Elodie GIOVANNOLI Laboratoire d’Astrophysique de Marseille, FRANCE Advisor : Veronique BUAT...
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 spectrum
Results : 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
Nu
mb
er o
f g
alax
ies
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
Nu
mb
er o
f g
alax
ies
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 ~5
94% 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?