Atomic and molecular data for stellar atmosphere modelling: Phoenix Darko Jevremović Astronomska opservatorija Belgrade Regional meeting on atomic and

Atomic and molecular data Atomic and molecular data

for stellar atmosphere for stellar atmosphere

modelling: Phoenixmodelling: Phoenix

Darko Jevremović Darko Jevremović Astronomska opservatorija Astronomska opservatorija

BelgradeBelgradeRegional meeting on atomic and molecular Regional meeting on atomic and molecular

datadata

BelgradeBelgradeJune 14June 14thth 2012 2012

OutlineOutline

PHOENIX – brief descriptionPHOENIX – brief description

A/M/D data needed A/M/D data needed

PHOENIX – highlights of resultsPHOENIX – highlights of results•personal viewpersonal view•66Li problemLi problem•Atmospheric models for Atmospheric models for evolutionary modelling and evolutionary modelling and populations synthesispopulations synthesis

ConclusionsConclusions

Stellar atmospheresStellar atmospheres

Thin layer between stellar interior Thin layer between stellar interior and vacuum and vacuum Thickness from few centimeters in Thickness from few centimeters in neutron stars to several A.U. In neutron stars to several A.U. In supergiantssupergiantsMost of information about stars are Most of information about stars are coming from that layer coming from that layer (temperature chemical composition (temperature chemical composition etc.)etc.)

PhoenixPhoenix

general stellar atmosphere codegeneral stellar atmosphere code

solves eq. of RT, SE and structure solves eq. of RT, SE and structure simultaneouslysimultaneously

used from novae/supernovae to used from novae/supernovae to brown dwarfs/extrasolar planets - brown dwarfs/extrasolar planets - now even AGN's neutron stars etc.now even AGN's neutron stars etc.

more than 500 papers about more than 500 papers about Phoenix methods/resultsPhoenix methods/results

Phoenix collaboratorsPhoenix collaboratorsPeter Hauschildt Professor and Andreas Schweitzer (and Peter Hauschildt Professor and Andreas Schweitzer (and bunch of students) Hamburg bunch of students) Hamburg

France Allard - Chercheur at the C.R.A.L. in Lyon, FranceFrance Allard - Chercheur at the C.R.A.L. in Lyon, France

Edward Baron - Professor at the University of Oklahoma Edward Baron - Professor at the University of Oklahoma

Dave R. Alexander Professor, Jason W. Ferguson – Dave R. Alexander Professor, Jason W. Ferguson – Assistant Professor at the Wichita State UniversityAssistant Professor at the Wichita State University

Travis Barman - Postdoc Lowel ObservatoryTravis Barman - Postdoc Lowel Observatory

Jason P. Aufdenberg – Assistant proffesor at Embry-Riddle Jason P. Aufdenberg – Assistant proffesor at Embry-Riddle Aeronautical University (Florida)Aeronautical University (Florida)

Darko Jevremovic Belgrade ObservatoryDarko Jevremovic Belgrade Observatory

Derek Homeier LyonDerek Homeier Lyon

Eric Lentz – Oak Ridge National LaboratoryEric Lentz – Oak Ridge National Laboratory

C. Ian Short Assistant Professor at the Saint Mary's C. Ian Short Assistant Professor at the Saint Mary's UniversityUniversity

Francis LeBlanc Professeur Agrégé at the Université de Francis LeBlanc Professeur Agrégé at the Université de Moncton, CanadaMoncton, Canada

Phoenix advantagesPhoenix advantages

huge number of ions treated in huge number of ions treated in NLTENLTE

excellent equation of state excellent equation of state (molecules, dust, clouds, choice of (molecules, dust, clouds, choice of metalicity)metalicity)

choice of plan-parallel or spherical choice of plan-parallel or spherical RT RT

velocity fieldsvelocity fields

many more - more than 300 many more - more than 300 parameters for each run parameters for each run

http://www.hs.uni-hamburg.de/EN/For/ThA/phoenix/index.html

Phoenix – general Phoenix – general

Basic physical modelBasic physical modelspherical shellspherical shell

static (stars) or expanding nova, winds, static (stars) or expanding nova, winds, SNSN

HS or HD equilibriumHS or HD equilibrium

central source provides energycentral source provides energy

energy conservation – temperature energy conservation – temperature structurestructure

momentum cons. pressure & velocity momentum cons. pressure & velocity str.str.

