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Atomic and molecular data for stellar atmosphere modelling: Phoenix

Darko Jevremović Astronomska opservatorija Belgrade Regional meeting on atomic and molecular data Belgrade June 14 th 2012. Atomic and molecular data for stellar atmosphere modelling: Phoenix. Outline. PHOENIX – brief description A/M/D data needed PHOENIX – highlights of results

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Atomic and molecular data for stellar atmosphere modelling: Phoenix

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  1. Darko Jevremović Astronomska opservatorija Belgrade Regional meeting on atomic and molecular data Belgrade June 14th 2012 Atomic and molecular data for stellar atmosphere modelling: Phoenix

  2. Outline • PHOENIX – brief description • A/M/D data needed • PHOENIX – highlights of results • personal view • 6Li problem • Atmospheric models for evolutionary modelling and populations synthesis • Conclusions

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

  4. Phoenix general stellar atmosphere code solves eq. of RT, SE and structure simultaneously used from novae/supernovae to brown dwarfs/extrasolar planets - now even AGN's neutron stars etc. more than 500 papers about Phoenix methods/results

  5. Phoenix collaborators Peter Hauschildt Professor and Andreas Schweitzer (and bunch of students) Hamburg France Allard - Chercheur at the C.R.A.L. in Lyon, France Edward Baron - Professor at the University of Oklahoma Dave R. Alexander Professor, Jason W. Ferguson – Assistant Professor at the Wichita State University Travis Barman - Postdoc Lowel Observatory Jason P. Aufdenberg – Assistant proffesor at Embry-Riddle Aeronautical University (Florida)‏ Darko Jevremovic Belgrade Observatory Derek Homeier Lyon Eric Lentz – Oak Ridge National Laboratory C. Ian Short Assistant Professor at the Saint Mary's University Francis LeBlanc Professeur Agrégé at the Université de Moncton, Canada

  6. Phoenix advantages huge number of ions treated in NLTE excellent equation of state (molecules, dust, clouds, choice of metalicity)‏ choice of plan-parallel or spherical RT velocity fields many more - more than 300 parameters for each run http://www.hs.uni-hamburg.de/EN/For/ThA/phoenix/index.html

  7. Phoenix – general • Basic physical model • spherical shell • static (stars) or expanding nova, winds, SN • HS or HD equilibrium • central source provides energy • energy conservation – temperature structure • momentum cons. pressure & velocity str. • RT – special relativistic form

  8. PHOENIX RT • Assumptions: • spherical symetry • time independence • full special relativistic treatment in Lagrangian frame • partial integro-differential equations • telegrapher's equation boundary value problem in spatial coordinate and initial value problem in wavelength space

  9. Phoenix RT

  10. PHOENIX model construction • equation of state: • high temperature (hot stars, Supernovae, novae ) – need for many ions • low temperature (cool stars, brown dwarfs extrasolar planets) – need for molecules, dust • statistical equilibrium & RT must be solved together – non local • new databases CHIANTI 4.02, 5.1, APED

  11. Table of NLTE species

  12. PHOENIX MOLECULES

  13. PHOENIX DUST

  14. PHOENIX line blanketing • atomic line list ~42x106 lines • molecular line list ~109 lines • direct opacity sampling – of line blanketing – dynamical selection • depth dependent Voigt or Gauss profile

  15. PHX computational problem • memory &I/O – line lists too large for memory = scratch files • number ofpoints typically 30000-500,000 leading to ~40,000 seconds of CPU time for one calculation of spectrum • typically 10-20 iterations for model to converge (in bad cases 100's)‏ • leading to several days for a single model (typical grid has thousands!!)‏

  16. PHX computational problem solution – paralel computation on supercomputers dramatically reduces wall-clock time per model makes achievable full scale model calculations scaling nearly linear with number of CPU (limited by IO perfomance)...

