1 / 15

The accuracy of Giraffe measurements of radial velocity in young clusters

The accuracy of Giraffe measurements of radial velocity in young clusters. Richard Jackson – Keele University in collaboration with Rob Jeffries and Amy Dobson - Keele Jim Lewis and Sergey Koposov - Casu. The accuracy of Giraffe measurements of

marlis
Download Presentation

The accuracy of Giraffe measurements of radial velocity in young clusters

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. The accuracy of Giraffe measurements of radial velocity in young clusters Richard Jackson – Keele University in collaboration with Rob Jeffries and Amy Dobson - Keele Jim Lewis and Sergey Koposov - Casu

  2. The accuracy of Giraffe measurements of radial velocity in young clusters Gamma Velorum cluster To study cluster kinematic substructure We need to know • Typical uncertainty in RV (using MAD) • Tail of the uncertainty distribution in RV (3) Any bias in RV with SNR and/or Teff Lithium rich Jeffries, Jackson, Cottaar et al. 2013 One distribution or two? ? Frequency RV (km/s)

  3. Empirical “Poisson” uncertainty in RV - for short term repeats Spectra vs SNR and vsini Derive a normalised uncertainty -independent of SNR and vsini Measured uncertainty of repeat observations

  4. Empirical “Poisson” uncertainty in RV - for short term repeats Spectra vs SNR and vsini Reduce to normalised uncertainty independent of SNR and vsini Measured uncertainty of repeat observations Normalised uncertainty

  5. Empirical “Poisson” uncertainty in RV - for short term repeats 8463 repeats in 8 clusters Gama2Vel Cha_I rho_oph NGC2264 NGC2547 NGC2516 NGC6633 IC4665 + field stars (Corot sample) Fix C = 26.5 Fix Bav=5.7 RV/2 x SNR/(1+vsini2/C2) RV/2 x SNR Uncertainty normalised to Find B(Teff) RV/2 x SNR/(1+vsini2/C2) where B varies with Teff and B/C2 constant logTeff

  6. Uncertainty in wavelength calibration - for long term repeats Change day 1 to 2 plate 1 Change day 1 to 2 plate 2 Simcal 0.22 & 0.23 Uncertainty 0.08 & 0.09 Simcal -0.10 & -0.17 Uncertainty 0.15 & 0.08 Change day 2 to 3 plate 1 Change day 2 to 3 plate 2

  7. Uncertainty in wavelength calibration - for long term repeats Simcal 0.22 & 0.23 Uncertainty 0.08 & 0.09 Change day 1 to 2 plate 1 Change day 1 to 2 plate 2 Simcal -0.10 & -0.17 Uncertainty 0.15 & 0.08 Change day 2 to 3 plate 1 Change day 2 to 3 plate 2 SIMCAL offset in wavelength scale varies through night - In similar way for all filters. Appears to be a “mechanical offset” - independent of SNR & vsini

  8. Total uncertainty in RV - for long term repeats between OBs Normalised uncertainty Poisson uncertainty (2 spectra per OB) Total uncertainty between OBs (2047 repeats) Poisson term A = 0.28 km/s B = 5.70 km/s C = 26.5 km/s Cumulative probability Wavelength term Normalised uncertainty

  9. Total uncertainty in RV - for long term repeats between OBs Normalised uncertainty Poisson uncertainty (2 spectra per OB) Total uncertainty between OBs 2047 repeats Poisson term A = 0.28 km/s B = 5.70 km/s C = 26.5 km/s Cumulative probability Wavelength term Tail of empirical uncertainty between OBs Fraction of population Normalised uncertainty Tail of Poisson uncertainty RV / (normalisation factor)

  10. Total uncertainty in RV - for long term repeats between OBs Normalised uncertainty Poisson uncertainty (2 spectra per OB) Total uncertainty between OBs 2047 repeats Poisson term A = 0.28 km/s B = 5.70 km/s C = 26.5 km/s Cumulative probability Wavelength term Normalised uncertainty Comparison empirical and Velclass uncertainties -Velclass uncertainties are ~ 2 higher.

  11. Absolute accuracy of RVs observed in HR10, HR15N and HR21 23 standards Standard stars RV of standards from Soubiran et al. 2013 rms uncertainty 0.04km/s

  12. Absolute accuracy of RVs observed in HR10, HR15N and HR21 23 standards Standard stars Field stars RV = 0.32 km/s RV = 0.09 km/s RV of standards from Soubiran et al. 2013 rms uncertainty 0.04km/s Data set GE_SD_CR ~1500 Corot targets

  13. Variation in absolute RV between HR10 and HR21 filters Apparent bias in Velclass RVs (for HR21) a function of SNR and/or Teff?

  14. Possible causes of difference in RV measured by Velclass and CCF method Target HIP066032 (Spt K2) RV template hi-res synthetic 50-4.0-0.0 (COELHO 2005) Velclass method CCF method Measured difference in RV Differences in templates used

  15. The accuracy of Giraffe measurements of radial velocity in young clusters • Comparison of repeat measurements of RV in young clusters shows that the measurement uncertainty can be normalised to a simple function of SNR and vsini with a weaker dependence stellar properties. • The measurement uncertainty at higher SNR is dominated by a fixed uncertainty of ~0.28km/s due to changes in wavelength calibration between setups. • Analysis of RVs of standard stars shows a bias of ~0.4km/s for measurements made using HR21 (but no significant bias for HR10 and HR15N). The most likely cause is a mismatch between target spectra and synthetic RV templates. • Where possible stellar properties used to select RV templates should be fixed for each target - based on the best available estimates of Teff, logG and Fe/H. • Following the planned change to GAIA/Phoenix synthetic spectra revised RVs should be re-analysed for evidence of bias with Teffand/or SNR in all filters.

More Related