1. Spectroscopic Data ASTR 3010 Lecture 15 Textbook Ch.11

2. Spectroscopic Measurement

3. Schematic Diagram of a Typical Spectroscopic Data

4. Only Readout the relevant portion of CCD array Spectroscopic data are typically long and slender. Spectroscopic data are typically long and slender. to save the readout time and storage space…

5. Actual Spectroscopic Data Similar to Imaging Data, a similar set of calibration images is obtained for spectroscopic observation  same pre-processing!! Similar to Imaging Data, a similar set of calibration images is obtained for spectroscopic observation  same pre-processing!! o over-scan correction o trimming o bad-pixel correction o cosmic ray hits removal o zero correction o dark correction o flat-fielding

6. Unique spectroscopic calibration data Unlike imaging observations, two additional kinds of calibration data are obtained for spectroscopic observations. Unlike imaging observations, two additional kinds of calibration data are obtained for spectroscopic observations. o arc images (wavelength correction) o smooth spectrum standards (telluric feature correction) o (and possibly flux standard stars = standard stars in imaging)

7. Steps of spectroscopic data reduction Array pre-processing Spectrum Extraction Wavelength Calibration Telluric Correction Interpretation of Spectra bad pixel, bias, over-scan, trim, zero, flat-fielding find  trace  extract  normalize using arc images (e.g., gas emission lines) using stars with known smooth spectra line width measurement, T eff, [Z/H], vsini, etc.

8. Extraction of Spectra finding the aperture and defining the sky regions  apfind & apedit words in green denote corresponding IRAF commands for the task

9. spectral aperture is not always a horizontal line! need to trace the aperture along the dispersion axis  aptrace

10. Wavelength calibration using Arc images Excited lines from a combination of noble gases (He, Ne, Ar, Xe, Th, etc.) Excited lines from a combination of noble gases (He, Ne, Ar, Xe, Th, etc.) using arc images, you can convert pixel numbers to wavelength! identify

11. How do we extract (find and trace) arc spectra? or very faint objects? or very faint objects? Use well exposed bright star spectrum as a reference! Use well exposed bright star spectrum as a reference!

12. Normalization or Flux Calibration continuum or splot sensfunc and calibrate continuum

13. Telluric Correction Telluric standard stars : stars with no (or very little) spectral line feature. low metallicity stars, white dwarfs, fast rotating stars low metallicity stars, white dwarfs, fast rotating stars telluric

14. Plotting the extracted spectra and … splot  display the extracted spectrum and do simple operations on the spectrum such as continuum normalization and equivalent width measurements. ‘h’ + ‘k’ EW fit with A Gaussian to continuum=1

15. Equivalent Width Quantitative indicator of the strength of a spectral feature Quantitative indicator of the strength of a spectral feature EW = area of the spectral feature EW = area of the spectral feature 1.0 0.0 area = area EW  unit is the wavelength unit of the spectrum

16. One caveat in spectroscopic pre-processing… Flat images… flat images sometime taken w/wo the dispersing element. Which one is better? Is only one kind useful?

17. Flats in spectroscopic data this spectrum is a combination of the above detector flat + spectral response of the system. Flat-fielding is to remove the pixel-to-pixel sensitivity variation! Other gradual, global variation can be taken out later.

18. In summary… Important Concepts Structure of the spectroscopic data Steps of spectroscopic reduction Important Terms aperture tracing telluric correction equivalent width good manual h h h h h tttt tttt pppp :::: //// //// iiii rrrr aaaa ffff.... nnnn oooo aaaa oooo.... eeee dddd uuuu //// iiii rrrr aaaa ffff //// ffff tttt pppp //// iiii rrrr aaaa ffff //// dddd oooo cccc ssss //// ssss pppp eeee cccc tttt.... pppp ssss.... ZZZZChapter/sections covered in this lecture : 11.6