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IntroductionMethod
SimulationsThe End
The birth of the first tinyobjects
Umberto Maio (OATS)Marie Curie Fellow
.
....................................................in collaboration with: M. Petkova, K. Dolag, B. Ciardi,
L. Tornatore, S. Khochfar, J. Johnson, F. Iannuzzi,
M. A. Campisi, R. Salvaterra, N. Yoshida, P. Creasey,
L. Koopmans, V. Müller, V. Biffi, F. Pace, P. Dayal
....................................................
Outline
1 IntroductionMotivationsGeneral overview
2 MethodMolecules and metalsChemistry and cooling
3 SimulationsPopIII and II, SFR, ZLF, GRBs, DLAs, Non-G
4 The End
IntroductionMethod
SimulationsThe End
MotivationsGeneral overview
Motivations
Goal: Primordial structure formation and transition fromthe first metal-free ’PopIII’ star formation regime(high-mass or low-mass stars?) to the common,metal-enriched ’PopII-I’ one (low-mass ’solar’ stars):→ What is the formation epoch of first objects?→ What is the role of molecules and metals in the early ISM?→ How relevant is PopIII for star formation and metal spreading?→ What are the effects of different IMFs on SFR?→ What are the implications for early observables (LF, GRB)?→ What are the effects of the underlying matter distribution?→ What are the effects on cosmic re-ionization?...Requirements: Study the chemical properties of cosmic
medium during cosmological evolution.Techniques: N-body/Sph simulations (with Gadget).
IntroductionMethod
SimulationsThe End
MotivationsGeneral overview
Overview of structure formationThe Universe is supposed
to expand at a rate H0 ≃ 68 km/s/Mpc;
to have flat geometry (zero spatialcurvature);
to consist of dark matter, baryonicmatter and cosmologicalconstant/dark energy.
Cosmological parameters (Planck, 2013):Ω0,DM = 0.26, Ω0,b = 0.04, Ω0,Λ = 0.7⇒ Ω0,tot = 1;σ8 = 0.83, n = 0.96
Standard: H0 = 70 km/s/Mpc, Ω0,Λ = 0.7, Ω0,DM = 0.26,Ω0,b = 0.04, σ8 = 0.9, n = 1.
IntroductionMethod
SimulationsThe End
MotivationsGeneral overview
Theoretical scenario:
Cosmic structures originate from the growth of matterperturbations at early times (inflation), in an expandingUniverse.Baryonic structures form from in-fall and cooling of gas intoDM potential well.Eventually, a cloud can form if the radiative losses aresufficient to make the gas condense and fragment:
tcool =32
nkTL(n, T )
≪ tff =
√
3π32Gρ
At early times, the cooling function is dominated bymolecules ! After pollution from formed (baryonic)structures (→ chemical feedback) metals dominate.
IntroductionMethod
SimulationsThe End
MotivationsGeneral overview
primordial environments...
Small dark-matter haloes
Barkana& Loeb, 2001
H-cooling haloes: Tvir ≥ 104 K H2-cooling haloes: Tvir < 104 K
IntroductionMethod
SimulationsThe End
Molecules and metalsChemistry and cooling
...hosting molecular and metal evolution in their ISM
For a complete picture −→ necessity to follow gravity andhydrodynamics coupled to molecular evolution and metalproduction during cosmic time (e.g. Galli& Palla, 1998; Abel et al., 1997)