RT – special relativistic formRT – special relativistic form

PHOENIX RTPHOENIX RT

Assumptions:Assumptions:spherical symetryspherical symetry

time independence time independence

full special relativistic treatment in full special relativistic treatment in Lagrangian frameLagrangian frame

partial integro-differential equationspartial integro-differential equations

telegrapher's equation boundary value telegrapher's equation boundary value problem in spatial coordinate and problem in spatial coordinate and initial value problem in wavelength initial value problem in wavelength spacespace

Phoenix RTPhoenix RT

PHOENIX model PHOENIX model constructionconstruction

equation of state:equation of state:high temperature (hot stars, high temperature (hot stars, Supernovae, novae ) – need for many Supernovae, novae ) – need for many ionsions

low temperature (cool stars, brown low temperature (cool stars, brown dwarfs extrasolar planets) – need for dwarfs extrasolar planets) – need for molecules, dustmolecules, dust

statistical equilibrium & RT must statistical equilibrium & RT must be solved together – non localbe solved together – non local

new databases CHIANTI 4.02, 5.1, new databases CHIANTI 4.02, 5.1, APEDAPED

Table of NLTE speciesTable of NLTE species

PHOENIX MOLECULESPHOENIX MOLECULES

PHOENIX DUSTPHOENIX DUST

PHOENIX line blanketingPHOENIX line blanketing

• atomic line list ~42x10atomic line list ~42x106 6 lineslines• molecular line list ~10molecular line list ~109 9 lineslines

direct opacity sampling – of line direct opacity sampling – of line blanketing – dynamical selectionblanketing – dynamical selection

depth dependent Voigt or Gauss depth dependent Voigt or Gauss profileprofile

PHX computational PHX computational problemproblem

memory &I/O – line lists too large for memory memory &I/O – line lists too large for memory = scratch files= scratch files•number ofnumber ofpoints typically 30000-500,000 points typically 30000-500,000 leading to ~40,000 seconds of CPU time for leading to ~40,000 seconds of CPU time for one calculation of spectrumone calculation of spectrum

typically 10-20 iterations for model to typically 10-20 iterations for model to converge (in bad cases 100's)converge (in bad cases 100's)• leading to several days for a single model leading to several days for a single model (typical grid has thousands!!)(typical grid has thousands!!)

PHX computational PHX computational problemproblem

solution – paralel computation on solution – paralel computation on supercomputerssupercomputers

dramatically reduces wall-clock time per dramatically reduces wall-clock time per modelmodel

makes achievable full scale model makes achievable full scale model calculationscalculations

scaling nearly linear with number of CPU scaling nearly linear with number of CPU (limited by IO perfomance)...(limited by IO perfomance)...

AMD data for PhoenixAMD data for Phoenix

AMD data are used in different parts AMD data are used in different parts of the code for solving different of the code for solving different physical problems - interconnectedphysical problems - interconnectedEOSEOSOpacity calculationOpacity calculationRTRTNLTE/statistical equilibriumNLTE/statistical equilibrium


EOSEOSGoal to accurate calculate partial Goal to accurate calculate partial pressures for all the species at all pressures for all the species at all atmospheric depthsatmospheric depthsWe need good ionization potentials We need good ionization potentials for atomsfor atomsReaction rates for molecules Reaction rates for molecules Formation rates for dustFormation rates for dustComplex problem!! lot of matrix Complex problem!! lot of matrix inversionsinversions


Opacity calculationOpacity calculationPartial pressures + lists of atomic Partial pressures + lists of atomic and molecular linesand molecular linesNecessary to have accurate energy Necessary to have accurate energy levels, line strengths, and levels, line strengths, and parameters for Stark and Van der parameters for Stark and Van der Walls broadeningWalls broadeningFor each wavelength point and For each wavelength point and atmospheric depth contribution of all atmospheric depth contribution of all the lines in the vicinity is calculated the lines in the vicinity is calculated (DOS) (DOS)


RTRT emission and absorption coefficients emission and absorption coefficients for each wavelength/depth point for each wavelength/depth point enter in the RT equation and now it enter in the RT equation and now it is possible to solve it accuratelyis possible to solve it accuratelyAt the same time as the RT is solved At the same time as the RT is solved some integrals are calculated which some integrals are calculated which enter in SE (basically radiative rates enter in SE (basically radiative rates for each transition)for each transition)


NLTE/SENLTE/SEFor solving SE for each species we For solving SE for each species we do need radiative and collisional do need radiative and collisional rates (need cross sections)rates (need cross sections)And when solved we get the And when solved we get the population of every level of each population of every level of each NLTE treated species and they enter NLTE treated species and they enter calculations in the next iterationcalculations in the next iteration

PHOENIX ResultsPHOENIX Results

Sun, Vega...Sun, Vega...

Nova/Supernova modelsNova/Supernova models

wind-modelswind-models

cool stars & brown dwarfscool stars & brown dwarfs

AGNAGN

G2V (solar like)G2V (solar like)

VEGAVEGA

Nova Cygni 1992 Nova Cygni 1992

results – results – Sge SgeK5-M0III, Teff=3860 R=53Ro M=1.7Mo logg=0.55 Aufdenberg et al.

