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Page 1: Lecture 2 - iac.esiac.es/winterschool/2017/media/Lectures_XXIX/lecture2.pdf · 8 ‘Recipe-based modelling’ making a solar model spectrum is possible adjusting MANY free parameters:

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Lecture 2

Page 2: Lecture 2 - iac.esiac.es/winterschool/2017/media/Lectures_XXIX/lecture2.pdf · 8 ‘Recipe-based modelling’ making a solar model spectrum is possible adjusting MANY free parameters:

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Models of cool stellar atmospheres and synthetic spectra

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time-independent1D geometrya star is flat (spherically-symmetric only for giants)local thermodynamic equilibriumno sources or sinks of enegryhydrostatic equilibriumsimple convection recipies - MLTno winds, magnetic fieldsno chromopsheres

Classical models of stellar atmospheresKurucz, Marcs http://kurucz.harvard.eduhttp://marcs.astro.uu.se

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MariaBergemann5

ateachdepth

Classical models of stellar atmospheres

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MariaBergemann6

ateachdepth

Input parametersfor a model atmosphere

Classical models of stellar atmospheres

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Page 8: Lecture 2 - iac.esiac.es/winterschool/2017/media/Lectures_XXIX/lecture2.pdf · 8 ‘Recipe-based modelling’ making a solar model spectrum is possible adjusting MANY free parameters:

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‘Recipe-based modelling’making a solar model spectrum is possible

adjusting MANY free parameters:

✓ abundances to match meteorites

✓ mixing length to approximate convective energy transport

✓ ‘micro-’, ‘macro-turbulence’ to represent turbulent mixing

✓ ‘astrophysical’ atomic data

Classical models of stellar atmospheres

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Models of (cool) stellar atmospheres➡ Hydrodynamics and convection ➡ Non-local thermodynamic equilibrium➡ Chromospheres➡ Coronae➡ Pulsations➡ Winds and mass loss➡ Terrible amounts of data from atomic and nuclear physics➡ Molecular opacities➡ Asymmetric shapes with ‘hot spots’➡ MOLsphere (H2O, SiO) ➡ Non-equilibrium chemistry

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LTE works remarkably well

in many cases

but it fails, too, sometimes…

Non-local thermodynamic equilibrium

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Non-local thermodynamic equilibrium

very low densities in the atmospherescollisions between gas particles are too weak to establish LTE

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Non-LTE reaction channelsoverionization and photon pumping by super-thermal radiation field

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Non-LTE reaction channelsoverrecombination and photon suctionoverionization and photon pumping

by super-thermal radiation field

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Non-LTE reaction channelsoverrecombination and photon suctionoverionization and photon pumping

by super-thermal radiation field resonance line scattering & photon loss

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LTENLTE

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Non-local thermodynamic equilibriumeffect on solar elemental abundances from -0.3 to +0.2 dex

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4 6 8 10 12 14Ionisation potential (eV)

-0.4

-0.3

-0.2

-0.1

0.0

0.1

0.2

0.3

∆ N

LTE

-0.4

-0.2

0.0

0.2

KNa

Eu

Al

FeMg

Si

Zn

S CO

N

3D NLTE1D NLTE

Li

Non-local thermodynamic equilibriumeffect on solar elemental abundances from -0.3 to +0.2 dex

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Turnoff star

NLTE effects grow with Teff, log(g), and [Fe/H]

Red giant

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Modelling spectral linesmodelling spectra of cool stars: lines are not simple gaussians Hyperfine structure, isotopic shifts, pressure broadening

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radiative energy exchange

mass conservation

momentum conservation

energy conservation

Radiative hydrodynamics (RHD)

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Grids of 3D RHD modelshttps://staggergrid.wordpress.com

Convection and granulation:- all FGKM stars- granules larger for lower log(g)and [Fe/H]- contrast larger for higher Teff

Freytag et al. (1997)

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X

Z

3D RHD simulation of a metal-poor red giant star → no well-defined stellar surface

optical surface

2Mm

color - temperature

3D RHD or hydrostatic?

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Convective overshoot into the photosphere the concept of a ‘mean’ 1D hydrostatic structure is meaningless

3D RHD model atmospheres

Collet (2008)

upflow

downdraft1D Radiative Eq.

in metal-poor stars, adiabatic cooling dominates overradiative heating Qrad

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• rising and descending gas volumes have different line-of-sight velocities

• spectral lines are shifted and asymmetric

3D RHD model atmospheres

Fe II line profile in a 3D simulation of solar surface convection

Nordlund et al. (2009)

Colour-Temperature

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3D RHD model atmospheresElemental abundances from molecular lines are lower than predictions of 1D hydrostatic models

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1D LTE estimateof Teff and log(g)

Stellar parameters

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<3D>NLTETeff<3D>NLTETeff

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<3D>NLTETeff

<3D>NLTElog(g)

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29Bergemann et al. (2012)

<3D>NLTETeff

<3D>NLTElog(g)

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Red Supergiants: atmospheres

➡ Global 3D RHD simulations star-in-a-boxstar completely enclosed in simulation domain

➡ Boundary conditions: ➡ central luminosity source, ➡ open external boundaries

➡ Low spatial resolution

➡ Gravity: prescribed potential

➡ Opacities: grey or binning

➡ Time per model: monthsChiavassa et al. (2011,2013)

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Velocity fields have an effect on the structure of atmosphere through the line blanketing

CO lines

in 1D hydrostatic models, V fields are represented by ‘micro-turbulence’ and ‘macro-turbulence’

3D RHD model atmospheres

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The effect of convection on the radiation field is huge in the frequencies of strong molecular absorption (e.g. TiO)

3D RHD model atmospheres

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Model fit to TiO bands (Teff = 3560 K)

Model fit to the full SED (Teff = 4280 K)

TiO: overestimate the flux in the near IRoptical/IR SED: under-predict the TiO strengths

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Red Supergiants: atmospheres

Tsuji (2003)

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36Davies et al. (2013)

Unsolved problems

are RSG warm or cool?SED fittingTiO fitting

impact on evolution of massive stars and SNe

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AGB stars

3D RHD simulationsof the outer envelope and atmosphere

- long-lasting giant convection cells, ~years- short-lived surface granules- strong radial pulsations → shocks→ radiation pressure on dust winds

Freytag et al. (2017)

x(RSun)

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Left: The spherically averaged radial velocity V(r; t) for the full run time and radial distance. Right: mass-shell movements plotted as iso-mass contour lines

AGB stars

Freytag et al. (2017)

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Schematic view of an AGB atmosphere

Decin (2003)

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Stars and windsThe Sun RSG Blue Supergiants

Driving mechanism d Pgas/dr Prad on ions and dust

Prad on ions

mass (MSun) 1 8 … 40 10 … 100luminosity (LSun) 1 104 … 106 105 … 106

radius (RSun) 1 500 … 1500 10 … 200

Teff (K) 5777 3000 104 … 5 104

wind temperature (K) 106 1000 8000 … 40000

mass loss rate (MSun/yr) 10-14 10-6 … 10-4 10-6 … 10-5

life time (yr) 1010 105 107

total mass loss (MSun) 10-4 < 0.5 90 %