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Atmospheric dynamics of red supergiant stars

Atmospheric dynamics of red supergiant stars. Andrea Chiavassa Groupe de Recherche en Astronomie et Astrophysique du Languedoc GRAAL. Thesis advisor: Bertrand Plez. Outline. RSG stars The modeller's point of view The virtual observer’s point of view Spectroscopy Interferometry

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Atmospheric dynamics of red supergiant stars

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  1. Atmospheric dynamics of red supergiant stars Andrea Chiavassa Groupe de Recherche en Astronomie et Astrophysique du Languedoc GRAAL Thesis advisor: Bertrand Plez

  2. Outline • RSG stars • The modeller's point of view • The virtual observer’s point of view • Spectroscopy • Interferometry • Conclusions et perspectives

  3. Outline • RSG stars • The modeller's point of view • The virtual observer’s point of view • Spectroscopy • Interferometry • Conclusions et perspectives

  4. RSG stars - 1 RRSG 500 - 1000 Rsun 10 < MRSG < 30 Msun 3450 K < TRSG < 4100K (Levesque et al., 2005) Meynet & Maeder, 2003

  5. RSG stars - 2 AAVSO Vis mag Time RSGs: • are irregular, small-amplitude variables - strong molecular bands (TiO ...) • broad lines (vmacro10 km/s, Josselin et Plez 2004)  continuum poorly defined, spectrum synthesis is difficult ... Flux (arbitrary units)

  6. RSG stars - 3 Profiles are variable in depth, width and velocity ! (stronger variations are seen in other RSG). Time-variable structure in line profiles is a natural and necessary consequence of giant convective cells Josselin & Plez, 2007

  7. RSG stars - 4 Haubois et al. 2006 H band - IONIC Alpha Ori is big and relatively nearby. Excellent target for Interferometry • Surface inhomogeneities • Parametric models not enough to explain physics • Need for more complicated models? HST - Faint Object Camera UV Bright spot model for 700 nm (TiO) mas Young et al. 2000 mas

  8. And the answers to RSG questions? • CO5BOLD (COnservative COde for the COmputation of COmpressible COnvection in a BOx of L Dimensions, l=2,3) developed by Freytag, Steffen, Ludwig et al. (for RSG, Freytag et al., 2002; 2008 in prep.) • Key point: coupling of radiation and hydrodynamics, which dominates in the physics of the transition layers • This tool will help to investigate: • the nature of the convection pattern • the atmospheric velocity fields • the impact of convection on spectral lines, visibility curves and phases

  9. Outline • RSG stars • The modeller's point of view • The virtual observer’s point of view • Spectroscopy • Interferometry • Conclusions et perspectives

  10. The modeller's point of view, CO5BOLD - 1 • STAR-IN-A-BOX setup: • Used to model RSG stars • The gravitation is spherical potential • The computational domain is a cube with equidistant directions, all the 6 surfaces have the same open boundaries • Strictly LTE and short characteristic method • Grey and non-grey (5 bins, under development) Bolometric Intensity - Freytag et al. 2002

  11. http://www.astro.uu.se/~bf/ (B. Freytag)

  12. Velocity fields • Velocities are a consequence of the strong convective motions. Approx radius position • Shock peak velocities saturates at  25 km/s. • In the upper photosphere the velocities are typically supersonic (Mach>1). Mach number 1 Radius (Rsun)

  13. RSG simulations: state-of-the art Polynomial fit • CPU-time: 100 days more or less continuously on CPU-clock speed of 3 GHz • Drifting parameters, but relaxation in the last part Radius (Rsun) Time (years)

  14. Out line • RSG stars • The modeller's point of view • The virtual observer’s point of view • Spectroscopy • Interferometry • Conclusions et perspectives

  15. 3D radiative transfer code OPTIM3D - 1 • Integral computed with Gauss-Laguerre quadrature of order 9 1.1 sec /  (numerical resolution 2353) R = / = c/v  100000 at 6000 Å ~ 5 h / 1000Å ! (clock speed of 3 GHz)

  16. 3D radiative transfer code OPTIM3D - 2 • Opacity tables generated with MARCS with billion of molecular (see Gustafsson, 2008) and atomic (VALD) lines • Double linear interpolation for T and  only once • Linear interpolation at right wavelength • /= R = 500000

  17. 3D radiative transfer code OPTIM3D - 3 • Cross-check: Linfor3D on 3D CO5BOLD local model for 3 artificial iron lines • Interpolation in the opacity tables is the main cause of the difference • OPTIM3D  large range of wavelength + millions of lines simultaneously • Linfor3D  high performing abundances determination

