Atomic and molecular data for stellar atmosphere modelling: Phoenix Darko Jevremović Astronomska...
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Transcript of Atomic and molecular data for stellar atmosphere modelling: Phoenix Darko Jevremović Astronomska...
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
AMD data for PhoenixAMD data for Phoenix
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
AMD data for PhoenixAMD data for Phoenix
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)
AMD data for PhoenixAMD data for Phoenix
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)
AMD data for PhoenixAMD data for Phoenix
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
Models for stellar evolution and Models for stellar evolution and population synthesispopulation synthesis
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
Models for stellar evolution and Models for stellar evolution and population synthesispopulation synthesis
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)