Deneb

Results -L/T dwarfsResults -L/T dwarfs

dust formation and opacitydust formation and opacity• TTeffeff <2500K <2500K

changes spectrum dramaticallychanges spectrum dramatically

cloud formationcloud formation• dust opacity drops for Tdust opacity drops for T

eff eff <1700K<1700K

results -cool atmospheresresults -cool atmospheres

AGN - example

AGN - example

Phoenix - personal viewPhoenix - personal view

how I got involved & some things I how I got involved & some things I worked onworked on new “chromospheric” mode - more new “chromospheric” mode - more

flexibility and comparison with other flexibility and comparison with other codescodes

radiative collisional switchingradiative collisional switching improved collisional routines improved collisional routines comparison with MULTIcomparison with MULTI treatment of depth dependant treatment of depth dependant turbulent velocityturbulent velocity

Phoenix - personal viewPhoenix - personal view

•66Li problem (BFS)Li problem (BFS)MnI/MgII interaction in solar MnI/MgII interaction in solar

chromospherechromospheregrid of models for stellar grid of models for stellar

evolutionary codes ( with Eddie and evolutionary codes ( with Eddie and Aaron)Aaron)introduction of introduction of

chemi-ionization/recombination chemi-ionization/recombination processes with Milan & Toljaprocesses with Milan & Tolja

66Li problemLi problem•66Li - light isotope of lithium three Li - light isotope of lithium three protons and three neutronsprotons and three neutrons•generally produced generally produced 22H(H() ) 66Li Li •Primordial origin - BBN - after H,Primordial origin - BBN - after H,22H ,H ,33He He and and 77Li the most abundant isotope, but Li the most abundant isotope, but calculated calculated 66Li/ Li/ 77Li ratio is 0.01% to 0.18%Li ratio is 0.01% to 0.18%•In some extreme predictions as high as In some extreme predictions as high as 3.7% (depending on reaction rate 3.7% (depending on reaction rate 66Li(p,a)Li(p,a)33HeHe

66Li problem – other possible Li problem – other possible sources sources

spalation from collisions of heavier spalation from collisions of heavier elements (CNO) with cosmic rayselements (CNO) with cosmic rays

galactic formation (cosmic rays from galactic formation (cosmic rays from spiral waves...)spiral waves...)

SNII enrichment of interstellar mediumSNII enrichment of interstellar medium

solar/stellar flaressolar/stellar flares

accretion of planets accretion of planets

66Li in Sun, cool starsLi in Sun, cool stars

Depletion during the early phases of Depletion during the early phases of stellar evolution (convective core - stellar evolution (convective core - destroying Li at 10destroying Li at 1066K - mixing material - K - mixing material - basically we do not expect almost any Li basically we do not expect almost any Li to survive)to survive)

determination of age using Li depletion - determination of age using Li depletion - assumption that Lithium can not be assumption that Lithium can not be produced on the surface of late type starsproduced on the surface of late type stars

but…but…

Solar wind – Solar wind – 66Li/Li/77Li around 3 %Li around 3 %

Solar atmosphere - Solar atmosphere - 66Li/ Li/ 77Li around 1%Li around 1%

Metheoritic data Metheoritic data 66Li/ Li/ 77Li around 2%Li around 2%

Other stars - measured up to 12 %???Other stars - measured up to 12 %???

So obviously something is not right So obviously something is not right

Measurements of Measurements of 66Li Li

In Sun – ultrahigh resolution In Sun – ultrahigh resolution spectroscopyspectroscopy

Problem - Problem - 66Li has basically the same Li has basically the same electronic structure as electronic structure as 77Li with a small Li with a small isotopic shift (around 0.1isotopic shift (around 0.1))

first attempts in stars – using line first attempts in stars – using line asymetries - not very reliableasymetries - not very reliable

other option – measuring center of other option – measuring center of gravity gravity

Measurements of Measurements of 66LiLi

in the past few years spectrum in the past few years spectrum synthesis - comparison with observed synthesis - comparison with observed spectraspectra

necessary to have excellent atomic necessary to have excellent atomic data for spectral synthesis data for spectral synthesis

observations with very high observations with very high resolution and very high S/N resolution and very high S/N

ObservationsObservations

Belfast groupBelfast group4 stars VLT Kueyen Telescope UVES4 stars VLT Kueyen Telescope UVESreduced using IRAFreduced using IRAF

