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Spectral lines analysis - PowerPoint Presentation

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Spectral lines analysis - PPT Presentation

Rotational velocity and velocity fields Spring School of Spectroscopic Data Analyses 812 April 2013 Astronomical Institute of the University of Wroclaw Wroclaw Poland Giovanni Catanzaro ID: 560844

analyses school data spectroscopic school analyses spectroscopic data 2013 velocity line profile rotational motion lines limb distribution radial star

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Slide1

Spectral lines analysis

Rotational velocity and velocity fields

Spring School of Spectroscopic Data Analyses

8-12 April 2013

Astronomical Institute of the University of Wroclaw

Wroclaw, Poland

Giovanni Catanzaro

INAF - Osservatorio Astrofisico di CataniaSlide2

 

 

 

equator

Projected rotational velocity

09/04/2013

Spectroscopic School of Data Analyses

2

 

Because

the Doppler

effect

we

can

see

only

the component of the

equatorial

velocity

parallel

to the line of

sightSlide3

 

 

 

equator

 

Special case:

i

=90º

All rotational velocity is parallel to line of sight: star

appears

to rotate with

v

eq

09/04/2013

Spectroscopic School of Data Analyses

3Slide4

 

 

equator

 

Special case:

i

=0º

All rotational velocity is perpendicular to line of sight: star appears not rotate

09/04/2013

Spectroscopic School of Data Analyses

4Slide5

Rotation shapes line profile

09/04/2013

Spectroscopic School of Data Analyses

5

Rotational profileSlide6

 

limb darkening

 

Rotational

profile

09/04/2013

Spectroscopic School of Data Analyses

6Slide7

Profile fitting for v sin i

Observed spetrum with several synthetics overimposed. Each synthetic spectrum was computed for different value of rotational velocity.

 

Instrumental profile

 

09/04/2013

Spectroscopic School of Data Analyses

7Slide8

Importance of Resolution

09/04/2013

Spectroscopic School of Data Analyses

8

Example: FeII 5316.615 Å

 

 

T

eff

= 7000 K

Log g = 4.00

HERMES

R = 80000Slide9

Fourier analysis

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Spectroscopic School of Data Analyses

9

~0,007

 Slide10

Limb darkening

Limb darkening shifts the zero to higher frequency

09/04/2013

Spectroscopic School of Data Analyses

10Slide11

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

looks

like

that of a

more slowly rotating star, thus the first zero of the transform

move

to lower frequencies

 

 

09/04/2013

Spectroscopic School of Data Analyses

11Slide12

Velocity fields

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Spectroscopic School of Data Analyses

12

Motions of the photospheric gases introduce Doppler shifts that shape the profiles of most spectral linesTurbulence are non-thermal broadening

We can make two approximations:The size of the turbulent elements is large compared to the unit optical depth Macroturbulent limit

The size

of the turbulent elements

is small

compared to the unit optical

depth

Microturbulent limit

Velocity fields are observed to exist in photospheres oh hot stars as well as cool stars.Slide13

Macroturbulence

Turbulent cells are large enough so that photons remain

trapped in them from the time they are created until they escape from the star

Lines are Doppler broadened: each cell produce a complete spectrum that is displaced by the Doppler shift corresponding to the velocity of the cell.

The observed spectra

is:

I

n

= I

n

0

*

Q(Dl

)

I

n

0

is the unbroadened profile and Q(Dl) is the macroturbulent velocity distribution.What do we use for Q?09/04/2013Spectroscopic School of Data Analyses

13Slide14

Radial-Tangent model

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Spectroscopic School of Data Analyses

14

We could just use a Gaussian

(isotropic) distribution

of radial components of the velocity field (up and down motion), but this is not realistic:

Rising hot material

Cool sinking material

Horizontal

motion

Convection zone

If you included only a distribution of up and down velocities, at the limb these would not alter the line profile

since

the motion would not be in the radial direction. The horizontal motion would contribute at the limb

Radial motion

→ main

contribution

at disk center

Tangential motion

→ main contribution at limbSlide15

09/04/2013

Assume that a certain fraction of the stellar surface, A

T

, has tangential motion, and the rest, A

R

, radial motion

Q

(

Dl

) = A

R

Q

R

(

Dl

) + A

T

Q

T

(

Dl)

Spectroscopic School of Data Analyses

15

The R-T prescription produces

a

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.Slide16

09/04/2013

Macro

10 km/s

5 km/s

2.5 km/s

0 km/s

Pixel shift (1 pixel = 0.015

Å)

Relative Intensity

Effect of Macroturbulence

It does not alter the total absorption of the spectral lines, lines broadened by macroturbulence are also made shallower.

Spectroscopic School of Data Analyses

16Slide17

09/04/2013

At

low rotational velocities it is difficult to distinguish

between

them

:

red

line

is computed for v sini

=

3 km/s,

x

= 0

km/s

blue

line

for v sini

= 0

km/s

and x

= 3 km/s

Relative

Flux

Pixel (0.015

Å/pixel)

Amplitude

Frequency

(c/

Å)

Spectroscopic School of Data Analyses

17

There is a

tradeoff

between rotation and macroturbulent velocities.

You

can

compensate

a

decrease

in

rotation

by

increasing

the

macroturbulent

velocity

.

While

, In

the

wavelength

space

the

differences

are

barely

noticeable

, in

Fourier

space

(

right

),

the

differences

are

larger.Slide18

Example: b

Comae (Gray et al., 1996)09/04/2013

Spectroscopic School of Data Analyses

18

d(

s) individual lines

h(

s

) thermal profile

i(

s

) instrumental profile

d(

s

) a

veraged and divided by

i(s

) Slide19

Microturbulence

09/04/2013

Spectroscopic School of Data Analyses

19

Contrarly to macroturbulence, we deal with microturbulence when turbulent cells have sizes small compared to the mean free path of a photon.In this case the velocity distribution of the cells molds the line profile in the same way the particle distribution does.

 

Line absorption coefficient without microturbulence

Particles velocity distribution (gaussian)

 

The convolution of two gaussian is still a gaussian with a dispersion

parameter given

by:

 

 Slide20

09/04/2013

Spectroscopic School of Data Analyses

20

Landstreet et al., 2009, A&A, 973

Typical values for

x

are 1-2 km s

-1

, small enough if compared to the other components of the line broadening mechanism.

It is a very hard task to attempt the direct measurement of

x

by fitting the line profile. Very high resolution (>10

5

), high SNR spectra and slow rotators stars (a few km s-1) are needed.Slide21

Blackwell diagrams

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Spectroscopic School of Data Analyses

21

1998, A&A, 338, 1041

FeII

CrIISlide22

09/04/2013

Spectroscopic School of Data Analyses

22

Catanzaro & Balona, 2012, MNRAS, 421,1222

Other type of diagram: from a set of spectral lines, we require that the inferred abundance not depend on EW

Example: HD27411, Teff = 7600 ± 150, log g = 4.0

±

0.1

71 lines FeISlide23

09/04/2013

Spectroscopic School of Data Analyses

23

Thanks for your attention