molecules determine first structure formation
metals determine subsequent structure formation
stellar evolution determines timescales and yields
Following and implementing metal and molecule evolution innumerical codes (N-body/SPH Gadget) required(Yoshida et al., 2003; Tornatore et al., 2007; Maio et al., 2007, 2010; Biffi & Maio, 2013)
IntroductionMethod
SimulationsThe End
Molecules and metalsChemistry and cooling
H + e− → H+ + 2e−
H+ + e− → H + γH + γ → H+ + e−
H− + e− → H + 2e−
H− + γ → H + e−
He + e− → He+ + 2e−
He+ + e− → He + γHe+ + e− → He++ + 2e−
He++ + e− → He+ + γHe+ + γ → He++ + e−
He + γ → He+ + e−
H + e− → H− + γH− + H → H2 + e−
H + H+ → H2+ + γH2+ + H → H2 + H+
H2 + H → 3HH2 + H+ → H2+ + HH2 + e− → 2H + e−
H− + H → 2H + e−
H2 + γ → H+2 + e−
H+2 + γ → 2H+ + e−
H2 + γ → 2HH+2 + γ → H + H
+
H− + H+ → 2HH− + H+ → H2+ + e−
H2+ + e− → 2HH2+ + H− → H + H2D + γ → D+ + e−
D+ + e− → D + γD + H2 → HD + HD+ + H2 → HD + H+
HD + H → D + H2HD + H+ → D+ + H2H+ + D → H + D+
H + D+ → H+ + DHe + H+ → HeH+ + γHeH+ + H → He + H+2HeH+ + γ → He + H+
IntroductionMethod
SimulationsThe End
Molecules and metalsChemistry and cooling
Abundance determination
Given the molecular network, abundance determination for eachspecies, i , is carried out by accounting for creation and destruction ofni via:
dnidt
=∑
p
∑
q
kpq,inpnq −∑
l
klinlni ,
kpq,i = kpq,i (T )[cm3 s−1]: creation rate from species p and q
kli = kli (T )[cm3 s−1]: destruction rate from interactions with the species l
dt can be discretized as a fraction (e.g. ≃ 1/10) of the hydro-timestep
Similar O.D.E. can be written for all the species considered!(i.e., e−, H, H+, He, He+, He++, H2, H+2 , H
−, D, D+, HD, HeH+)
IntroductionMethod
SimulationsThe End
Molecules and metalsChemistry and cooling
Gas cooling function andthe role of metals −→
In primordial regimes, themain coolants are H, He andmolecules (H2 and HD).
In metal enriched ones,metal fine-structuretransitions from C, O, Fe, Si(dominant over molecules atlow temperatures).
Cooling leads the gas in-fall into DM potential wells.
(Maio et. al, 2007)
IntroductionMethod
SimulationsThe End
PopIII and II, SFR, ZLF, GRBs, DLAs, Non-G
Zcrit : transition from popIII to popII-I star formationWe study the effects connected to the existence of a criticalmetallicity Zcrit (e.g. Bromm & Loeb, 2003; Schneider et al., 2003) and the transitionfrom popIII SF (Z < Zcrit ) to popII-I SF (Z ≥ Zcrit ).
In order to address such issues, we perform several numericalsimulations of early structure formation adopting differentvalues for Zcrit and exploring different scenarios.
Simulation set-up(Maio et al., 2010, 2011b, Maio & Iannuzzi, 2011; Maio, 2011; Maio & Khochfar, 2012)
standard-ΛCDM cosmology (1,7,14,43,143Mpc a side);molecular and metal chemistry;assume Zcrit = (10−6, 10−5, 10−4, 10−3) Z⊙assume different popIII IMFs (→ top-heavy/Salpeter)assume different matter distributions (→ G vs non-G)
IntroductionMethod
SimulationsThe End
PopIII and II, SFR, ZLF, GRBs, DLAs, Non-G
Results (1/20): effects for different Zcrit
Zcrit :10−3 Z⊙ 10−6 Z⊙
z=11
z=13