  18. OPTIM3D produces: UVES lpha Ori RHD model To constrain the atmospheric dynamics To constrain the structure size

  19. Surface pattern of RSGs

  20. H band - Large convective cells • Large cell 400-500 Rsun, lifetime of years (st35gm03n07) • Lifetime intergranular lanes and dark spots few months

  21. Optical - complex convection pattern H band TiO 6100 A Ca II H line Bright spot model for 700 nm (TiO) • Complex substructures - More spectacular than in H band! • Inversion of the contrast • Shocks in Ca II H line! mas Star at 174.3 pc ( 44.6 mas) Young et al. 2000 mas -1000 Rsun Shocks +1000

  22. Photocenter H band (3.5 years covered) TiO 6100 A (1.5 years covered) +1 mas • TiO displacement up to 120 Rsun (15% stellar radius) and 20 Rsun for H band • If alpha Ori at 200pc: - TiO displacement  2.8 mas (detectable with GAIA!) - H band  0.5 mas -1 mas -2 mas +1 mas

  23. Summary • The convection pattern of RSGs changes with the wavelength • Large convective cells • Spectacular in the optical • Calibration for GAIA

  24. Out line • RSG stars • The modeller's point of view • The virtual observer’s point of view • Spectroscopy • Interferometry • Conclusions et perspectives

  25. Characteristic velocities in the atmosphere - 1 asymmetric, variable cross-correlation functions (CCF) and irregular variations How to extract dynamical information ? Tomography (Alvarez et al. 2001) C8 C1 Velocity (km/s) Velocity (km/s) Synthetic spectrum’s CCF in the optical range Observed CCF of MuCep (Josselin & Plez, 2007)

  26. Characteristic velocities in the atmosphere - 2 The velocityamplitude is in qualitative agreement with the observations. Even mask C1 is not 0 km/s  simulation  observations < v(C1) > = 2.3 km/s V466 Cas

  27. Characteristic velocities in the atmosphere - 3 20 km/s v(C8r) vs v(C8b) v(C8r) vs C1 v(C8b) vs C1  8 km/s Simulation: time covered ≈ 1.5 year The trend of the variations is in qualitative agreement (e.g., slope of the black curve) Velocity amplitudes larger in the observations Representative Observations: time covered ≈ 1.5 year (Josselin & Plez 2007)

  28. Characteristic velocities in the atmosphere - 4 depth(C8r) vs v(C8b) depth(C8r) vs C1 depth(C8b) vs C1 Simulation: time covered ≈ 1.5 year The trend of the variations is in qualitative agreement (e.g. slope blue and red) C1 is deeper in the simulations Representative Observations: time covered ≈ 1.5 year (Josselin & Plez 2007)

  29. CO lines comparison to Wallace & Hinkle, 1996 Depth and width reproduced without need for micro- or macro-turbulence. < v correction > = - 2.3 km/s < v correction > = - 0.9 km/s Flux (arbitrary units) Flux (arbitrary units) observations Colors  3.5 years covered Velocity (km/s) Velocity (km/s) =23057.543Å, =5.411 eV, log(gf)=-4.311  =23097.094Å, =1.476 eV, log(gf)=-4.195

  30. CO lines comparison to Wallace & Hinkle, 1996 Line asymmetries and shifts of few km/s. RHD simulation good for high  but no good for lower  Flux (arbitrary units) Flux (arbitrary units) Colors  3.5 years covered observations Velocity (km/s) Velocity (km/s) =23057.543Å, =5.411 eV, log(gf)=-4.311  =23097.094Å, =1.476 eV, log(gf)=-4.195

  31. Ti I line at 6261.11 Å - 1 • Ori (Gray, 2008) FWHM (km/s) 6262 Simulation - period covered 550 days with a time-step of 23 days Variations in velocity! Variations in the positions of the lines and their depths in Gray (2008), as already pointed out by Josselin & Plez 2007!!!!!!, and in RHD simulation =6261.11Å, =3.430 eV, log(gf)=-5.735

  32. Ti I line at 6261.11 Å - 2 • shapes at 1km/s level • shifts much larger than shape variations • The predominant shape is a reversed ”C” Time covered = 1.5 y • Ori (Gray, 2008) Velocity (km/s)

  33. Summary • RHD simulations are in qualitative agreement on the velocity amplitude with respect to the observations • No need for macro- turbulence • Velocity correction due to the convection • Bisector predominant shape is a reversed ”C” in accord with the observations

