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SPHEROIDAL PANCHROMATIC INVESTIGATION IN DIFFERENT ENVIRONMENTAL REGIONS (SPIDER)

SPHEROIDAL PANCHROMATIC INVESTIGATION IN DIFFERENT ENVIRONMENTAL REGIONS (SPIDER). F. La Barbera (1) ; R.R. de Carvalho (2) ; I.G. de La Rosa (3) ; P.A. Lopes (4) ; I. Ferreras (5) ; R.R. Gal (6) ; H.V. Capelato (2)

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SPHEROIDAL PANCHROMATIC INVESTIGATION IN DIFFERENT ENVIRONMENTAL REGIONS (SPIDER)

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  1. SPHEROIDAL PANCHROMATIC INVESTIGATION IN DIFFERENT ENVIRONMENTAL REGIONS (SPIDER) F. La Barbera(1); R.R. de Carvalho(2); I.G. de La Rosa(3); P.A. Lopes(4); I. Ferreras(5);R.R. Gal(6); H.V. Capelato(2) (1) INAF-OAC; (2) INPE-DAS, Sao José dos Campos, Brazil; (3) IAC, Tenerife, Spain; (4) OV/UFRJ, Rio de Janeiro, Brazil; (5) University College London; (6) Institute for Astronomy, Hawaii, USA

  2. Spheroidal systems contribute with a significant fraction of the total stellar mass in the local universe number density stellar mass function fraction of dry mergers size evolution stellar population content (age, metallicity, .....) Constraining their observed properties may help understand better the hierarchical scenario of galaxy formation and evolution Environment might play a crucial role Early-type galaxies (ETGs)

  3. Studying the galaxy’s progenitors Paleontology of galactic properties Reference point Low redshift High redshift Smaller samples Less data Large samples Better data Small differences Large(r) differences Early-type galaxies (ETGs) Constraining the formation/evolution (of ETGs)

  4. SDSS-DR7 (u=22.0,g=22.2, r=22.2, i=21.3, z=20.5) UKIDSS-Large Area Survey (LAS; Y=20.5, J=20, H=18.8, K=18.4) The SDSS+UKIDSS dataset THE SPIDER

  5. The SDSS+UKIDSS dataset SDSS+UKIDSS photometric system (overall throughput curves)

  6. true value true value griz+YJHK: advantages NIR data describe the old, quiescent stellar population in galaxies, hence following more closely the mass distribution NIR bands are much less sensitive to metallicity (through line-blanketing), and less sensitive to age than optical data Using grizYJHK bands, we minimize the age-metallicity degeneracy

  7. GOALS Establishing the waveband dependence of the scaling relations of ETGs (Faber-Jackson, Kormendy relations, Fundamental Plane) Measuring the variation of stellar population properties INSIDE galaxies and along the mass sequence of ETGs …….. as a function of the environment - characterized by either local density (potential) or global properties (halo mass) Systematic comparison of different approaches/techniques to measure stellar population properties (e.g. diagnostic diagrams of spectral indices, spectral fitting, PCA spectral analysis, SED fitting of the grizYJHK photometry)

  8. Sample selection and galaxy parameters

  9. The ETG’s sample We select a volume-limited sample of early-type galaxies from SDSS-DR6 as in Miller et al. (2003, ApJ 586), and Sorrentino et al. (2006, A&A 460) Mr<-20 (~ separation between ordinary and bright spheroids; Capaccioli et al. 1992, MNRAS 259) z≤0.095; where Mr matches the SDSS spectroscopic completeness limit (r*~17.8) spectroscopy available z≥0.05; minimizing the aperture bias (Gomez et al. 2003, ApJ 584) early-type galaxies eclass<0, FracDevr>0.8 (as in Bernardi et al. 2003, AL 125, 1849) Velocity dispersion available, with 70≤σ0≤420 km s-1 and zWarn=0

  10. The ETG’s sample The optical sample of 39,993 ETGs is matched to UKIDSS-LAS DR4, resulting into an sample of 5,080optical+NIRETGs

  11. SDSS r band Re, <μ>e, Sersic index n, b/a, disky/boxy parameter (a4) Galaxy parameters - 2DPHOT

  12. Galaxy parameters - 2DPHOT r i z Y J H K g low 2 (<1.5) high 2 (<1.5) Examples of 2D fitting from g through K

  13. Regions possibly contaminated by nebular emission are masked out in the fit Residual spectrum revealing the Hβ nebular emission. Galaxy parameters - spectra The SDSS spectra are re-analyzed with the software STARLIGHT (Cid Fernandes et sl. 2005, MNRAS 358) STARLIGHT provides the linear combination of SSP models, that broadened with a given σ0, best matches the observed spectrum The SSP models are those of the new high resolution (2.3Å FWHM) α-enhanced MILES library. Example of STARLIGHT spectral fitting

