1. Properties of high redshift galaxies from 24 μm images Paola Santini Università di Roma “La Sapienza” Osservatorio Astronomico di Roma Scuola nazionale di Astrofisica - IX ciclo - Maracalagonis 20 – 26 maggio 2007 Collaborators: Adriano Fontana, Cristian De Santis, Stefano Gallozzi, Emanuele Giallongo, Andrea Grazian, Nicola Menci, Laura Pentericci, Sara Salimbeni

2. The GOODS-MUSIC sample 14847 objects both z (9862) and Ks (2931) selected Photometry from 0.3 to 8.0 µm (14 bands): U35 U38 (MPG/ESO-WFI) U VIMOS (VLT) B V i z (HST-ACS) J H Ks (VLT-ISAAC) 3.6 4.5 5.8 8.0 µm (Spitzer-IRAC) + 1068 spectra from K20, GOODSV1, CXO, VVDS, COMBO17 ~ 135 arcmin 2 CDF-South Great Observatories Origins Deep Survey-MUltiwevelength Southern Infra-red Catalog (Grazian et al. 2006, A & A, 419, 915G) 928 galaxies (668 secure identifications) (428 galaxies with finer classification) 72 stars, 68 AGNs PSF-matching method to detect objects exploiting higher resolution images and the GOODS-MUSIC catalog MIPS 24 µm data (Spitzer) Pixel size=1.2’’ PSF~5.16’’

3. Fitting the SEDs Polletta (2006) Early type Normal star forming Starbursts AGNs

4. The colour cut ((U-V) Johnson ~0.6) is based on the bimodality observed in the (U-V) vs B relation (Salimbeni et al., in preparation) 24 μm data can select a sample of early type galaxies Early type Normal star forming Starbursts AGNs

5. Stellar mass – spectral type Early type Normal star forming Starbursts AGNs The stellar masses are consistent with the fitted spectral type

6. t/τ – spectral type Early type Normal star forming Starbursts AGNs

7. t/τ - mag 24μm Early type Normal star forming Starbursts AGNs

8. Conclusions and future work We have found two independent ways to select a sample of early type galaxies at high z  combining L IR and (U-V) RF  from t/τ Stellar masses are consistent with the spectral classification. The aim of this work is to study the evolutionary trend between different populations  number density Finally we will compare our results with theoretical models predictions

9. Sub-areas with different S/N have different magnitude limits All magnitudes are AB;   =0.7  M =0.3 H 0 =70 km s -1 Mpc -1 (Grazian et al. 2006 A&A…419..915G) The GOODS-MUSIC sample Total 14847 objects both z (9862) and Ks (2931) selected: at least 72 known stars, 68 AGNs, 928 galaxies (668 secure identifications) (428 galaxies with finer classification)

10. The GOODS-MUSIC sample Photometric redshifts SFR Dust Z M(stars) U 360nm B 420nm V 520nm R 650nm I 800nm J 1250nm K 2200nm Multicolour surveys allow us to estimate photometric redshifts and physical properties of each object of the catalog Photometric z 668 secure spectroscopic redshifts

11. AGN contamination AGNs may contribute to IR emission from accretion processes onto SMBH a)Remove objects with optical spectroscopic AGN identification; b)Cross-correlation between 24 µm catalog and X-hard band (not obscured by dust) of GOODS field and remove bright X-hard emitters; c)Diagnostic IR diagrams ( F 8 µm / F 3.6 µm vs F 24 µm / F 8 µm ); d)IR spectroscopy (high ionization lines).

12. PAH features Complex organic molecules in the ISM which are excited from stars UV radiation Polycyclic Aromatic Hydrocarbon

13. X-rays observations Star Formation Rate estimators Radio emission SFR (M o yr -1 ) = 1.4 · 10 -28 L 1500-2800Å (erg s -1 Hz -1 ) SFR (M o yr -1 ) = 7.9 · 10 -42 L Hα (erg s -1 ), H α (6563Å) SFR (M o yr -1 ) = 1.4 · 10 -41 L OII (erg s -1 ), O II (3727Å) SFR (M o yr -1 ) = 0.25 · 10 -28 L 1.4 GHz (erg s -1 Hz -1 ) Total IR luminosity SFR (M o yr -1 ) = 1.71 · 10 -10 L 8-1000 µm (L o ) SFR (M o yr -1 ) = 2.2 · 10 -40 L 0.5-2 keV (erg s -1 Hz -1 ) SFR (M o yr -1 ) = 2.0 · 10 -10 L 2-10 keV (erg s -1 Hz -1 ) Optical emission lines UV luminosity PAH features Stellar emission Absorbed UV light Dust emission 24 μm filter M82 (ISO) REDSHIFT EFFECT

14. ConvPhot Measures colors between two images having different resolutions a)Each object is extracted from the “detection image”, making use of the parameters and of the isophotal area (expanded) defined by SExtractor; b)Each object is filtered with a convolution kernel to match the “measure” PSF and normalized to unit total flux (“model profiles”); c)The intensity of each “model” object is then scaled in order to match the intensity of the object in the “measure” image. The scaling factors are found via a χ 2 minimisation over all image pixels (all objects are fitted simultaneously). Images must be perfectly aligned and must have the same pixel scale Detection imageMeasure image De Santis et al. 2007, 2007NewA...12..271D 24 µm image (MIPS) z-band image (ACS) Pixel size = 0.03’’ PSF ~ 0.12’’ Pixel size = 1.2’’ PSF ~ 5.16’’

15. ConvPhot the method relies on the accurate spatial and morphological information contained in the detection image morphology and positions do not change significantly between the two bandwidths most of the objects detected in the measure image are contained in the input catalog objects blended in the measure image are well separated in the detection image ADVANTAGE ASSUMPTIONS SIMULATIONS I and B images smoothed with a 0.5 arcsec kernel De Santis et al. 2007, 2007NewA...12..271D

16. 24 μm catalog

17. Redshift distribution Peaks in the distribution are features of GOODS- South field (cosmic variance) mag 24μm < 20

18. Salimbeni et al. 2006 in preparation The red line is the locus of minima between the two distributions used for the class separation. The distribution appears to be bimodal at least up to z=2. Color bimodality