  34. Out line • RSG stars • The modeller's point of view • The virtual observer’s point of view • Spectroscopy • Interferometry • Conclusions et perspectives

  35. Interferometry IONIC filter FLUOR filters Water CO CN Global spectrum

  36. Intensity profiles and limb-darkening - 1 Angular Angular intensity dispersion is larger than the temporal ones Temporal Median p/R

  37. Intensity profiles and limb-darkening - 2 Claret LD law (2000) with new coefficients (blue) Claret LD law with ATLAS9 3500K,log(g)=0, solar metallicity (green) Modification of LD law by Ludwig & Beckers (2008) (red) RHD snapshot p/R cycles/R

  38. Numerical resolution and visibility maps • Small bright artificial patches (few pixels wide) • Median smoothing applied • Difference at 7th lobe (0.035 Rsun-1, i.e. 28 Rsun3.3 pixel) No smoothing smoothing cycles/Rsun

  39. Visibility - the first lobe 10% at first null • Dispersion due to large (250-500 Rsun) convective cells • Fluctuations are 10% at 0.006 Rsun-1 (first null point)  additional uncertainty for radius measurement! • No clear distinction between angular and temporal fluctuations Angular synthetic vis H band LD UD of 16mas at 173 pc (70 Rsun) Temporal fluctuations Angular fluctuations cycles/Rsun cycles/Rsun

  40. Visibility - the second, third and fourth lobes • Clear deviation from circular symmetry. Signal higher than UD or LD predictions!!! • Scatter becomes larger with spatial frequencies • Signature of the characteristic size of convective cells H band LD UD of 16 mas at 173 pc (70 Rsun) cycles/Rsun 120 Rsun (15% R) 70 Rsun (8% R) 50 Rsun (6% R)

  41. Visibility - the second, third and fourth lobes • How to detect this with today interferometer: • Searching for angular fluctuations using Earth rotation (1 night, same configuration) • Looking for temporal fluctuations (1 night, same configuration at two epochs) 10% Temporal fluctuations Angular fluctuations Vis<10-14% Vis<2-7% Vis<6-10%

  42. Comparison to observations: Ori (Haubois et al. 2006) in IONIC • First data at high spatial frequency • Data from lower to higher frequency explained with one model! • Characterization of the convection size.  Ori covered by cells of 50-120 Rsun • More measure at 20-25 arcsec-1 for signature of large cell Spatial frequency Squared Visibility UD of 43.65 mas   44.6 mas at 174.3 pc

  43. Comparison to observations: Ori (Perrin et al. 2004) in K222 • Confirmation in the K band: presence of cells of 50 to 120 Rsun • Measure at 20 to 23 arcsec-1explained cells of 200 Rsun Spatial frequency Visibility UD of 43.65 mas Linear LD of 43.64 mas UD of 43.65 mas   43.6 mas at 179 pc

  44. Importance of high spectral resolution - 1 • Variation of the interferometric data between different spectral features, and between features and continuum Chiavassa et al., 2007 (SF2A)

  45. Importance of high spectral resolution - 2 • The visibility is wavelength dependent! • It is crucial to have high spectral resolution • H band is a good target wavelength   45 mas at 173.5 pc AMBER spectral resolution of 1500 Resolution of 12000

  46. Comparison to observations:Mu Cep (Perrin et al. 2005) in K band K203 K215 • RHD model cannot fit all the data with one model! • Not even changing cells distribution <2%   15.8 mas at 490 pc K222 Spatial frequency K239

  47. Closure phases Structures of 80 Rsun • Commonly non zero or ±  surface inhomogeneities • Wavelength dependent • Necessary to observe at high spatial frequencies • H band has larger dispersion IONIC Closure Phase (degree) K222 Max baseline (m) Structures of 50 Rsun

  48. Summary • Average limb-darkening profile • Convection-related surface structures cause visibility fluctuations that: • Add uncertainty on radius measurement • Clearly deviate from circular symmetry at high frequency •  Ori is covered by cells of 50-120 Rsun • Importance of high spectral resolution to characterize the convection pattern

  49. Out line • RSG stars • The modeller's point of view • The virtual observer’s point of view • Spectroscopy • Interferometry • Conclusions et perspectives

  50. Conclusions - 1 • The convection pattern in RSGs is wavelength dependent. Few large (400-500 Rsun) convective cells in the IR with a lifetime of years and complex pattern in the optical. • RHD simulations have been compared to observations: • Qualitative agreement on the velocity amplitude • No need for macro-turbulence • Reverse-”C” shape, line shifts and asymmetries without using or macro-turbulence • Detection of convection cells on Ori from interferometric data

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