  14. The environment

  15. The environment We use the largest group/Cluster catalogue generated from SDSS at low redshift (z<0.1; 5162 groups at z>0.05) using a 3D FoF algorithm as in Berlind et al. 2006, ApJSS 167 The sample of ETGs is also matched to the catalogue of Compact Groups (CGs) from McConnachie et al. 2009, MNRAS 395. 400 Compact Groups have at least one ETG member. 25 Fossil Groups from the largest homogenous sample available at low redshift (La Barbera et al. 2009, AJ 137)

  16. the quantities σcl, R200, M200 are measured using the virial analysis as in Girardi et al. 1998, ApJ 505; Biviano et al. 2006, A&A 456 ; Popesso et al. 2007, A&A 464. we flag those groups with substructures detected (at the 5% level) by the (3D) Δ test (Dressler & Shectman 1988, AJ 95) we re-estimate the central redshift and velocity limits by the gap-technique (Katgert et al. 1996, A&A 310; Adami et al. 1998, A&A 331; Olsen et al. 2005, A&A 435); member galaxies are identified by the shifting gapper technique (Fadda et al. 1996, ApJ 473); Group members (points); interlopers (circles) Cluster properties For each group of the FoF catalogue, we re-select the group members (from SDSS-DR7), and re-estimate velocity dispersion (σcl), physical radius (R200), and mass (M200) as in Lopes et al. 2009, MNRAS 392. For each group,

  17. Distribution of ETGs with respect to local galaxy density. The sample covers three orders of magnitude in ΣN. Cluster properties For a given group, local galaxy density is estimated by using only the (projected) distribution of its member galaxies. We define the local density, ΣN, as N/(πdN2), where N is the square root of the number of group members. This ensures that dN scales with cluster mass.

  18. Cluster properties Distribution of ETGs with respect to the mass of the parent cluster where they reside. The sample covers almost two orders of magnitude in M200.

  19. HIGH DENSITY-HIGH MASS Example of a rich cluster in the updated FoF catalogue. Velocity dispersion is 1010 km s-1, while cluster mass is 2.7×1015 Msun. Red squares mark the objects with spectra available from SDSS-DR7 in the cluster field (not necessarily cluster members).

  20. INTERMEDIATE MASS Example of a group in the updated FoF catalogue. Velocity dispersion is 520 km s-1, while cluster mass is 5×1014 Msun. Red squares mark the objects with spectra available from SDSS-DR7 in the cluster field.

  21. SDSS SDSS SDSS UKIDSS-LAS UKIDSS-LAS UKIDSS-LAS HIGH DENSITY-LOW MASS Examples of (the 400) Compact groups (CGs) from the catalogue of McConnachie et al. 2009, MNRAS 395. The CGs are defined according to the original Hickson criteria. 70% of these groups have a counterpart in the FoF catalogue.

  22. X-ray emission map from the RASS for the same FG. The LXis typical for an entire galaxy group/cluster. Example of Fossil Group (FG) from La Barbera et al. 2009, AJ 137. The optical light is dominated by a bright elliptical galaxy in the center, with a large magnitude gap (≥2mag) between first and second rank galaxies. LOW DENSITY-HIGH MASS

  23. Some results for the entire sample

  24. The trend implies both a negative metallicity gradient (higher metallicity towards the center), AND a small but significantly positive age gradient (younger stars towards the center) Internal color gradients Mean internal color gradient, g-X, between g band and one of the other wavebands (from r through K). Evolving back in time the age gradient, we find that this might explain (some of) the compactness of ETGs at high z. From La Barbera & de Carvalho 2009, ApJL 699, 76

  25. g i r z MAG.LIM Y H K J Kormendy relations We find that the slope, β, of the KR depends significantly on the waveband, with larger slope values at longer wavelengths. Is this variation important to analyze the evolution in size of ETGs at high z?

