language : i) Cross-correlation between the object spectrum and a template spectrum in direct space, ii). Cross-correlation ... done for cool M stars. Tentative ...
SF2A 2008 C. Charbonnel, F. Combes and R. Samadi (eds)
RADIAL VELOCITIES WITH THE GAIA RVS SPECTROMETER Viala, Y.P. 1 , Blomme, R. 2 , Damerdji, Y. 3 , Delle Luche, C.1 , Fr´emat, Y.2 , Gosset, E.3 , Jonckheere, A.2 , Katz, D.1 , Martayan, C.2 , Morel, T.3 , Poels, J.3 and Royer, F.1 Abstract. Four different method are used to derive radial velocities from spectra observed by the Gaia Radial Velocity Spectrometer (RVS). They are briefly presented here together with very preliminary results.
1
Introduction
The main aim of the Gaia Radial Velocity Spectrometer (RVS) is to determine the radial velocities of nearly 100 to 200 millions of stars, with an expected accuracy of 1 km/s up to magnitude V = 13 and 15 km/s down to V = 16. These data will be a very useful tool for kinematics and dynamics studies of our Galaxy. The Gaia data will be processed and analyzed by an international consortium (DPAC) including ESA and european institutes participating to the mission (Mignard & Drimmel 2007). Within DPAC nine coordination units CU have in charge a specific scientific or management problem. The processing of spectroscopic data provided by the RVS is devoted to CU6. The aim of this paper is to briefly present the work done within the development unit (DU) ”Single transit analysis (STA)” in charge of analysing the data obtained during a unique transit of an object through the RVS field of view. 2
Radial velocity determination of single stars during a single transit
Deriving radial velocities of the observed object is an important task of DU STA. We restrict here to radial velocity determination of single stars. Four different algorithms have been developped using Java programming language : i) Cross-correlation between the object spectrum and a template spectrum in direct space, ii) Cross-correlation between the object spectrum and a template spectrum in Fourier space, iii)Cross-correlation between the object spectrum and a template spectrum in Fourier space using the Chelli’s method (Chelli 2000), iv) Method of minimum distance between the object spectrum and a series of templates. A detailed escription of these methods can be found in (Viala et al. 2007). For a given set of astrophysical parameters/magnitude, Monte-Carlo simulations (provided by CU2) led to 1000 spectra differing only by noise realisation but all shifted by 20 km/s. Radial velocities from the series of spectra were derived by the 4 algorithms. As an example, figure 1 shows histograms of the radial velocities for solar type stars of magnitude 8.6, 10.6 and 12.6. The mean value of the distribution slighly differ from 20 km/s : this small bias is due to different slopes of the continuum between the object and the template spectrum. The dispersion of the distribution gives the error on the radial velocity determination. Preliminary error derivations are listed in table 1 for several spectral types. 3
Conclusion
For a single transit and for the three methods discussed, radial velocities can be determined with an fairly good accuracy in the range 1 to 8 km/s down to magnitude GRV S ≤ 14 for F-G-K spectral types. Accuracies and magnitude limit are much less good for hotter stars (Spectral types O, B and A). Tests have not yet been done for cool M stars. Tentative determination of the projected rotational velocities, using the three algorithms developped within DU STA is planned for a near future. 1 2 3
Observatoire de Paris, GEPI, 92195 Meudon Cedex Observatoire Royal de Belgique, Avenue circulaire 3, B 1180 Uccle(Bruxelles) Institut d’Astrophysique et de Geophysique, Universite de Liege, Allee du 6 aout, B-4000 Liege c Soci´
et´ e Francaise d’Astronomie et d’Astrophysique (SF2A) 2008
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SF2A 2008 40
200 = 20.15 +- 0.04 sigvr = 0.73 +- 0.04
CC-Dir
30 20
100
10
50
0 18 50
19
40
20
21
22
= 19.64 +- 0.04 sigma = 0.63 +- 0.04
CC-Fou
200 = 29.35 +- 0.09 sigvr = 2.2 +- 0.1
CC-Dir
150
= 29.35 +- 0.09 sigvr = 2.2 +- 0.1
CC-Dir
150 100 50
0 22 200
23
24
25
26
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29
30
31
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= 29.15 +- 0.09 sigma = 2.4 +- 0.1
CC-Fou
150
33
0 22 200
23
24
25
26
27
28
29
30
31
32
150
33
34
35
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= 29.15 +- 0.09 sigma = 2.4 +- 0.1
CC-Fou
30 100
100
50
50
20 10 0 18 20
19
20
21
Chelli
15
22
0 22 100
23
24
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Chelli
= 22.1 +- 0.1 sigvr = 2.0 +- 0.1
10
34
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0 22 100
23
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Chelli
= 30.1 +- 0.2 sigvr = 5.5 +- 0.2
50
34
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38
= 30.1 +- 0.2 sigvr = 5.5 +- 0.2
50
5 0 18 40
19
20
21
22
30
23
24
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26
= 20.08 +- 0.04 sigvr = 0.71 +- 0.04
Minimum distance
0 15 200 150
20
100
10
50
0
18
19
20
21
20
22
0
25
30
35
40
45
= 29.28 +- 0.09 sigvr = 2.2 +- 0.1
Minimum distance
0 15 200
20
25
30
35
150
40
45
= 29.28 +- 0.09 sigvr = 2.2 +- 0.1
Minimum distance
100 50
22
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Fig. 1. Histograms derived radial velocities by the 4 algorithms for a G5V star of RVS magnitude 8.6, 10.6 and 12.6 Table 1. Errors from Monte Carlo simulations on radial velocity derivation for single stars of various spectral types
Sp. type
Tef f
logg
Fe/H
K5V
4000 K
4.0
0.0
G5V
5500 K
4.0
0.0
F5V
7500 K
4.0
0.0
A5V
10000 K
4.0
0.0
B2V
20000 K
4.0
0.0
B0V
30000 K
4.0
0.0
O6V
39000 K
4.0
0.0
RVS magnitude 8.7 12.7 8.6 12.6 8.2 12.2 7.5 11.5 6.8 10.8 6.4 9.9 6.4
CCDir 0.63 7.1 0.73 7.9 0.87 8.6 0.94 11.1 3.0 31.9 2.7 33.5 4.1
error on vrad in km/s CCFou Chelli MinDist 0.63 1.8 0.62 7.5 22.2 7.4 0.63 2.0 0.71 8.1 26.6 8.1 0.85 3.7 0.86 8.8 46.2 8.5 0.92 5.9 0.96 12.9 46.2 10.6 3.1 15.5 2.4 33.7 315 24.8 2.8 17.0 2.3 18.3 204 28.9 0.5 14.5 53.0
References Chelli, A. 2000, AA, 358, L59 Mignard, F., & Drimmel, R. 2007, ESA Note, GAIA-CD-SP-DPAC-FM-030-2 Viala, Y., Blomme, R., Dammerdji, Y., et al. 2007, ESA Note, GAIA-C6-SP-OPM-YV-004-1 Viala, Y., Blomme, R., Dammerdji, Y., et al. 2008, ESA Note, GAIA-C6-SP-OPM-YV-002-3
