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TRANSCRIPT
Dust in the Wind: Intergalactic DustExtinction and its Implications
Ying Zu (OSU)
August 29, 2010
D.H. Weinberg (OSU), Romeel Dave(Arizona), Mark
Fardal(UMass), Neal Katz(UMass), Dusan Keres(Harvard),
and B. D. Oppenheimer(Leiden)
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1 IntroductionDiscovery of Intergalactic DustPossible Origins of “Intergalactic” DustMotivation
2 Simulations and Metal DistributionsSimulationsGalaxy Sample and Metal Distributions
3 Results3-D correlation functionsDust-to-Metal Ratio and Dust DistributionAn Alternative Hybrid Dust Model in No-Wind Simulation
4 Implications of Diffuse Cosmic Dust
5 Conclusions
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Figure: dust from the Eyjafjallajokull volcano (earth surface)
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Figure: noctilucent cloud possibly seeded by space dust (upperatmosphere)
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Figure: ghostly spokes in Saturn’s B ring, shadows of charged dust clouds(solar system)
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Figure: a dust cloud across a rich field of stars (local ISM)
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Figure: extended FIR emission indicates outflowing dust entrained bysuperwinds in M 82 (galactic halo)
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Can we extrapolate the existence of dust tothe IGM?
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Rudnicki, K. & Wszolek, B. (1992)
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Statistical Detection of IG DustMenard et al. (2010); MSFR
fobs = f0µe−τλ
Magnification by galaxiesµ: magnification
Extinction and reddeningdue to dust around galaxiesτλ: optical depth at λ
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Statistical Detection of IG Dust (MSFR)
MSFR examined the meancolors of photometricallyidentified quasars as functionof angular separation fromforegroud galaxies in a 3800square degree area from SDSS.
85, 000 quasars at z > 1
24 million galaxies atz ∼ 0.3
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Possible Origins of MSFR Dust
Pre-galactic: Pop III stars [Yoshida et al. (2004)] 7
Inner-galactic: LMC-like dwarfs ?
Extra-galactic: Winds [Davies et al. (1998)] ?
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“The Problem is of a Quantitative Nature“
Can the simulation with galactic winds explain MSFR observation?
What dust-to-metal ratio is required?
How is dust distributed in the simulation?
Do the models without galactic winds provide a vaible alternativeexplanation of MSFR observation?
What further observations can test the model predictions andprovide greater insight into IG dust?
What does this imply about the survival of dust in the IGM andhigh-Z SN comology?
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Simulations
Modified Gadget-2: Tree-particle-mesh + Smoothed particlehydrodynamics [Oppenheimer & Dave (2008)]
Ωm = 0.25,ΩΛ = 0.75,Ωb = 0.044, h = 0.7, σ8 = 0.8, n = 0.95(WMAP 5)
nDM = 2883, nSPH = 2883, L = 50 h−1Mpc, mSPH = 9× 107M
Galaxies: SKID groups of stars and cold (T < 3× 104K ) dense(ρ/ρbaryon > 1000) gas particles that are associated with a commondensity maximum, large than 64mSPH
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Galaxy Identification: SKID
Figure: Blue particles are dark matter, red are gas, and yellow arebaryonic particles where star formation has occurred [Weinberg et al.(2002)]
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Wind VS. No-Wind
Wind: “momentum-driven”
wind velocity ∝ σ [Murrayet al. (2005)]