Modeling using PhoenixModeling using Phoenix

stellar parametersstellar parameters

LTE NextGen modelsLTE NextGen models•introduction of shifted introduction of shifted 66Li lines in the Li lines in the master listmaster list

intervention in the codeintervention in the code

ModelingModeling

We introduce We introduce 66Li/Li/77Li as a parameterLi as a parameter

direct opacity sampling = at each direct opacity sampling = at each wavelength point opacity is calculated wavelength point opacity is calculated as a sum of opacities from all as a sum of opacities from all contributing speciescontributing species

((77Li)Li) =(1- =(1-)) ((77Li)totLi)tot

((66Li)Li) = =((66Li)totLi)tot

ResultsResults

22 minimization minimization

66Li Parameters Li Parameters

Models for stellar evolution and Models for stellar evolution and population synthesispopulation synthesis

DSED – Dartmouth stellar evolution DSED – Dartmouth stellar evolution database database http://stellar.dartmouth.edu/~modelshttp://stellar.dartmouth.edu/~models

More tha 6000 models in LTE different More tha 6000 models in LTE different metalicitiesmetalicities

Used as boundary conditions for Used as boundary conditions for evolutionary modelsevolutionary models

http://stellar.dartmouth.edu/~models


AMES AMES basic grid – improved treatment of basic grid – improved treatment of molecules; added huge number of molecules; added huge number of H2O, VO and TiO lines – AMES lines; H2O, VO and TiO lines – AMES lines; dust settling etc.dust settling etc.

T=2000 – 10000KT=2000 – 10000K

log Z=-2.5 - +0.5log Z=-2.5 - +0.5

log g = 0-5 log g = 0-5


new grid based on AMES modelsnew grid based on AMES modelsimproved abundances of elements improved abundances of elements using GS98 abundancesusing GS98 abundances

there are some changes:there are some changes:

log Z=-2.5,-2.0 -1.5, -1.0, -0.5, 0.0, log Z=-2.5,-2.0 -1.5, -1.0, -0.5, 0.0, +0.15 +0.3, +0.5+0.15 +0.3, +0.5

introduction of different enhancement introduction of different enhancement of alpha elements of alpha elements

alpha=-0.2, 0, +0.2 +0.4 +0.6 +0.8alpha=-0.2, 0, +0.2 +0.4 +0.6 +0.8

Modeling examples T Modeling examples T (3000,5000, (3000,5000, 7000, 9000, logg=4.5, Z=-1)7000, 9000, logg=4.5, Z=-1)

Modeling examples Z Modeling examples Z (-2.5,-1.5, (-2.5,-1.5, -0.5, +0.5, Teff=4000, logg=4.5, -0.5, +0.5, Teff=4000, logg=4.5, alpha=+0.2)alpha=+0.2)

Modeling examples Modeling examples (0, 0.2, (0, 0.2, 0.4, 0.6,0.8 Teff=4000, logg=4.5, Z=-0.4, 0.6,0.8 Teff=4000, logg=4.5, Z=-2)2)

Some resultsSome results

NGC 6791NGC 6791

Preliminary results other Preliminary results other clustersclusters

VAMDC data for PhoenixVAMDC data for Phoenix

Summary – we need many many Summary – we need many many very accurate AMD data to calculate very accurate AMD data to calculate good and proper spectragood and proper spectraVAMDC concept is very interesting VAMDC concept is very interesting for uniformity of data and easier for uniformity of data and easier accessaccessWe are a bit old fashioned – we bring We are a bit old fashioned – we bring data to the computational resources data to the computational resources – meaning that usually we download – meaning that usually we download data from database only once data from database only once

VAMDC data for PhoenixVAMDC data for Phoenix

Bit impractical to move Gbytes of data Bit impractical to move Gbytes of data around around

We are interested in accuracy/quality We are interested in accuracy/quality assessment of dataassessment of data

Service which would do proper referencing Service which would do proper referencing and crediting of our sources of data would be and crediting of our sources of data would be much appreciated much appreciated

Service with information and alerts about Service with information and alerts about newly available data (as most of us does not newly available data (as most of us does not have resources to follow all the literature)have resources to follow all the literature)

ConclusionsConclusions

Phoenix is powerful tool for doing different Phoenix is powerful tool for doing different things in astrophysical plasma modelling things in astrophysical plasma modelling

Generally we like problems – when solved Generally we like problems – when solved new important results follownew important results follow

Extensions – 2D just about to become fully Extensions – 2D just about to become fully operational - will broaden operational - will broaden

3D first steps taken 3D first steps taken

GR included in principleGR included in principle

Better atomic/molecular data etc...Better atomic/molecular data etc...

More physics....More physics....

Thanks for your attentionThanks for your attention

Collisional routinesCollisional routines

Collisional routines (Mg, Collisional routines (Mg, Ca)Ca)

Documents

Atomic and molecular data for stellar atmosphere modelling: Phoenix Darko Jevremović Astronomska opservatorija Belgrade Regional meeting on atomic and