Elodie GIOVANNOLI Laboratoire d’Astrophysique de Marseille, FRANCE Advisor : Veronique BUAT

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15/12/ 2009. ESF conference , Obergurgl. Spectral energy distribution modeling from UV to 70µm for LIRGs at z=0.7 . Elodie GIOVANNOLI Laboratoire d’Astrophysique de Marseille, FRANCE Advisor : Veronique BUAT C ollaborators : Denis Burgarella , Stefan Noll. OUTLINE - PowerPoint PPT Presentation

Transcript of Elodie GIOVANNOLI Laboratoire d’Astrophysique de Marseille, FRANCE Advisor : Veronique BUAT

Elodie GIOVANNOLILaboratoire d’Astrophysique de Marseille, FRANCE

Advisor : Veronique BUATCollaborators : Denis Burgarella, Stefan Noll

Spectral energy distribution modeling from UV to 70µm for

LIRGs at z=0.7

15/12/2009ESF conference, Obergurgl

OUTLINE

Motivation: accurate estimation of physical parameters , SED-fitting

1. Introduction : LIRGs’ characteristics Description of the sample

2. SED fitting Code CIGALE http://www.oamp.fr/cigale/

3. Application to the LIRGs sample Mid-IR slope SFR/Mass

4. Future task

Population detected at 24 µm is dominated by LIRGs at 0.5≤z≤1.0

Plot : At z≈1, IR-Luminous galaxies appears to be responsible for 70% of the comoving IR energy density.

REF: Le Floc’h et al. 05 Caputi et al. 07 Magnelli et al. 09 Roghiero et al. 09

Le Floc’h et al. 05

Study of LIRGs to understand the formation and evolution of galaxies from z=1.

LIRGs' characteristics (Luminous Infrared Galaxies)

ULIRGs

LIRGs

Low luminosity galaxies

Comoving IR energy density

1011 < LIR , L< 1012

Description of the sampleSample of 181 LIRGs <z>=0.70 +/- 0.05 Detected at 24µm : f24µm ≥ 83 µJy

Sub-sample of 62 LIRGS (flux at 70 µm) Selection of the GTO SPITZER/MIPS CDFS (Chandra Deep Field South) (Le Floc’h et al. 2005), cross-correlated with MUSYC (Multiwavelength survey by Yale-Chile) and FIDEL (Far-Infrared Deep Extragalactic Legacy Survey)

UV (2310 A) GALEX images

U U38 B V R I z J H K MUSYC

3.6 4.5 5.8 8.0 µm CDFS, IRAC

24 and 70 µm CDFS + FIDEL, MIPS

17 filters

CIGALE : Code Investigating GALaxy Emission *

SED-fitting

CIGALE code developped at LAM-Marseille (Burgarella et al. 05, Noll et al. 09)Task: To derive physical galaxy parameters from broad-band UV-to-IR SEDs at given redshifts.

INPUT : Photometric broad-bands Star Formation History Fraction of AGN Dust Attenuation IR library AGN templates Fit of the entire spectrumResults : best model (χ2) + bayesian analysis (close to Kauffmann et al. 2003).*http://www.oamp.fr/cigale/*For now, only downloading the code is possible but a more sophisticated interface will be in place at the end of February 2010.

OUTPUT : input parameters + M, SFR, Ldust

SFR0

SFR

SFR=SFR0.e-(t/tau)

age

Populations synthesis codes

Maraston et al. (2005) (including TP-AGB stars)

PEGASE

Stellar populations:

Combination of a young + an old stellar population with exponentially decreasing SFR at different rates.

Dust attenuation: Calzetti et al. (2000)

IR models:

Dale & Helou (2002) models , parametrised by the factor α, related to the ratio f60/f100

α : power law slope of the dust mass distribution over heating intensity

Wavelength, µm

t1 t2

AGN contribution : AGN templates, Siebenmorgen&Krugel 2004

Application to the LIRGs sample : preliminary results of the bayesian analysis

Num

ber o

f gal

axie

s

Log Mstar, M Log Ldust, L Log SFR, Myr-1

Age of ySP, Gyr Fraction of ySP Fraction of AGN

Application to the LIRGs sample : preliminary results of the bayesian analysis

Num

ber o

f gal

axie

s

Log Mstar, M Log Ldust, L Log SFR, Myr-1

Age of ySP, Gyr Fraction of ySP Fraction of AGN

Fraction of IR Luminosity reprocessed by dust heated by an AGN.

AGN detection

Code CIGALE

49 objects identified

Stern et al. 2005

26 objects identified

Brand et al. 2006

9 objects identified

Total sample

After AGN identification:Total sample: 121 objects70 µm sample : 42 objects

Before AGN identification:Total sample: 181 objects70 µm sample : 62 objects

Sample with a detection at 70μm, no AGNs

The mid-IR slope brings informations on the fit of IR libraries.

Dust temperature ?Association of a dust temperature following these models will give rather cold galaxies

L24/L70 higher than predicted by models.

In agreement with Zheng et al. 2007,stacking analysis

The mid-IR slope

Sample with a detection at 70μm, no AGNs

The mid-IR slope brings informations on the fit of IR libraries.

Dust temperature ?Association of a dust temperature following these models will give rather cold galaxies

The mid-IR slope

The AGN contamination is too weak to induce such an increase of νLν24μm/νLν70μm observed.

The local SED templates are not well-suited to fit fluxes from distant galaxies.See Symeonidis et al. 2009

Magnelli et al. 2009

SFR density

Strong contribution to the star formation activity beyond z≈0.7

We expect actively star forming galaxies

LIRGs

Normal galaxies

ULIRGs

Characteristics :

Millenium simulations underestimate the SFR

Mstar> 1011 M: in good agreement with semi analyticl models from Buat et al.08 and Noeske et al. 07

Mstar < 1011 M : in good agreement with Santini et al. 09 red area: unexepected high SFR , SFR/SFRmodels ~594% of the sample is actively star-bursting :M > 2.0.1010

The relation SFR/Mass

Summary & perspectives

Our results show that CIGALE is able to fit SED from UV to FIR

Get ready forthcoming Herschel data

Improvment of the code to provide a valuable and friendly tool to interprete the future data of Herschel : HeRMES consortium

(The Herschel Multi-tiered Extragalactic Survey)

- Add IR libraries : Chary&Elbaz, Siebenmorgen&Krugel - Add AGN templates : accurate measure of the fraction of AGN

Fit of the IR counterpart thank to several black bodies Accurate estimation of the dust temperature Evidence for a hot/cold population at high redshift?