the evolution in abundance of the individual elements out to z≈1 (at least in a single spatial bin) O Mg Si S

  27. Abundance ratios and SN yields [Mg/Fe] [Si/Fe] [S/Fe] Theabundance ratios between elements and Fe would allow the comparison with the metal abundance yields expected from different SN types and therefore to constrain the history of ICM enrichment through SNIa and SNII.

  28. Summary We presented a sample of 39 galaxy clusters at 0.4<z<1.4 extracted from the XMM-Newton archive. We do not observe a statistically significant abundance evolution with z in the integrated emission from the whole cluster. The most significant deviation from no evolution is found in the 0-0.6r500 sample (90% c.l.) Dividing the emission in 3 radial bins, no significant evidence of abundance evolution (al-ways below 1σ) could be observed. We compared our results with previous works in the literature. Our results are fully consistent with Balestra et al. (2007), Maughan et al. (2008) and Anderson et al. (2009) samples at z > 0.4, as indicated by a power-law fit of the z-Z distributions (differences in γ and normalization always <2σ). We computed error-weighted means of the spatially resolved abundances in three redshift bins. The abundance weighted mean is consistent to be constant with redshift at every radius. The trend in the 0.15-0.4r500 radial bin complements nicely the measures of Maughan et al., and agrees with the predictions of Ettori (2005) model. We parametrized the dependence of the metal abundance on both the radius r and the redshift z with a function of two variables Z (r,z). The relation obtained show a significant negative trend of Z with the radius and, although no significant evolution with the redshift is detected, it represents the first time that the ICM abundance has been parametrized as a function of both r and zthat could be directly compared with the models of diffusion of metals and the simulations of chemical enrichment in the ICM.

More Related