S PECTRAL LINE ANALYSIS : LOG G Giovanni Catanzaro INAF - Osservatorio Astrofisico di Catania 9 april 2013 Spring School of Spectroscopic Data Analyses.

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Presentation transcript:

S PECTRAL LINE ANALYSIS : LOG G Giovanni Catanzaro INAF - Osservatorio Astrofisico di Catania 9 april 2013 Spring School of Spectroscopic Data Analyses 8-12 April 2013 Astronomical Institute of the University of Wroclaw Wroclaw, Poland Spring School of Data Analyses 1

9 april 2013 S PECTRAL LINES An absorption line is produced in a stellar spectrum whenever photons of energy E=h =hc/ =E U -E L are absorbed by an atom or ion that jumps from a lower to an upper energy level. Lyman Balmer      = R [ 1/n l 2 – 1 /n u 2 ] R = x Hz Hydrogen Energy Levels Spring School of Data Analyses 2

9 april 2013 S PECTRAL LINES   Hydrogen Energy Levels Spring School of Data Analyses 3  n  excitation potential of the level n   = 10.2 eV Ionization Energy for Hydrogen (n to infinity): I = 13.6 eV (  912 Ǻ) ionization energy

9 april 2013 S PECTRAL LINES The intensity of a spectral line is related to the number of absorbers, i.e. atoms or ions of the given elements at the lower level of the transition. In LTE (Local Thermodynamic Equilibrium) the fraction of ions that can absorb is given by the Saha and Boltzmann equations. Ionization - Saha Excitation - Boltzmann Element abundance Electron pressure  gravity Spring School of Data Analyses 4 temperature

9 april 2013 S PECTRAL LINES Dispersion profile (Lorentzian) There are several mechanisms that broaden a spectral line, which is never a  function (infinitely-narrow feature). 1)Natural atomic absorption 2)Pressure broadening 3)Thermal Doppler broadening 4)Microturbulence 5)Rotation Etc. Gaussian profile Spring School of Data Analyses 5

9 april 2013 Different types of pressure broadening nTypeLines affectedPerturber 2Linear StarkHydrogenProtons,electrons 4Quadratic Stark Lines in hot stars Ions, electrons 6Van der Waals Lines in cool stars Neutral hydrogen Pressure broadening implies a collisional interaction between the atoms absorbing light and other particles: ions, electrons, atoms or molecules (in cool stars). Change in energy of the levels induced by the collisions Spring School of Data Analyses 6

9 april 2013 S PECTRAL LINES Thermal Doppler profiles Dispersion (Lorentzian) profiles “Weak” lines Both broadening mechanisms at work  the line is shaped by the convolution G( )*L( ): “Voigt function” G( )L( ) Spring School of Data Analyses 7

9 april 2013 S PECTRAL LINES Thermal Doppler profiles Dispersion (Lorentzian) profiles “Strong” lines When the line intensity increases (e.g. abundance) the optical depth at the line center becomes high  the line core reaches a minimum level and the wings get broad. These lines are said “saturated”. Strong lines of abundant elements and ions (HI, NaI, MgII, CaI, CaII, etc.) G( ) L( ) Spring School of Data Analyses 8

9 april 2013 S PECTRAL LINES Optical depth. k, l continuum and line absorption coefficients Line transfer equation Source function j emission coefficients normal To observer AA   Star surface Spring School of Data Analyses 9

9 april 2013 S PECTRAL LINES The solution of transfer equation gives the emerging flux (at the top of the atmosphere  =0) as: Numerical solution! E 2 exponential integral of order 2 For To a first, rough approximation: In LTE the source function at  is the Planck function evaluated at T(  )  S is decreasing outwards Spring School of Data Analyses 10

9 april 2013 S PECTRAL LINES The flux at the line center (where l is maximum) comes from the upper atmospheric layers, where the source function is lower. The larger l the smaller x 1 must be to obtain an optical depth  1 x to the star center Spring School of Data Analyses 11

M EASURING THE GRAVITY IN STARS 9 april 2013 In principle we can measure gravity in a direct way: Obtain Mass via spectroscopy and the Doppler effect (binary stars for example) Measure the radius by an independent means (interferometry, lunar occultations, eclipsing binaries) In principle this can only be done for very few stars must rely on spectroscopic determinations Spring School of Data Analyses 12

9 april 2013 Increasing of gravity translates into a compression of the photosphere and therefore in an increase of the pressure Therefore pressure dependences can be translated in gravity dependences Ionization equilibrium P sensitive to damping constant for strong lines P dependence of the linear stark broadening in H Spring School of Data Analyses 13

9 april 2013 The strenght of a spectral line is related to the ratio of the line and continuous absorption coefficients: Rewrite the Saha equation in a more schematic form Include all terms not dependent on pressure Number of atoms/ions in r+1 ionization stages Number of atoms/ions in the r ionization stages Remember also that: Spring School of Data Analyses 14