box: 1Mpc3 ; popIII IMF: top-heavy with slope=-1.35, range=[100M⊙ ,500M⊙ ]
Gas resolution: 116 M⊙/h (Maio et al., 2010)
IntroductionMethod
SimulationsThe End
PopIII and II, SFR, ZLF, GRBs, DLAs, Non-G
Results (2/20): polluting the surrounding medium
Phase diagrams with color contours for enriched gas(Zcrit = 10
−4 Z⊙ , box side = 1 Mpc)
z=16 z=14 z=11
Metals produced by stellar evolution pollute the surrounding,pristine gas with an “inside-out” mode. (Maio et al, 2011b)
IntroductionMethod
SimulationsThe End
PopIII and II, SFR, ZLF, GRBs, DLAs, Non-G
Results (3/20): effects on the surrounding
Radial fractions of PopII and PopIII gas in the most massive halo onscales ∼ 10 − 1000 pc (physical) (Maio et al., 2011b)
IntroductionMethod
SimulationsThe End
PopIII and II, SFR, ZLF, GRBs, DLAs, Non-G
Results (4/20): changing the popIII IMF
PopIII range (Salpeter IMF – top-heavy IMF) SN range (Salpeter IMF)
Mass ranges for popIII IMF and/or massive SN have significant impacts:
Larger masses → Shorter stellar lifetimes → Earlier enrichment →Shorter “popIII epoch”
(Maio et al., 2010)
IntroductionMethod
SimulationsThe End
PopIII and II, SFR, ZLF, GRBs, DLAs, Non-G
Results (5/20): halo properties
105 106
Mgas [Msunh-1]
10-7
10-6
10-5
10-4
SF
R [M
sun/
yr]
z=19.00z=18.01z=17.02z=16.00z=15.00z=14.00z=13.01z=12.00z=11.00z=10.00z=9.50z=9.12z=9.00
102 103 104 105
M* [Msunh-1]
10-7
10-6
10-5
10-4
SF
R [M
sun/
yr]
z=9.00z=9.12z=9.50
z=10.00z=11.00z=12.00z=13.01z=14.00z=15.00z=16.00z=17.02z=18.01z=19.00
105 106
Mgas [Msunh-1]
103
104
105
Tm [K
]
z=19.00z=18.01z=17.02z=16.00z=15.00z=14.00z=13.01z=12.00z=11.00z=10.00z=9.50z=9.12z=9.00
102 103 104 105
M* [Msunh-1]
1
10
100
sSF
R [G
yr-1]
z=19.00z=18.01z=17.02z=16.00z=15.00z=14.00z=13.01z=12.00z=11.00z=10.00
z=9.50z=9.12z=9.00
Biffi & Maio (2013)
IntroductionMethod
SimulationsThe End
PopIII and II, SFR, ZLF, GRBs, DLAs, Non-G
Results (6/20): halo populations
105 106
Mgas [Msunh-1]
10-9
10-8
10-7
10-6
10-5
10-4
Z
Zcrit=10-4 Zsun
z=19.00z=18.01z=17.02z=16.00z=15.00z=14.00z=13.01z=12.00z=11.00z=10.00z=9.50z=9.12z=9.00
8 10 12 14 16 18 20redshift
0.00
0.05
0.10
0.15
0.20
f hal
oes(
Z>
10-4Z
sun)
105 106
Mgas [Msunh-1]
10-5
10-4
10-3
10-2
10-1
Xm
ol
z=19.00z=18.01z=17.02z=16.00z=15.00z=14.00z=13.01z=12.00z=11.00z=10.00z=9.50z=9.12z=9.00
8 10 12 14 16 18 20z
0.0
0.2
0.4
0.6
0.8
1.0
SF
R h
alo
cont
ribut
ion
popII-IpopIII
Biffi & Maio (2013)
IntroductionMethod
SimulationsThe End
PopIII and II, SFR, ZLF, GRBs, DLAs, Non-G
Results (7/20): halo relations
10-9 10-8 10-7 10-6 10-5 10-4
Z
10-5
10-4
10-3
10-2
10-1
Xm
ol
z=19.00z=18.01z=17.02z=16.00z=15.00z=14.00z=13.01z=12.00z=11.00z=10.00z=9.50z=9.12z=9.00
10-7 10-6 10-5 10-4 10-3
M*/MDM
10-5
10-4
10-3
10-2
10-1
x mol
z=19.00z=18.01z=17.02z=16.00z=15.00z=14.00z=13.01z=12.00z=11.00z=10.00z=9.50z=9.12z=9.00
Mannucci et al. (2010)
3.0 3.5 4.0 4.5 5.0 5.5Log(M*[Msun]) - 0.32 Log(SFR[Msun/yr])
-10
-9
-8
-7
-6
-5
-4
Log(
Z)
z=9.00z=9.12z=9.50
z=10.00z=11.00z=12.00z=13.01z=14.00z=15.00z=16.00z=17.02z=18.01z=19.00
Unaccounted outliers...???Hetheroscedasticity...???
