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Spectroscopy – The Analysis of Spectral Line Shapes The detailed analysis of the shapes of spectral lines can give you information on: 1. Differential rotation in stars 2. The convection pattern on the surface of the star 3. The location of spots on the surface of stars 4. Stellar oscillations 5. etc, etc. Basic tools for line shape analysis: 1. The Fourier transform 2. Line bisectors Both pioneered by David Gray To derive reliable information about the line shapes requires high resolution and high signal-to-noise ratios: • R = l/dl ≥ 100.000 • S/N > 200-300 Fourier Transform of the Rotation Profile David Gray pioneered using the Fourier transform of spectral lines to derive information from the shapes. ∞ i(f) = I(l)e2pilf ∫ –∞ dl Where I(l) is the intensity profile (absorption line) and frequency f is in units of cycles/Å or cycles/pixel (detector units) Because of the inverse relationship between normal and Fourier space (narrow lines translates into wide features in the Fourier domain), the Fourier transform is a sensitive measure of subtle shapes in the line profile. It is also good for measuring rotation profiles. The Instrumental Profile The observed profile is the spectral line profile of the star convolved with the instrumental profile of the spectrogaph, i(l) What is an instrumental profile (IP)?: Consider a monochromatic beam of light (delta function) Perfect spectrograph A real spectrograph If the IP of the instrument is asymmetric, then this can seriously alter the shape of the observed line profile No problem with this IP Problems for line shape measurements It is important to measure the IP of an instrument if you are making line shape measurements If D(Dl) is the observed profile (your data) then D(Dl) = H(Dl)*G(Dl)*I(Dl) Where: D = observed data H = intrinsic spectral line G = Broadening function (rotation * macroturbulence) I = Instrumental profile * = convolution In Fourier space: d(s) = h(s)g(s)i(s) You can either include the instrumental response, I, in the modeling, or deconvolve it from the observed profile. Fourier Transform of the Rotation Profile Fourier Transform of the Rotation Profile The Fourier transform of the rotational profile has zeros which move to lower frequencies as the rotation rate increases (i.e. wider profile in wavelength coordinates means narrower profile in frequency space). Limb Darkening Limb darkening shifts the zero to higher frequency Limb Darkening The limb of the star is darker so these contribute less to the observed profile. You thus see more of regions of the star that have slower rotation rate. So the spectral line should look like a more slowly rotating star, thus the first zero of the transform should move to lower frequencies Limb Darkening Ic/Ic0 = (1 – e) + e cosq Effects of Differential Rotation on Line shapes The sun differentially rotates with equatorial acceleration. The equator rotational period is about 24 days, for the pole it is about 30 days. Differential rotation can be quantified by: w = w0 + w2 sin2f + w4sin4f a = w2/(w0 + w2) Solar case a = 0.19 + → equator rotates faster – → pole rotates faster f is the latitude Differential rotation parameter Effects of Differential Rotation on Line shapes Effects of Differential Rotation on Line shapes The inclination of the star has an effect on the Fourier transform of the differential profile Differential Rotation in A stars In 1977 Gray looked for differential rotation in a sample of A-type star and found none. This is not surprising since we think that the presence of a convection zone is needed for DR and A-type stars have a radiative envelope. Differential Rotation in A stars Gray found two strange stars. g Boo has a weak first sidelobe and no second side lobe. g Her has no sidelobes at all. This may be the effects of stellar pulsations. Differential Rotation in F stars In 1982 Gray looked for differential rotation in a sample of F-type star and concluded that there was no differential rotation. Spot activity on F-type stars is not seen, but they do have a convection zone so DR is possible. Differential Rotation in F stars y Cap a=0 a = 0.25 However, in 2003 Reiners et al. found evidence for differential rotation in F-stars Velocity Fields in Stars Early on it was realized that the observed shapes of spectral lines indicated a velocity broadening in the photosphere termed „turbulence“ by Rosseland. A theoretical line profile with thermal broadening alone will not reproduce the observed spectral line profile. This macroturbulent velocity broadening is direct evidence of convective motions in the photospheres of stars From Velocity to Spectrum N(v)dv = 1 e–(v/v0)2dv p½v0 N(v)dv is the fraction of material having velocities in the range v → v + dv and v is allowed only on stellar radii. The projection of velocities along the line of sight = b0 cos q b = l v0cos q c 2 Dl 2 1 Dl 1 = p½b cosq exp [–( b0cosq ) dDl N(Dl)dl = ½ exp [ –( b ) p b 0 Dl = l cos q c [ [ Note that b, the width parameter, is a function of q, b0 is constant. At disk center N(l) reflects N(v) directly, but way from the center the Doppler distribution becomes narrower. At the limb N(Dl) is a delta function. Including Macroturbulence in Spectra The observed spectra (ignoring other broadening mechanisms for now) is the intensity profile convolved with the macroturbulent profile: In = In0 * Q(Dl) In0 is the unbroadened profile and Q(Dl) is the macroturbulent velocity distribution. What do we use for Q? The Radial-Tangential Prescription from Gray We could just use a Gaussian distribution of radial components of the velocity field (up and down motion), but this is not realistic: Horizontal motion to lane Convection zone Rising hot material Cool, sinking intergranule lane If you included only a distribution of up and down velocities, at the limb these would not alter the line profile at the limb since the motion would not be in the radial direction. The horizontal motion would contribute at the limb Radial motion at disk center → main contrbution at disk center Tangential motion at disk center → main contribution at limb The Radial-Tangential