W EAK LINES ( NO STRONG WINGS ) IN COOL STARS 9 april 2013 Most part of an element in the next higher ionization stage Saha In cool stars H - dominates the opacity of the continuos These lines are insensitive to gravity, but are useful to set the abundance of the element Spring School of Data Analyses 15

W EAK LINES ( NO STRONG WINGS ) IN COOL STARS 9 april 2013 Most part of an element in the same ionization stage Saha Again H - dominates the opacity of the continuos These lines are sensitive to gravity Spring School of Data Analyses 16

9 april 2013 Example: in solar like stars iron is mostly ionized Fe I lines are insensitive to gravity FeII lines are sensitive to gravity Fuhrmann et al. (1997) A&A, 323, 909 log g = 3.58 Procyon Teff = 6500 K Spring School of Data Analyses 17

9 april 2013 B ROAD WINGS OF NEUTRAL LINES IN COOL STARS Van der Waals Quadratic Stark H - dominates the opacity of the continuos Most part of element is ionized Depending of the relative size of damping constants we will have different regimes: from no gravity dependence (  nat dominant) to maximum dependence (van der Waals dominant) Spring School of Data Analyses 18

9 april 2013 HD K0V HD99322 K0III POP-UVES Database Spring School of Data Analyses Cyg - K5V T eff =4500 K logg = Aql – K1III T eff =4520 K logg = 2.65 Courtesy of A. Frasca (Priv. Comm.)

9 april 2013 T eff =7500 K Catanzaro et al (2013), MNRAS, in press HD T eff =7500 ± 180 K log g = 4.00 ± 0.10 Fossati et al (2011) MNRAS, 417, 495 Teff=7150 K, log g = 4.20 Teff=7380 K, log g = 4.08 Teff=7250 K, log g = 4.20 Teff=7670 K, log g = 4.44 Spring School of Data Analyses 20 log g = 2.0 log g = 3.0 log g = 4.0 log g = 5.0

9 april 2013 B ROAD WINGS OF IONIC LINES IN COOL STARS Again, depending we have different regimes: from no gravity dependence (  nat dominant) to maximum dependence (van der Waals dominant) HD Teff=5597 K Log g = 3.97 [Fe/H]=0.10 Vsin i = 4 km/s Ramirez et al., 2007, 465, 271 Log g = 3, 4, 5 Spring School of Data Analyses 21

9 april 2013 B ROAD WINGS OF B ALMER LINES IN HOT STARS Struve (1929): great wings of Balmer lines in early-type stars are due to linear Stark Effect R Distribution of ions gives a non-zero E at the position of the H The resulting splitting of atomic levels can be expressed as the  of the spectral components: Greater compression of the photosphere results in a greater E, so l is proportional to E and than to P e In this stars H absorption dominates k than it is proportional to N H H lines increase in strength toward lower luminosity classes Spring School of Data Analyses 22

9 april 2013 In this case more is the gravity narrow is the line T eff =7000 K T eff =10000 K T eff =25000 K Spring School of Data Analyses 23 log g = 2.0 log g = 3.0 log g = 4.0 log g = 5.0

9 april 2013 Catanzaro et al. (2004), A&A, 425, 641 Leone & Manfre’ (1997), A&A, 320, 257 Influence of chemical composition Spring School of Data Analyses 24

T HE GRAVITY - TEMPERATURE DIAGRAM 9 april 2013 Each curve is computed for a costant iron abundance (fixed using lines not sensitive to g), while varyng the surface gravity for a given temperature (or vice versa) to recover the observed EQWs Spring School of Data Analyses 25

9 april 2013 Lehner et al., 2000, MNRAS, 314, 199 Lyumbikov et al., 2002, MNRAS, 333, 9 Spring School of Data Analyses 26

B ALMER JUMP AS LOG G INDICATOR 9 april 2013 log g = 3.00 log g = 4.00 log g = 5.00 Spring School of Data Analyses 27

9 april 2013 Example:  Boo T eff =7600 K, log g = 3.7 (Ventura et al., 2007, MNRAS, 381, 164) log g = 3.00 log g = 4.40 Spring School of Data Analyses 28

9 april 2013 log g E MPIRICAL INDICATORS : T HE W ILSON -B APPU EFFECT Spring School of Data Analyses 29

9 april 2013 StarTeff (K)log g Arcturus4158 ± ± 0.16  Boo A 5230 ± ± 0.05 Courtesy of Antonio Frasca CaII K line Example: Arcturus (K1.5III) vs  Boo A (G8V) Allende-Prieto, 2004, A&A, 420, 183 Spring School of Data Analyses 30

T HANKS FOR YOUR ATTENTION 9 april 2013 Spring School of Data Analyses 31