←− f⋆ − xmol correlation: f⋆ ∝ xmol
IntroductionMethod
SimulationsThe End
PopIII and II, SFR, ZLF, GRBs, DLAs, Non-G
Results (8/20): sSFR – early bursty Universe
0 5 10 15z
0.1
1.0
10.0
100.0
sSF
R [G
yr-1]
Coe (2013)Stark (2013)
Zheng (2012)Gonzalez (2012)Bouwens (2012)
Reddy (2012)Schiminovich (2010)Michalowski (2010)
Yabe (2009)Stark (2009)
Pannella (2009)Dunne (2009)Daddi (2007)
Noeske (2007)
DATA| |
Dave’ vzw (2011)Dave’ sw (2011)Dayal (2013)Salvaterra (2013)Tescari Ch24-sA-sW (2014)Biffi & Maio (2013)
THEORY
Biffi & Maio (2013)
IntroductionMethod
SimulationsThe End
PopIII and II, SFR, ZLF, GRBs, DLAs, Non-G
Results (9/20): disc formation and alignment
Haloes hosting rotating gas Alignment gas-DM
8 10 12 14 16 18 20redshift
0.00
0.05
0.10
0.15
0.20
f co-
rota
ting
halo
es
fcosϑ > 0.8 > 20%fcosϑ > 0.8 > 50%
xmol > 5e-4Z > 1e-3 ZsunZ > 1e-4 Zsun
105 106 107
Mgas [Msunh-1]
-1.0
-0.5
0.0
0.5
1.0
cosϑ
gas-
DM
aligned
contra-aligned
All z: corr= -0.0320.00 > z > 16.50, corr= 0.1316.50 > z > 14.50, corr= 0.1214.50 > z > 10.50, corr= -0.0910.50 > z > 8.50, corr= -0.02
cos ϑ =j · jmeanj jmean
cos ϑ =jgas,in · jDMjgas,in jDM
Biffi & Maio (2013)
IntroductionMethod
SimulationsThe End
PopIII and II, SFR, ZLF, GRBs, DLAs, Non-G
Results (10/20): UV luminosity functions
For each galaxy: Lλ = LIIλ + LIIIλ
in L5, L10, L30
PopII-I SEDs from Starbust99(Vazquez & Leitherer, 2005).PopIII SEDs from Schaerer (2002).No dust assumed
Observational data points from:
Bouwens et al., 2007 (circles); z=6Bouwens et al., 2011 (circles); z=7-8McLure et al., 2010 (triangles); z=7-8Oesch et al., 2012 (squares); z=8
Fit: Su et al., 2012 (solid line); z=6.
Resulting slope: ∼ −2consistent with HUDF data(Dunlop et al., 2013, Dayal, Dunlop, Maio, Ciardi, 2013)
Salvaterra, Maio, Ciardi, Campisi, 2013
IntroductionMethod
SimulationsThe End
PopIII and II, SFR, ZLF, GRBs, DLAs, Non-G
Results (11/20): Implications for high-z GRB hosts
Tracing LGRBs from the SFR of their host galaxies
Differential GRB hosting probability → dP =dNGRB(Log10(SFR[M⊙/yr ]))
NGRB dLog10(SFR[M⊙/yr])
Large objects (high SFR) are rarer than small objects (low SFR):high-z GRBs are more likely found in intermediate-, low-size objects!
IntroductionMethod
SimulationsThe End
PopIII and II, SFR, ZLF, GRBs, DLAs, Non-G
Results (12/20): UV luminosities of GRB hosts
Data points from:Tanvir et al., 2012
νion −→
Most high-z GRB hosts are primordial faint galaxies Most ionizing photons are produced in faint galaxies(they lie below current HST, VLT detection limits) (at z = 6 and z = 8)
IntroductionMethod
SimulationsThe End
PopIII and II, SFR, ZLF, GRBs, DLAs, Non-G
Results (13/20): Statistical properties of GRB hosts
SFR ∼ 0.01 − 0.1M⊙/yr M⋆ ∼ 107M⊙
sSFR ∼ 5 − 10 Gyr−1 Z ∼ 5 × 10−2Z⊙
Data from: Tanvir et al., 2012 (SFRs), Kawai et al., 2006 (Z)
See Salvaterra, Maio, Ciardi, Campisi (2013)
IntroductionMethod
SimulationsThe End
PopIII and II, SFR, ZLF, GRBs, DLAs, Non-G
Results (14/20): Physical relations for GRB hosts
IntroductionMethod
SimulationsThe End
PopIII and II, SFR, ZLF, GRBs, DLAs, Non-G
Results (15/20): PopIII-GRB rates and hostsLGRB rate:
different progenitorsi.e. stars with
1: Z > Zcrit→any popII-I
2: Zcrit < Z ≤ 0.5Z⊙→low-Z popII
3: Z ≤ Zcrit→ fGRBup = 0.006→ fGRBup2 = 0.022(upper limits fromSwift sample, 2011)
RGRB =γbζBH fGRB
4π
Z
zρ̇⋆
dz′
(1 + z′)
dV
dz′
Z
Lth(z′)
Ψ(L′)dL′
RGRB : gamma-ray burst rate, γb : beaming factor, ζBH : fractionof expected BH (IMF), fGRB : fraction of expected GRB fromcollapse onto a BH (Swift), ρ̇⋆ : star formation rate density(simulation), Ψ(L): Schechter luminosity fct. (assumption), Lth :instrumental sensitivity (Swift)PopIII IMF: top-heavy over [100, 500]M⊙PopII IMF: Salpeter over [0.1, 100]M⊙Zcrit = 10
−4 Z⊙
Detectable fraction (by BAT/Swift) of PopIII GRBs:∼ 10% at z > 6& 40% at z > 10of the whole population
PopIII-GRB-hosts:the highest probability of finding PopIII GRBs isin hosts with M⋆ < 10
7 M⊙ and Z & Zcrit(efficient pollution)
(from Campisi, Maio, Salvaterra, Ciardi, 2011)
IntroductionMethod
SimulationsThe End
PopIII and II, SFR, ZLF, GRBs, DLAs, Non-G
Results (16/20): observed DLAs at z ≃ 7?
