1. Jeju, 27-29 Feb 2012, The legacy of Akari: a panoramic view of the dusty universe

2. Outline Samples definition SED fitting on multi-λ data Dust attenuation recipes Green valley galaxies SFR calibrations

3. Sample selections AKARI FIS all sky survey FIS Bright Source Catalogue Xmatched with IRAS PSCz + SDSS/DR7 and GALEX/GR4-5 surveys 2MASS data also added Primary sample: 776 galaxies selected at 90 µm: (Takeuchi et al. 2010) 363 galaxies all detected 153 galaxies Xmatched at 140 µm with AKARI/IRC PSC (Buat et al. 2011) (Yuan et al. 2011) and poster 2-21 for details

4. SED fitting with CIGALE Reliability of SED fitting results checked on artificial galaxies: Buat et al. 2011

5. Parameter estimation

6. Dust attenuation Takeuchi et al. 2010, Buat et al. 2011

7. Meurer et al. 95, 99, Calzetti et al. 00 f (1200-2500Å), : a proxy for dust attenuation in local starburst galaxies observed by IUE and IRAS The slope of the UV continuum: a measure dust attenuation? Dale et al. 07 See also Boissier et al. 07 Munoz-Mateos et al. 09 SINGS

8. see also Howell et al 2010, Goldader et al. 2002, Buat et al. 2005, Seibert et al. 05 Munoz- Mateos et al. 09, Overzier et al. 10 etc… Buat et al. 2011 AKARI-SDSS-GALEX data + SED fitting Very dispersed relations A FUV (from L ir /L UV) mag o LIRGs __ Meurer et al 99 Seibert et al. 05 - - Salim et al 07 Takeuchi et al. 10 FUV-NUV a proxy for ß AKARI-SDSS-GALEX: a very large dispersion

9. FUV-NUV FUV-r colour A FUV = 2.39 (FUV-NUV)+0.89 (σ = 0.83) σ(FUV-NUV) = 0.2 mag σ(A FUV ) = 0.5 mag A FUV = 0.65 (FUV-r)+0.04 (σ = 0.76) σ(FUV-r) = 0.2 mag σ(A FUV ) = 0.1 mag UV-optical colours are only crude estimators of dust attenuation See also Johnson et al. 2007

10. Green valley: star formation and dust attenuation Takeuchi et al. 2010, Heinis et al. in prep Blue cloud star forming galaxies NUV-r < 3.5 Red cloud, quiescent galaxies NUV-r > 4.7 Green valley 3.5<NUV-r<4.7

11. Galaxies in the green valley: Distributions of D4000 and SSFR close to those of the blue cloud galaxies but with a tail towards quiescent galaxies. The galaxies in the green valley have larger attenuations than blue galaxies On going work

12. SFR calibrations Buat et al. 2011: Combining IR and UV data Yuan et al. 2011: Calibration of MIR fluxes

13. Adding UV and IR measurements to estimate the SFRs Buat et al. 11 SFR( M sun yr -1 ) = (1- ) SFR(IR)+SFR(UV obs ) SFR(IR) and SFR(UV) from recipes (e.g. Kennicutt 98) corresponds to the fraction of L(IR) due to the heating by old stars Hirashita et al. 03, Iglesias-Paramo et al. 04,06, Bell 03 = 0.3-0.4 (star forming galaxies) η= 0.17 +/- 0.10

14. logSFR 9 = 0.99 log(L 9 )-9.02 (σ=0.18 dex) logSFR 18 = 0.90 log(L 18 )-8.03 (σ=0.20 dex) MIR luminosities calibrated in SFRs Yuan et al. 2011

15. Comparison with calibrations from Spitzer AKARI Log(SFR 8 /SFR 9 ) = -0.14 +/- 0.18 (Wu et al) Log(SFR 8 /SFR 9 ) = -0.25 +/- 0.16 (Zhu et al) Fluxes at 8 and 24 µm from the best model (Dale and Helou 02 templates) Log(SFR 24 /SFR 18 ) = -0.01 +/- 0.12 (Wu et al) Log(SFR 24 /SFR 18 ) = -0.05 +/- 0.11 (Zhu et al) Log(SFR 24 /SFR 18 ) = -0.04 +/- 0.17 (Rieke et al)

16. Conclusions Reference samples based on a FIR selection and with large wavelength coverage. Reliable SFR and dust attenuation retrieved from SED fitting, calibrations investigated. Green valley galaxies easily identified: combination of dusty « blue cloud » galaxies and more quiescent objects Samples which can be used for comparison in high z studies: Elbaz et al., Wang et al. (similar samples) Symeonidis et al (in prep)