Infrared Emission from High-Redshift Galaxies in Cosmological SPH Simulations
aa r X i v : . [ a s t r o - ph . C O ] J u l **FULL TITLE**ASP Conference Series, Vol. **VOLUME**, c (cid:13) **YEAR OF PUBLICATION****NAMES OF EDITORS** Infrared Emission from High-Redshift Galaxies inCosmological SPH Simulations
Kentaro Nagamine, Tae Song Lee, and Jun-Hwan Choi
Department of Physics and Astronomy, University of Nevada Las Vegas,4505 S. Maryland Pkwy, Box 454002, Las Vegas, NV 89154-4002,U.S.A.
Abstract.
We compute the infrared (IR) emission from high-redshift galaxiesin cosmological smoothed particle hydrodynamics (SPH) simulations by couplingthe output of the simulation with the population synthesis code ‘GRASIL’ bySilva et al. Based on the stellar mass, metallicity and formation time of eachstar particle, we estimate the full spectral energy distribution (SED) of eachstar particle from ultraviolet (UV) to IR, and compute the luminosity functionof simulated galaxies in the
Spitzer broadband filters for direct comparison withthe available
Spitzer observations.
A significant fraction of the energy density in the Universe comes from theIR emission reprocessed by dust. Therefore we need to take into account thisconversion process from stellar UV photons to dust thermal emission in IR inorder to estimate the total cosmic SFR density in the Universe properly. Theobservations by the
Spitzer Space Telescope give us excellent opportunities totest our models of galaxy formation and evolution.Theorists have utilized both semianalytic models and cosmological hydro-dynamic simulations of galaxy formation to understand the history of cosmicstar formation (e.g., Kauffmann & Haehnelt 2000; Nagamine et al. 2000, 2001).However, so far the modeling of dust extinction and the energy conversionfrom UV to IR have not been considered in detail in these modeling (but seeLacey et al. 2007, 2010). In this article, we report the preliminary results of ourattempt to compute the IR emission from simulated galaxies in cosmologicalhydrodynamic simulations.
Cosmological hydrodynamic simulations allow us to model galaxy formationstarting from high- z to the present time without any assumptions on the dy-namics of collapsing gas or merging dark matter halos. We use the updatedversion of the GADGET-3
SPH code (originally described in Springel 2005).Our code includes radiative cooling by H, He, and metals (Choi & Nagamine2009b), heating by a uniform UV background radiation, star formation (SF,Choi & Nagamine 2009a), supernova feedback, a phenomenological model forgalactic winds (Choi & Nagamine 2010), and a sub-resolution model of multi-1
Nagamine, Lee, & Choi
Figure 1. SEDs of different emitting physical components within theGRASIL model: stars (top left), molecular clouds (MC; top right), cirrus(bottom left), and total (bottom right). The time evolution of a single stellarpopulation is shown from t = 1 Gyr to 12 Gyr from top to bottom in eachpanel. Dust absorbs the UV photons, and re-emit the energy in the IR as themolecular cloud and cirrus emission. phase ISM (Springel & Hernquist 2003). Once the gas density exceeds the SFthreshold density, a star particle is allowed to be born from a gas particle ateach time-step in order to statistically reproduce the computed SFR on average.We use a series of simulation runs with different box sizes (comoving 10, 34, and100 h − Mpc) and resolution to cover a wide range of galaxy masses.The GRASIL code (Silva et al. 1998) computes the time-dependent SEDsof simulated galaxies in the wavelengths of 100˚
A < λ <
The left panel of Figure 2 shows an example SED of a simulated galaxy at z = 3with a stellar mass M ⋆ ∼ M ⊙ . One can see that some UV photons areabsorbed by dust and re-emitted as the dust thermal emission with a peak near100 µ m. nfrared Emission from High- z Galaxies
100 1000 10000 1e+05 1e+06 1e+07 1e+08log λ [ Å ] L og L λ [ e r g / s / Å ] l og [ d N / d ( m a g )] ( M p c ^ - ) Figure 2.
Left:
Total SED from UV to IR of a simulated galaxy at z = 3,computed by coupling the GADGET-3 output and the GRASIL code. Right:
AB magnitude luminosity functions (LFs) in the
Spitzer broadband filters of160, 70, 24, 8, 5.8, 4.5, 3.6 µ m, from right to left. The latter four LFs arealmost overlapping each other.Figure 3. Stellar mass vs. AB magnitude ( left ) and galaxy metallicity vs.AB magnitude ( right ) for simulated galaxies at z = 3. Once we obtain the full SED of simulated galaxies, we first compute theAB magnitudes using the
Spitzer broadband filters, and examine the luminosityfunctions as shown in the right panel of Figure 2. We find that the simulatedgalaxies are brighter in the longer wavelength filters, although we still need toidentify the exact cause of this trend.Figure 3 shows the relation between the AB magnitude, stellar mass, andmetallicity of simulated galaxies at z = 3. As expected, more massive galaxieshave brighter AB magnitudes. We also see that in general, the higher massgalaxies have higher metallicities. However, the scatter in metallicity for theluminous galaxies is much larger compared to when it is plotted against galaxystellar mass, presumably owing to dust extinction and re-emission processes.Figure 4 compares the monochromatic rest-frame luminosity functions at 8and 24 µ m of simulated galaxies at z = 2 against observed data. The agreementbetween the two is quite good, except for the last data point at the lowestluminosity, where the observation might be suffering from the flux limit. Summary.
We presented the preliminary results of our initial attempt tocalculate the IR emission from high- z galaxies in our cosmological hydrodynamicsimulations. The resulting rest-frame luminosity functions at 8 µ m and 24 µ m Nagamine, Lee, & Choi
Figure 4. Monochromatic rest-frame LFs at 8 and 24 µ m for z = 2simulated galaxies, compared against observational data by Caputi et al.(2007) and Rodighiero et al. (2009). The downturn of simulated LFs at low-luminosity end is due to the resolution limit of this simulation with a comovingbox size of 10 h − Mpc. agree very well with the observations, which is very encouraging. Through moredetailed analyses on the relationship between star formation histories, metallici-ties, and IR luminosities, we hope to gain more insight on the physical propertiesof IR galaxies observed by the
Spitzer . Acknowledgments.
We thank Laura Silva for providing us with the GRASILcode and its output. This work is supported by the NASA JPL Spitzer SpaceTelescope grant RSA No. 1347463. It is also supported in part by the NationalAeronautics and Space Administration under Grant/Cooperative Agreement No.NNX08AE57A issued by the Nevada NASA EPSCoR program, the President’sInfrastructure Award at UNLV, and by the NSF through TeraGrid resourcesprovided by the Texas Advanced Computing Center. Some simulations werealso performed at the UNLV Cosmology Cluster.