10-8 10-7 10-6 10-5 10-4 10-3
Z
108
109M
[MS
un]
NHI,20
IntroductionMethod
SimulationsThe End
PopIII and II, SFR, ZLF, GRBs, DLAs, Non-G
Results (17/20): primordial matter distributions andNon-Gaussianities
Basic assumption: Gaussianperturbations → evidences fornon-Gaussianities (CMB).Primordial non-Gaussianities areintroduced via (Salopek & Bond, 1990)
Φ = ΦL + fNL(
Φ2L− < Φ2L >
)
Φ is the Bardeen potential(Newton potential at sub-Hubblescales), ΦL is thelinear (Gaussian)part, and fNL the non-Gaussianparameter.
credit: Planck
fNL = 0, 10, 50, 100, 1000box sides: 0.5 and 100 Mpc/hnumber of particles: 2 × 3203
gas mass resolution: 42 M⊙/hand 3 × 108 M⊙/h
See: Maio & Iannuzzi (2011), Maio (2011), Pace & Maio (2013)
IntroductionMethod
SimulationsThe End
PopIII and II, SFR, ZLF, GRBs, DLAs, Non-G
Results (18/20): Non-G and the cosmic web
fNL=0
fNL=1000
IntroductionMethod
SimulationsThe End
PopIII and II, SFR, ZLF, GRBs, DLAs, Non-G
Results (19/20): Non-G and the GRB rate
From Swift dataMaio, Salvaterra, Moscardini, Ciardi (2012)
IntroductionMethod
SimulationsThe End
PopIII and II, SFR, ZLF, GRBs, DLAs, Non-G
Results (20/20): Non-G and the SZ effect
Power spectrum andbi-spectrum for they parameter:
y =kBσT
mec2
Z
neTe dl
over sets of 100random light-cones
Pace & Maio (2013)
fNL=0 fNL=100 fNL=1000
1e-13
1e-12
1e-11
1000 10000 100000
l(l+
1)P
y(l)
l
fNL=0fNL=100
fNL=1000 1e-36
1e-35
1e-34
1e-33
1e-32
1e-31
1e-30
1e-29
1e-28
1e-27
1e-26
1000 10000 100000
By(
l)
l
fNL=0fNL=100
fNL=1000
IntroductionMethod
SimulationsThe End
Summary...
We have presented results from cosmological N-Body,hydrodynamical, chemistry and radiative simulations
We studied the birth of first galaxies, their interplay with thesurroundings and observational expectations (LF, GRB, DLA).
Conclusions...
Early (z ∼ 15 − 20) metal enrichment from the first stars is verystrong with a rapid popIII/popII-I transition (z ∼ 10). A correlationbetween f⋆ and gas xmol is expected. No correlations betweenearly discs and hosting DM halo are found.
Observationally, LFs agree with data and DLAs/GRBs aresuitable probes of the primordial Universe.
Results are not very sensitive to the assumed Zcrit , popIII metalyields, IMF slope, primordial non-Gaussianities, etc.
IntroductionMethod
SimulationsThe End
The End
Grazie! Thank you!Umberto Maio
Marie Curie FellowEuropean Union FP7/2007-2013,
Actions, Grant Agreement n. 267251,Marie Curie Incoming Mobility Fellowships,
Astronomy Fellowships in Italy (AstroFIt)
IntroductionMethod
SimulationsThe End
IntroductionMotivationsGeneral overview
MethodMolecules and metalsChemistry and cooling
SimulationsPopIII and II, SFR, ZLF, GRBs, DLAs, Non-G
The End