1 / 24

6dFGS data quality: comparison of pipeline and IRAF redshifts

6dFGS data quality: comparison of pipeline and IRAF redshifts. Lesa Moore Macquarie University AAO 6dF Workshop 2005. Outline. Spectral reduction and S/N Wavelength calibration Cross-correlation redshift agreement Quality measures – S/N, Q, r Repeatability Final uncertainties

yuma
Download Presentation

6dFGS data quality: comparison of pipeline and IRAF redshifts

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. 6dFGS data quality:comparison of pipeline and IRAF redshifts Lesa Moore Macquarie University AAO 6dF Workshop 2005

  2. Outline • Spectral reduction and S/N • Wavelength calibration • Cross-correlation redshift agreement • Quality measures – S/N, Q, r • Repeatability • Final uncertainties • Based on comparisons between IRAF … and … 6dFDR/RUNZ processing

  3. Data • Three fields studied (A, B and C) with repeat observations of the B and C fields: • A: Mar 16 2002, reflection gratings • B1: Sep 9 2002, reflection gratings • B2: Sep 29 2003, VPH gratings • C1: Sep 29 2002, VPH gratings • C2: Sep 18 2003, VPH gratings

  4. Method • 6dFDR on separate V and R spectra • 6dFDR line lists • RUNZ on spliced spectra • IRAF dofibers on separate V and R spectra • My own line lists • IRAF xcsao on spliced spectra • Batch mode processing, no heliocentric correction in either case

  5. Spectral Reduction • 6dFDR reduction • Sometimes requires FIT rather than TRAM extraction (slower) • Sometimes requires FLUX WEIGHTING option turned off

  6. Signal to Noise Cross-processed Pipeline and IRAF reductions about equal VPH data superior to reflection grating data (figures from 6dFDR/RUNZ)

  7. Line lists and l calibration • Blue (V) data original line list had 14 lines • 6dFDR typically locates 12 • Software throws away 2 worst-fitting (leaves 10) • For red (R) data • Line list omitted strong Ne line at 7032.41 Å • Arc spectra deficient of lines redward of 7500 Å (does not affect cross-correlation) • Found 2nd order line from Hg at ~8092 Å

  8. l Calibration Test • Field C1 VPH reduced without sky subtraction • Sky lines measured • 6dFDR results (±0.4 Å) equal to or superior to IRAF

  9. Cross-correlation • An earlier version of RUNZ at Epping was applying the heliocentric correction incorrectly • RUNZ confused by noise in low S/N spectra • Spliced spectra much more reliable than separate R and V

  10. Redshift Agreement • Agreement if • |Dz| ≤ 0.0005 • |Dcz| ≤ 150 km/s • Overall agreement 81% for 294 galaxies in 3 fields • Could still both be wrong • need to check by eye

  11. Quality Measures • Compared this redshift agreement with: • S/N • RUNZ Q-ranking • Cross-correlation r-values as obtained from pipeline processing

  12. S/N • No strong correspondence between redshift agreement and S/N in separate R and V spectra

  13. Q-rankings • Large scatter even with high Q } 294

  14. Q-rankings • Around half the “disagrees” have Q of 3, 4, or 5 } 294

  15. Q-rankings • Around half the “disagrees” have Q of 3, 4, or 5 • Q=3 meant to imply 75% confidence (only 60% agree) } 294

  16. Cross-correlation r-value • R-value is a much moreuseful indicator of redshift reliability than Q-ranking • 84% of disagrees have r<6 • 27 of 33 disagrees with Q=3,4,5 have r<6 • 72% of agrees have r>6

  17. SIMBAD-RUNZ difference vs. Q-ranking • Q – rankings of 3, 4, 5 show large spread of error values (4, 14, 29 data points respectively) • Have applied heliocentric correction this time • Note bias towards high-q results

  18. SIMBAD-RUNZ difference vs. R-value • Differences scale inversely with r-values • St dev: sz = 0.00012, skm/s = 52 km/s (based on 34 galaxies whose redshift agreement meets criterion of |Dcz| ≤ 150 km/s)

  19. Repeatability • End columns are large discrepancies • All r>6 results lie within |Dz| ≤ 0.001 • Overall st.dev. sDz = 0.00033 • sDkm/s = 98 km/s

  20. Final uncertainties • Notes • 1. Based on 0.4 Å at 4000 Å • 2. Mean of “verr” from RUNZ (278 galaxies in total, 190 with r>6, possibly over-stated) • 3. 1/√2 * st. dev.(Dz) of repeat 6dF observations (125 galaxies in total, 81 with r>6) • 4. Added in quadrature • kms/s = z * 300,000 assumed in all cases

  21. Final uncertainties • Notes • 1. Based on 0.4 Å at 4000 Å • 2. Mean of “verr” from RUNZ (possibly over-stated) • 3. 1/√2 * st. dev.(Dz) • 4. Added in quadrature, final results rounded to one significant figure • kms/s = z * 300,000 assumed in all cases

  22. Summary • S/N superior with VPH gratings • RUNZ q-ranking not reliable indicator of z quality • Redshift agreement (IRAF-RUNZ) scales strongly with cross-correlation r-value • Small uncertainty in l calibration test • Larger uncertainties in cross-correlation and repeatability tests • Total uncertainties: • 100 km/s general uncertainty • 70 km/s uncertainty for r>6 redshifts

  23. Thanks • Macquarie University • Anglo-Australian Observatory • Wide-Field Astronomy Unit, Edinburgh • Supervisors: Quentin Parker (MU/AAO), Will Saunders (AAO) • 6df Galaxy Survey Team (37 members) • References • The 6dF Galaxy Survey: samples, observational techniques and the first data release, MNRAS, 355, 747-763 (2004) • This research has made use of the SIMBAD database, operated at CDS, Strasbourg, France

More Related