  26. The Fundamental Plane (FP) from g through K

  27. The FP and its waveband dependence optical wavebands log Re = a log σ0 + b <µ>e + c a~1.2 b~0.3 expected values virial theorem+homology+M/L=const. a=2 b=0.4 WHY THE WAVEBAND DEPENDENCE ? Constraining the origin of the TILT: a change of stellar population vs. galaxy mass is expected to be wavelength dependent, while other effects (homology breaking, dark-matter content variations, ….) are not Studying the FP at high redshifts, where observations are done in different wavebands

  28. La Barbera et al. 08: a=1.42±0.05 (r band); a=1.53±0.04 (K band) 1430 gals The FP and its waveband dependence a~1.45-52 a~1.05-52 SDSS FP OPTICAL FPs a b a b a~1.29-53 NIR FPs a b total 475 gals

  29. Edge-on projection of the FP in the grizYJHK wavebands. The best-fits (orthogonal fit) are shown by the dashed lines. The FP from g through K

  30. The FP from g through K Slopes of the FP from g through K for the entire sample (all environments). Ellipses denote 1σ confidence contours. For the orthogonal fit, we find that the coefficient “b” is independent of the waveband, consistent with previous studies. The “a” changes by only 15% from g through K.. No variation is found for the log σ0 fit (MIST algorithm, La Barbera+2000).

  31. The FP from g through K We model the tilt as a variation of age, (log t), and metallicity, (log Z), between more and less massive ETGs per decade in mass, and a variation of M/L with M which is NOT due to stellar populations (but, for instance, to either a change of dark matter content with mass or to non-homology). We indicate the fraction of the tilt, in the NIR, which is not due to (log t), and (log Z),as f. We fit this model to the grizYJHK values of the FP slopes (as in La Barbera+08). The NIR tilt of the FP is NOT due to stellar populations (f=0), with more massive galaxies being more metal rich and having the SAME age as less massive systems.

  32. The FP from g through K in different environments

  33. The FP and the environment Zepf & Whitmore 1993 (ApJ 418) found that the FP of ETGs in CGs differs from that of field galaxies, with ETGs in CGs having lower σo. Jorgensen et al. 1996 found that the FP coefficients are consistent for samples of galaxies residing in different nearby clusters (although with small sample sizes) de La Rosa et al. 2001 (AJ 122) found no difference between the FP of ETGs in CGs and those in other environments. Bernardi et al. 2006 (AJ 131, 1288) found that the FP relation is very similar between ETGs in high and low density regions, but with a small significant offset in the zero-point. This offset is consistent with a pure age difference of 1Gyr. D’Onofrio et al.2008 found that the FP coefficients are strongly correlated with the environment (cluster-centric distance and local density)

  34. Is the GLOBAL environment (halo mass)producing such discrepancy ? The r-band FP –LOCAL DENSITY We bin the sample of ETGs in groups with respect to local density (Nbin=50; Ngal=362). We find that the slope “a” is constant; while “b” increases with ΣN. However, we have not accounted for the fact that ETGs in different bins might have different distributions in the space of FP parameters After correcting for that, we find that the variation of “b” tends to become less significant (from 4 to 2σ). These results seem to be in disagreement with those of D’Onofrio et al. 2008, but…... Variation of the FP slopes as a function of local density.

  35. Zepf & Whitmore ‘93 Coefficient “c” and scatter of the FP. The variation is consistent with a pure age difference of 1Gyr. Edge-on projection of the FP for ETGs in the entire sample (black) and the CG catalogues. The FP for Compact Groups The slopes for the three samples are very similar.

  36. First results of the XMM to confirm the nature of FGs from La Barbera et al. 2009 (P.I. M. Paolillo) The FP for Fossil Groups Although the sample is small, we can tentatively measure the scatter and offset of the FP for FGs. The scatter is significantly smaller (at 4σ) than that of the entire sample, as expected for a population of isolated, passive galaxies. CONTAMINATION ?

  37. “a” vs. the effective filter wavelength for the field and high density samples. The difference is significant at ~3σ. The grizYJHK FP – LOCAL DENSITY Variation of the FP slopes from g through K in bins of local density. “a” smoothly increases with the waveband, while “b” is constant. The amount of variation in “a” seems to decrease from high to low density.

  38. BC03, SSP, Z=Zsun, t=10Gyr r-band Field Coefficient “c”, in the r-band, as a function of local density. The variation is consistent with a pure age difference of 1Gyr, consistent with Bernardi et al. 2006 (AJ 131). . Variation of the FP offset, “c”, from g through K, as a function of local density. “c” smoothly decreases towards higher ΣN for ALL wavebands. The grizYJHK FP – LOCAL DENSITY What is the role of metallicity?

  39. The variation of the FP relation from g through K implies significant differences in the mass sequence of (bright) ETGs between low and high density environments. Can we reconcile these results into a consistent picture for the mass assembling of ETGs in the different environments ? Conclusions

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