Prescription from Gray Assume that a certain fraction of the stellar surface, AT, has tangential motion, and the rest, AR, radial motion Q(Dl) = ARQR(Dl) + ATQT(Dl) AR –(Dl/z cos q) e = + p½zRcos q R 2 AT e–(Dl/z cos q) p½zTcos q And the observed flux p/2 ∫ QR(Dl)*Insin q cosq dq + Fn = 2pAR 0 p/2 2pAT ∫ QT(Dl)*Insin q cosq dq 0 T 2 The Radial-Tangential Prescription from Gray The R-T prescription produces as slightly different velocity distribution than an isotropic Gaussian. If you want to get more sophisticated you can include temperature differences between the radial and tangential flows. The Effects of Macroturbulence Macro Relative Intensity 10 km/s 5 km/s 2.5 km/s 0 km/s Pixel shift (1 pixel = 0.015 Å) Macroturbulence versus Luminosity Class Macroturbulence increases with luminosity class (decreasing surface gravity) Amplitude Relative Flux The Effects of Macroturbulence Pixel (0.015 Å/pixel) Frequency (c/Å) There is a trade off between rotation and macroturbulent velocities. You can compensate a decrease in rotation by increasing the macroturbulent velocity. At low rotational velocities it is difficult to distinguish the two. Above the red line represents V = 3 km/s, M = 0 km/s. The blue line represents V=0 km/s, and M = 3 km/s. In wavelength space (left) the differences are barely noticeable. In Fourier space (right), the differences are larger. The Effects of Macroturbulence Rotation affects the location of the first zero. Macroturbulence affects the size of the first side lobe and to a lesser extent the main lobe. Sometimes it is very important to measure the rotational velocity accurately. HD 114762 m sin i = 11 MJup Most likely vsini is 0-1 km/s. HD 114762 is an F8 star and the mean rotation of these stars is about 5 km/s. The companion could be a more massive companion, maybe even a late M-dwarf A word of caution about using Fourier transforms If you want to calculate the Fourier transform of the line you have to „cut out“ the line. This is the equivalent of multiplying your data with a box function. In Fourier space this is a sinc function which gets convolved with your broadening function. This changes the FT. → need to apply taper function (bell cosine, etc.) The Funny Shape of the Lines of Vega A clue may be found in the slow projected rotational velocity of Vega, an A0 V star Recall Gravity darkening Von Zeipel law (1924): equator Rotation pole Teff = C g0.25 ,C is a constant Because of gravity darkening and centrifugal force, the equator has lower gravity and a lower temperature. For a star viewed pole on this appears at the limb. Temperature/gravity sensitive weak lines will be stronger at the equator (limb) than at the poles. The Power of Spectral Line Bisectors What is a bisector? Curvature Span Bisectors as a Measure of Granulation Hot rising cell Cool sinking lane Solar Bisector Solar bisectors take on a „C“ shape due to more flux and more area of rising part of convective cells. There is considerable variations with limb angle due to the change of depth of formation and the view angle. The line profiles themselves become shallower and wider towards the limb. Bisectors as a Measure of Granulation The measurement of an individual bisector is very noisy. One should use many lines. These can be from different line strengths as one can „collapse“ them all into one grand mean. Note: this cannot be done in hotter stars the weak lines do not mimic the shape of the top portion of the bisector. Changes in the Granulation Pattern of Dwarfs Changes in the Granulation Supergiants The Granulation and Rotation Boundary Rapid rotation, Inverse „C“ bisectors Slow rotation „C“ shaped bisectors Bisectors as a Measure of Granulation Can get good results using a 4 stream model (Dravins 1989, A&A, 228, 218). These best reproduce hydrodynamic simulations 1. Granule center (rising material) 2. Granules (rising material) 3. Neutral areas (zero velocity) 4. Intergranule lanes (cool sinking material) Each has their own fractional areas An, velocity Vn, and Temperature Tn Constraints: 1. A1 + A2 + A3 + A4 = 1 2. V3 = 0 3. Mass conservation: A1×V1 + A2 ×V2 = A4×V4 Downflow = upflow Best way, is to use numerical hydrodynamic simulations Bisectors as a Measure of Granulation Examples of 4 component fits for stars from Dravins (1989) Rotation amplifies the Bisector span (Gray 1986): Using Bisectors to Study Variability The Effects of Stellar Pulsations Variations of Bisectors with Pulsations The 51 Peg Controversy Gray & Hatzes Gray reported bisector variations of 51 Peg with the same period as the planet. Gray & Hatzes modeled these with nonradial pulsations A beautiful paper that was completely wrong. Hatzes et al. More and better bisector data for 51 Peg showed that the Gray measurements were probably wrong. 51 Peg has a planet! Bisector Variations due to Spots Spot Pattern Changes in Radial Velocity due to changing shapes Star Patches Bisectors Bisector span Star Patches DT = 300 K Compared to DT = 2000 K for sunspots Spots vs. Planets HD 166435 Radial Velocity Radial Velocity Ca II Brightness Color Correlation of bisector span with radial velocity for HD 166435 Disk Integration Mechanics Cell i,j q 1. Divide the star into an x,y grid 2. At each cell calculate the limb angle q 3. Take the appropriate limb angle intrinsic line profile from model atmospheres, or just apply limb darkening law to a line profile or even a Gaussian profile (the poor person‘s way) 4. Calculate the radial velocity using the desired vsini. Include differential rotation if desired. Doppler shift your line profile 5. Use a random number generator to calculate the radial and tangential value of the macro-turbulent velocity with maximum value x. Apply additional Doppler shift due to the turbulent velocity 6. If there is a spot, you can scale the flux. If there are pulsations you can add velocity field of star. 7. Can add convective velocities/fluxes 8. Take area of cell and multiply it by the projected area (cos q) 9. Go to next i,j cell 10. Add all profiles from all cells 11. Normalize by the continuum 12. Check to make sure line behaves with vsin macro-turbulence. Make sure equivalent width is conserved.