dark-cosmology.dk /~pela
DESCRIPTION
Lighting up the light-shedding of illuminated enlightenment of bright light – or – Modeling Lya spectra. Peter Laursen, with Jens-Kristian Krogager & Johan Fynbo. | Niels Bohr Institutet | Københavns Universitet. www.dark-cosmology.dk /~pela. QSO2222-0946. - PowerPoint PPT PresentationTRANSCRIPT
www.dark-cosmology.dk/~pela
Lighting up the light-shedding of illuminated enlightenment of bright
light– or –
Modeling Lya spectra
| Niels Bohr Institutet | Københavns Universitet
Peter Laursen,with Jens-Kristian Krogager & Johan Fynbo
2
QSO2222-0946
HST/UVIS with the F606W filter
3
QSO2222-0946
VLT/X-Shooter (UVB arm)
4
QSO2222-0946
VLT/X-Shooter (UVB arm)
5
Modeling Ly lines
…has been done before
⇒
Verhamme et al. (2008) with MCLYA
6
MoCaLaTA
The model
7
Input parametersGeometry:• Radius• Number of clouds• Cloud size distributionState of the clouds and the intercloud medium:• Neutral hydrogen density• Temperature• Dust density ⇐ metallicityKinematics:• Cloud velocity dispersion• Outflow velocity
Emission:• Intrinsic line width• Emission scale length• Emission site/cloud correlation• Systemic redshift
rgal
Ncl
rcl,min; rcl,max; β
nHI,cl; nHI,ICM
THI,cl; THI,ICM
ZHI,cl; ZHI,ICM
V,cl
Vout
lin
e
He
m
Pcl
z
MoCaLaTA
8
rgal
Ncl
rcl,min; rcl,max; β
nHI,cl; nHI,ICM
THI,cl; THI,ICM
ZHI,cl; ZHI,ICM
V,cl
Vout
lin
e
He
m
Pcl
z
10 kpc∼105
10–100 pc;
Kim+ 03 (LMC)
–1.6
Dickey & Garwood 89; Williams & McKee 97
Input parameters
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10 kpc∼105
0.3 cm–
3;
0.2–0.5 cm-3 from e.g. Carilli+ 98; Ferrière 01; Gloeckler & Geiss 04 (MW)
ntot = 10–3–10–2 cm-3 (Dopita & Sutherland 03; Ferrière 01),xHI,ICM ∼ 10–8–10–5 (House 64; Sutherland & Dopita 93),
plus residual diffuse HI clouds.10–10–10–5 cm–3
10–100 pc;
–1.6
104 K;
106 K e.g. Brinks+ 00; Tüllmann+ 06,080.31
Z
From Zn, Si, and Fe abs. lines, as well as from[OII]/[OIII] and [NII]/H (R23 and N2 methods)
Input parameters
rgal
Ncl
rcl,min; rcl,max; β
nHI,cl; nHI,ICM
THI,cl; THI,ICM
ZHI,cl; ZHI,ICM
V,cl
Vout
lin
e
He
m
Pcl
z
10
10 kpc∼105
0.3 cm–
3; 10–10–10–5 cm–3
10–100 pc;
–1.6
104 K;
106 K0.31 Z
115±18 km s–1100–200 km s–1
From abs. line widths
Input parameters
rgal
Ncl
rcl,min; rcl,max; β
nHI,cl; nHI,ICM
THI,cl; THI,ICM
ZHI,cl; ZHI,ICM
V,cl
Vout
lin
e
He
m
Pcl
z
11
10 kpc∼105
10–100 pc;
–1.6
115±18 km s–1100–200 km s–1
130 km s–1 From [OII], [OIII], H, and H2.1 kpc From HST imaging (reff = 1.09 kpc)0.2–
0.5n/a
Input parameters
rgal
Ncl
rcl,min; rcl,max; β
nHI,cl; nHI,ICM
THI,cl; THI,ICM
ZHI,cl; ZHI,ICM
V,cl
Vout
lin
e
He
m
Pcl
z
0.3 cm–
3; 10–10–10–5 cm–3
104 K;
106 K0.31 Z
2.35 From [OII], [OIII], H, and H
12
10 kpc∼105
0.3 cm–
3; 10–10–10–5 cm–3
10–100 pc;
–1.6
104 K;
106 K0.31 Z
115±18 km s–1100–200 km s–1
130 km s–1
2.1 kpcn/a
Input parameters
Set by observationsStandard valuesFitted for
rgal
Ncl
rcl,min; rcl,max; β
nHI,cl; nHI,ICM
THI,cl; THI,ICM
ZHI,cl; ZHI,ICM
V,cl
Vout
lin
e
He
m
Pcl
z
2.35
13
Finding the best fit
1. Run trial models to get a rough fit
2. Run grid with Ncl ∈[104.5,105.5] and Vout ∈ [100,200] km s-1
⇒Ncl ∼ 105; Vout ∼ 150 km s-1
⇒
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Finding the best fit
3. Fit skewed Gaußians
4. Measurea) Red peak FWHMb) Peak separationc) Peak height ratiod) Peak flux ratio
2. Run grid with Ncl ∈[104.5,105.5] and Vout ∈ [100,200] km s-1
⇒Ncl ∼ 105; Vout ∼ 150 km s-1
1. Run trial models to get a rough fit
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Finding the best fit
3. Fit skewed Gaußians
4. Measurea) Red peak FWHMb) Peak separationc) Peak height ratiod) Peak flux ratio
2. Run grid with Ncl ∈[104.5,105.5] and Vout ∈ [100,200] km s-1
⇒Ncl ∼ 105; Vout ∼ 150 km s-1
1. Run trial models to get a rough fit
5. Calculate number of std. dev.s betweensynthetic and observed
spectra6. Identify best fitting model
and those for which all four fittingparameters fall within 1σ
16
Results
Best-fitting models give:Vout = 160 km s-1
log(NHI/cm-2) = 20.23Ncl = 2±1
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Results
Best-fitting models give:Vout = 160 km s-1
log(NHI/cm-2) = 20.23Ncl = 2±1
18
Conclusion
• Fitting Lya lines requires information about several parameters. A simple spectrum isn’t really enough.