  17. AMD data for Phoenix • AMD data are used in different parts of the code for solving different physical problems - interconnected • EOS • Opacity calculation • RT • NLTE/statistical equilibrium

  18. AMD data for Phoenix • EOS • Goal to accurate calculate partial pressures for all the species at all atmospheric depths • We need good ionization potentials for atoms • Reaction rates for molecules • Formation rates for dust • Complex problem!! lot of matrix inversions

  19. AMD data for Phoenix • Opacity calculation • Partial pressures + lists of atomic and molecular lines • Necessary to have accurate energy levels, line strengths, and parameters for Stark and Van der Walls broadening • For each wavelength point and atmospheric depth contribution of all the lines in the vicinity is calculated (DOS)

  20. AMD data for Phoenix • RT • emission and absorption coefficients for each wavelength/depth point enter in the RT equation and now it is possible to solve it accurately At the same time as the RT is solved some integrals are calculated which enter in SE (basically radiative rates for each transition)

  21. AMD data for Phoenix • NLTE/SE • For solving SE for each species we do need radiative and collisional rates (need cross sections) • And when solved we get the population of every level of each NLTE treated species and they enter calculations in the next iteration

  22. PHOENIX Results Sun, Vega... Nova/Supernova models wind-models cool stars & brown dwarfs AGN

  23. G2V (solar like)‏

  24. VEGA

  25. Nova Cygni 1992

  26. results –  Sge K5-M0III, Teff=3860 R=53Ro M=1.7Mo logg=0.55 Aufdenberg et al.

  27. Deneb

  28. Results -L/T dwarfs • dust formation and opacity • Teff <2500K • changes spectrum dramatically • cloud formation • dust opacity drops for Teff <1700K

  29. results -cool atmospheres

  30. AGN - example

  31. AGN - example

  32. Phoenix - personal view • how I got involved & some things I worked on • new “chromospheric” mode - more flexibility and comparison with other codes • radiative collisional switching • improved collisional routines comparison with MULTI • treatment of depth dependant turbulent velocity

  33. Phoenix - personal view • 6Li problem (BFS)‏ • MnI/MgII interaction in solar chromosphere • grid of models for stellar evolutionary codes ( with Eddie and Aaron)‏ • introduction of chemi-ionization/recombination processes with Milan & Tolja

  34. 6Li problem 6Li - light isotope of lithium three protons and three neutrons generally produced 2H() 6Li Primordial origin - BBN - after H,2H ,3He and 7Li the most abundant isotope, but calculated 6Li/ 7Li ratio is 0.01% to 0.18% In some extreme predictions as high as 3.7% (depending on reaction rate 6Li(p,a)3He

  35. 6Li problem – other possible sources spalation from collisions of heavier elements (CNO) with cosmic rays galactic formation (cosmic rays from spiral waves...)‏ SNII enrichment of interstellar medium solar/stellar flares accretion of planets

  36. 6Li in Sun, cool stars Depletion during the early phases of stellar evolution (convective core - destroying Li at 106K - mixing material - basically we do not expect almost any Li to survive)‏ determination of age using Li depletion - assumption that Lithium can not be produced on the surface of late type stars

  37. but… Solar wind – 6Li/7Li around 3 % Solar atmosphere - 6Li/ 7Li around 1% Metheoritic data 6Li/ 7Li around 2% Other stars - measured up to 12 %??? So obviously something is not right

  38. Measurements of 6Li In Sun – ultrahigh resolution spectroscopy Problem - 6Li has basically the same electronic structure as 7Li with a small isotopic shift (around 0.1)‏ first attempts in stars – using line asymetries - not very reliable other option – measuring center of gravity

  39. Measurements of 6Li in the past few years spectrum synthesis - comparison with observed spectra necessary to have excellent atomic data for spectral synthesis observations with very high resolution and very high S/N

  40. Observations • Belfast group • 4 stars VLT Kueyen Telescope UVES • reduced using IRAF

  41. Modeling using Phoenix stellar parameters LTE NextGen models introduction of shifted 6Li lines in the master list intervention in the code

  42. Modeling We introduce 6Li/7Li as a parameter direct opacity sampling = at each wavelength point opacity is calculated as a sum of opacities from all contributing species (7Li) =(1-)(7Li)tot (6Li) =(6Li)tot

  43. Results

  44. 2 minimization

  45. 6Li Parameters

  46. Models for stellar evolution and population synthesis DSED – Dartmouth stellar evolution database http://stellar.dartmouth.edu/~models More tha 6000 models in LTE different metalicities Used as boundary conditions for evolutionary models

  47. Models for stellar evolution and population synthesis • AMES • basic grid – improved treatment of molecules; added huge number of H2O, VO and TiO lines – AMES lines; dust settling etc. • T=2000 – 10000K • log Z=-2.5 - +0.5 • log g = 0-5

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