mass-loading factor ∝ σ−1
No-Wind
no momentum injection
thermal energy of SNepressurizes the gas but doesnot drive outlfows
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Wind simulation is empirically successful tomatch:
early IGM enrichment [Oppenheimer & Dave (2008)]
galaxy mass-metalicity relation [Finlator & Dave (2008)]
OVI absorption at low redshift [Oppenheimer & Dave (2009)]
enrichment and entropy levels in galaxy groups [Dave et al. (2008)]
sub-L∗ regime of the galaxy baryonic mass function [Oppenheimeret al. (2009)]
CAVEAT: we take it only as a representative illustration of howwinds could influence IG dust in terms of total amount anddistribution of metal/dust
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Wind simulation is empirically successful tomatch:
early IGM enrichment [Oppenheimer & Dave (2008)]
galaxy mass-metalicity relation [Finlator & Dave (2008)]
OVI absorption at low redshift [Oppenheimer & Dave (2009)]
enrichment and entropy levels in galaxy groups [Dave et al. (2008)]
sub-L∗ regime of the galaxy baryonic mass function [Oppenheimeret al. (2009)]
CAVEAT: we take it only as a representative illustration of howwinds could influence IG dust in terms of total amount anddistribution of metal/dust
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Galaxy Sample
< z >∼ 0.36, Leff ∼ 0.45L∗ → ng ∼ 0.01 h3Mpc−3
⇓
Wind Model: mcut = 5.4× 1010M → ng ∼ 0.01 h3Mpc−3
No-Wind Model: mcut = 5.4× 1010M → ng ∼ 0.033 h3Mpc−3
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Dust Tracer: “Free Metal”
We assume that cosmic dust traces gas-phase metallicity that isnot associated with any SKID group (free metal), under theassumption that quasars behind galaxies will not make it into theSDSS sample
Model All Z (1010M) free Z (1010M)
Wind 288.0 100.7 (35.0%)No-Wind 277.9 8.2 (3%)
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Surface density maps of the free metals
Wind Model
1 Mpc/h
No Wind Model
1 Mpc/h
5 Mpc/h 5 Mpc/h
-5
-4
-3
-2
-1
LOG(ρ)M
⊙h2/pc3
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3-D correlation functions (Dark Matter)
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3-D correlation functions (Galaxies)
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3-D correlation functions (Gas)
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3-D correlation functions (Metal)
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Match To MSFR Observation (SMC Dust)
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Be Quantitative: Exclusion Zone Test
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Be Quantitative: P[E < E (g − i)] & E p(log E )/E
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Dust Confined inside Galaxies
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Disk Opacity of Dwarf Galaxies
Figure: AV extinction map of LMC [Dobashi et al. (2008)]
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Hybrid Model in No-Wind Simulation
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Problems with Hybrid Model
reddening signal is dominated by high E (g − i) values (> 0.1mag)
requires dwarf galaxies with baryonic mass ∼ few ×1010M(Mbaryonic
LMC ∼ 3× 109M)
galaxy stellar mass function is overestimated in the No-Windsimulation.
It is extremely difficult to explain MSFR observation withoutoutflows
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Problems with Hybrid Model
reddening signal is dominated by high E (g − i) values (> 0.1mag)
requires dwarf galaxies with baryonic mass ∼ few ×1010M(Mbaryonic
LMC ∼ 3× 109M)
galaxy stellar mass function is overestimated in the No-Windsimulation.
