Neistein & Weinmann (MNRAS, 2010) Weinmann, Neistein & Dekel (in prep, 2010) Neistein, Li, Weinmann & Boylan-Kolchin (in prep, 2010)
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1 Neistein & Weinann (MNRAS, 2010) Weinann, Neistein & Dekel (in prep, 2010) Neistein, Li, Weinann & Boylan-Kolchin (in prep, 2010)
2 ! 1. Define a Galaxy hot gas cold gas stars Others: BH, etals, ejected gas " # 2. Quiescent Physical processes accretion of new gas cooling: hotcold SF: cold stars feedback (SN & AGN): cold hot t 3. Merger trees erger trees of subhalos dynaical friction stripping/accretion by satellites erger-induced bursts
3 Most SAMs follow White & Frenk (1991) g - hot gas density t 1 t2 ( T, Z ) : r Sutherland & Dopita (1993) Log halo ass cooling efficiency: Uncertainties Gas density profile, 3D effects (filaents) Assuing collisional ionization equilibriu Metals: non-solar abundance ratios Different ipleentations of White & Frenk concept. Gnat & Sternberg (2007); Wiersa et al. (2009); Lu et al (2010) cold fchot cooling no cooling AGN feedback fast cooling ~dynaical tie Tie since big-bang De Lucia & Blaizot (2007) Log[Gyr -1 ]
4 !"# Schiinovich et al (2010) Kennicutt (1998) De Lucia & Blaizot (2007) Log SFR density Log gas density SAMs: Uncertainties: H 2 or HI (SAM use H 2 +HI) - Fu et al (2010) Density averaged over the whole galaxy or local Large scatter observed star SF efficiency : Log halo ass cold disk star cold Tie [Gyr] Log[Gyr -1 ]
5 $%&'( - Cold gas is heated back to the hot coponent a hot star V h Kauffann et al (1999) =2 Cole et al. (2000) =5.5 Croton et al (2006) =0 Khochfar & Ostriker (2008) =2 - Cold gas is ejected out of the halo b a eject star V h Croton et al (2006) =2 Open issues: High level of uncertainty Not enough observational constraints Other kinds of feedback: AGN, preheating, SN-Ia, stellar feedback
6 )$%%! Motivation include ost of the physical processes (erger-trees, cooling, SF, feedback, accretion, bursts) keep it as siple as possible (while not changing the results of SAMs) deal with uncertainties within the recipes fit the data! sesa seel The recipes depend only on halo ass and redshift (ergers and satellites are treated in a siilar way as in SAMs) cooling: SF: cool f ( M, z) c f ( M, z) star s h h hot cold
7 The foralis is siple and copact: recycling SF cold accretion feedback ejection One equation for the quiescent evolution: cooling hot accretion Benefits We don t to paraeterize recipes in advance Tuning the odel is straight forward The coplex structure or erger-trees is being used
8 * %+ De Lucia & Blaizot SAM SeSAM 1. We run De Lucia & Blaizot SAM and save all transition rates 2. We average transition rates per halo ass and redshift: f cooling - SF - c Log[Gyr -1 ] s Log[Gyr -1 ] f Log halo ass Tie [Gyr] Log halo ass Tie [Gyr] 3. We use the averaged recipes within our odel, using the sae erger-trees as De Lucia & Blaizot
9 % $ Stellar ass functions Specific SF rates Blue our odel Red De Lucia & Blaizot (2007) Gray observations (Li & White 2009) Very siilar scatter! The scatter in the properties of galaxies coes ainly fro different erger-histories!!
10 Motivation explore the degeneracy span different scenarios identify iportant observ. constraints fit the data!, Stellar ass functions I no SN feedback II no ejection feedback III cold accretion IV only bursts V shutdown by ergers observations
11 -( I no SN feedback II no ejection feedback III cold accretion IV only bursts V shutdown by ergers Residual SF in passive galaxies cold gas fraction
12 '$. / -!0 ( M ) h Stellar-ass as a function of the subhalo ass at the tie of infall Behroozi, Conroy & Wechsler (2010) Assuptions on satellites at z=0: 1. Using only subhalos which survive until z=0 2. No redshift dependence: 3. infalling subhalos are siilar to other centrals 4. No ass gained after infall ( M, z) h Different SeSAM odels
13 '$ "11# Lines: central galaxies at each redshift Sybols: satellite galaxies at z=0, labeled by their infall z, stellar ass at infall Sybols: stellar ass at z=0 Contours: constant stellar ass All these effects odify the correlation function
14 2 345 / 6& 7( Standard SeSAMs: Observations: dust Is the plateau in conflict with the theory? Why ost odels behave the sae (and different fro the observ.)?
15 2 345"11# Fitting the plateau significant changes in SF and feedback efficiencies too low stellar ass function Reproducing both only by changing ergers high efficiency of SF bursts short dynaical friction ties at high-z
16 New SeSAM ethodology: siple & fast (8 sec for the Milli-MS) easy to tune no a-priory paraeterization of recipes 5 very different odels $ Abundance atching ore coplicated behavior in SeSAM dependence on environental effects dynaical friction different SF/feedback recipes needed high efficiency of ergers burst shorter accretion ties,'% 1. Choose your paraeters 2. Run the odel (on our server!) 3. See coparison against observations 4. Download catalogs Thank you! Run it fro your pal:
17 -
18 SF halo spin distribution, depends weakly on halo ass Cooling nuerical behavior for sall ass halos
19 1!$ What are the iniu cooling rates possible? cooling is balanced by feedback, (iniu cooling)=(zero feedback) cooling will then control the total aount of ass within stars & cold gas ~unique solution for cooling rates Model ingredients: zero SN feedback no erger induced SF bursts total freedo in cooling and SF: Log f c ( M h, z) Log f s ( M h, z)
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