It is extremely difficult to explain MSFR observation withoutoutflows
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comparison of reddening maps three models
Hybrid Dust, No Wind Model-5-4
-3-2
-1
Free Dust, No Wind Model Free Dust, Wind Model
LOG
E(g-i)
25Mpc/h
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Implication: Dust Survival
Thermal sputtering time scale ∼ 107.5(nH/10−3cm−3)−1 yrs fora = 0.01µm at T = 106 K [Draine & Salpeter (1979)]
Wind particles typically remain in the IGM for ∼ 109 years beforereaccreting onto galaxies [Oppenheimer et al. (2009)]
Thermal sputtering rates decline rapidly towards lower T ( by afactor of 300 at T = 105K )
Most ejected gas never rises above a few ×104 K in our Windsimulation
There is indeed a narrow window of environment for dust grains toescape and survive in the IGM
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Implication: Dust Survival
Thermal sputtering time scale ∼ 107.5(nH/10−3cm−3)−1 yrs fora = 0.01µm at T = 106 K [Draine & Salpeter (1979)]
Wind particles typically remain in the IGM for ∼ 109 years beforereaccreting onto galaxies [Oppenheimer et al. (2009)]
Thermal sputtering rates decline rapidly towards lower T ( by afactor of 300 at T = 105K )
Most ejected gas never rises above a few ×104 K in our Windsimulation
There is indeed a narrow window of environment for dust grains toescape and survive in the IGM
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Implication: Dust Survival
Thermal sputtering time scale ∼ 107.5(nH/10−3cm−3)−1 yrs fora = 0.01µm at T = 106 K [Draine & Salpeter (1979)]
Wind particles typically remain in the IGM for ∼ 109 years beforereaccreting onto galaxies [Oppenheimer et al. (2009)]
Thermal sputtering rates decline rapidly towards lower T ( by afactor of 300 at T = 105K )
Most ejected gas never rises above a few ×104 K in our Windsimulation
There is indeed a narrow window of environment for dust grains toescape and survive in the IGM
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Implication: Dust Environment
Most wind particles has T < 105 K in halos with M < 1013M, butT > 3× 106 K in M > 1013M halos
The growth rate and the destruction rate would be comparably slowin the low density IGM (∼ n2)
Galaxy-dust correlation will vary in different environments if thescreening effect does exist
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Implication: Dust Environment
Most wind particles has T < 105 K in halos with M < 1013M, butT > 3× 106 K in M > 1013M halos
The growth rate and the destruction rate would be comparably slowin the low density IGM (∼ n2)
Galaxy-dust correlation will vary in different environments if thescreening effect does exist
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Implication: Supernova Cosmology
IG dust obscuration is an accumulated effect, thus a monolithicfunction of SN redshift
IG dust at different Z will affect a given observed-frame wavelengthin different ways
IG dust should have a different extinction curve with the dust in thehost galaxies of SN (grayer?)
The Wind simulation predicts a AV = 0.0048mag and rmssightline-to-sightline variance ∼ 0.0052mag at z = 0.5 (MSFRAV = 0.03mag?)
The IG dust extinction level is small compared to the statisticaland systematic errors of current SN surveys, but will be anon-trival source of systematics for next-generatoin surveys
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Implication: Supernova Cosmology
IG dust obscuration is an accumulated effect, thus a monolithicfunction of SN redshift
IG dust at different Z will affect a given observed-frame wavelengthin different ways
IG dust should have a different extinction curve with the dust in thehost galaxies of SN (grayer?)
The Wind simulation predicts a AV = 0.0048mag and rmssightline-to-sightline variance ∼ 0.0052mag at z = 0.5 (MSFRAV = 0.03mag?)
The IG dust extinction level is small compared to the statisticaland systematic errors of current SN surveys, but will be anon-trival source of systematics for next-generatoin surveys
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Implication: Supernova Cosmology
IG dust obscuration is an accumulated effect, thus a monolithicfunction of SN redshift
IG dust at different Z will affect a given observed-frame wavelengthin different ways
IG dust should have a different extinction curve with the dust in thehost galaxies of SN (grayer?)
The Wind simulation predicts a AV = 0.0048mag and rmssightline-to-sightline variance ∼ 0.0052mag at z = 0.5 (MSFRAV = 0.03mag?)
The IG dust extinction level is small compared to the statisticaland systematic errors of current SN surveys, but will be anon-trival source of systematics for next-generatoin surveys
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Conclusions
The wind simulation is able to reproduce the MSFR observationprovided that about 25% of the metal mass in the IGM is in theform of SMC-like dust.
The large scale reddening signal will drop to 75%, 50%, and 30% ofthe original signal if we exclude sightlines that pass within 50, 100,and 200 h−1kpc of galaxies. This exclusion zone predictation can beused to constrain IG dust distribution and wind physics.
It is very difficult for the simulation without outflows to explainMSFR result.
The existence of a large scale diffuse dust component has to betaken into account in future SN cosmology.
We anticipate the develepment of IG dust study will take a similarroute as the weak-lensing cosmology, thus provides new insights intothe origin, evolution, and observational impact of dust in the IGM.
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