en:praktikum:sternspektren

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en:praktikum:sternspektren [2018/11/06 14:51] – [Radial velocity determination] schaffenrothen:praktikum:sternspektren [2023/09/19 06:49] (current) – rhainich
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 */ */
  
-The aim of this observation is to obtain an overview of different spectral types. Thus, we will give you the coordinates and the apparent magnitude of four stars of different spectral type that are well visible during the night of your observation. /*choose at least one star of each spectral type (O, B, A, F, G, K, M, special classes after consultation) that is well visible ($m_\mathrm{V} \le 6\,$mag)*/ Take spectra of these stars in order to classify them by means of the spectral lines and the shape of the continua. From the deviation of the absorption lines in the spectra from their rest wavelength, you can calculate the radial velocity of the star towards or away from us by using the Doppler effect. /* to find suitable stars, use pages like [[http://simbad.u-strasbg.fr/simbad/|Simbad]] - a help page for the parameter query at Simbad can be found [[en:etc:simbad|here]].*/+The aim of this observation is to obtain an overview of different spectral types. Thus, we will give you the coordinates and the apparent magnitude of four stars of different spectral type that are well visible during the night of your observation. Take spectra of these stars in order to classify them by means of the spectral lines and the shape of the continua.  
 + 
 +/* From the deviation of the absorption lines in the spectra from their rest wavelength, you can calculate the radial velocity of the star towards or away from us by using the Doppler effect.  
 +*/
  
  
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 The scripts needed for the data reduction can be found on the [[en:praktikum:zugang|Laboratory computer]] in the directory ''~/scripts/n1_dados''. The scripts needed for the data reduction can be found on the [[en:praktikum:zugang|Laboratory computer]] in the directory ''~/scripts/n1_dados''.
  
 +
 +{{section>deng:praktikum:a12:python#English&noheader}}
 ==== Selection and inspection of the data ==== ==== Selection and inspection of the data ====
  
-The first tasks are to login to the [[en:praktikum:zugang |Laboratory Computer]] and to copy the observational data (FITS files), including darkframes, and the additional calibration exposures from the directory ''~/data/<date>'' to your own directory ''~/<semester>/<group>''. There are different tools to view the FITS files (two dimensional CCD images or data tables). //ds9// is easy to handle and can be started from the terminal via:+The first tasks are to login to the [[en:praktikum:zugang |Laboratory Computer]] and to copy the observational data (FITS files), including darkframes, and the additional calibration exposures from the directory ''~/data/<date>'' to your own directory ''~/data_reduction/''. There are different tools to view the FITS files (two dimensional CCD images or data tables). //ds9// is easy to handle and can be started from the terminal via:
  
    ds9 filename.fit     ds9 filename.fit 
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 Now run the script by executing: Now run the script by executing:
  
-   ./1_findcaliblines.py+   python 1_findcaliblines.py
  
 Afterwards the following window will be displayed on the screen, showing the mercury and argon emission line spectrum. All lines that were identified by the script are highlighted by a red circle. Now, all lines with known wavelengths need to be  marked. For this task, the above example spectrum can be very useful. The script runs through a list of predefined lines. The wavelength of the current line is displayed in the upper part of the window. The line corresponding to this wavelength can now easily marked by clicking into the corresponding red circle with the left mouse button. This circle should now appear blue and the corresponding wavelength is written next to the line peak (see below). If a wavelength is displayed that does not correspond to any of the highlighted lines, this wavelength can be skipped with a right click. At least four lines need to be marked to facilitate a successful wavelength calibration. If all useful lines are marked, this procedure can be completed by pressing the ''Q key'' on the keyboard.  Afterwards the following window will be displayed on the screen, showing the mercury and argon emission line spectrum. All lines that were identified by the script are highlighted by a red circle. Now, all lines with known wavelengths need to be  marked. For this task, the above example spectrum can be very useful. The script runs through a list of predefined lines. The wavelength of the current line is displayed in the upper part of the window. The line corresponding to this wavelength can now easily marked by clicking into the corresponding red circle with the left mouse button. This circle should now appear blue and the corresponding wavelength is written next to the line peak (see below). If a wavelength is displayed that does not correspond to any of the highlighted lines, this wavelength can be skipped with a right click. At least four lines need to be marked to facilitate a successful wavelength calibration. If all useful lines are marked, this procedure can be completed by pressing the ''Q key'' on the keyboard. 
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 Now run the script: Now run the script:
  
-   ./3_createspectrum.py+   python 2_extractspectrum.py
  
 The following files are then created: The following files are then created:
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 Rerun the script to obtain a plot with adjusted line identifications.  Rerun the script to obtain a plot with adjusted line identifications. 
 +
 +/*
  
 ==== Radial velocity determination ==== ==== Radial velocity determination ====
 Due to the Doppler effect the relative velocity of a star towards or away from us results in a wavelength shift. This shift can be measured with the help of the absorption lines that are found in the spectrum. Due to the Doppler effect the relative velocity of a star towards or away from us results in a wavelength shift. This shift can be measured with the help of the absorption lines that are found in the spectrum.
-First we need to plot the fully calibrated spectrum in MIDAS, as shown before.+Please, ask the supervisors to create fits files of you spectra, first. 
 +We need to plot the fully calibrated spectrum in MIDAS.
    $inmidas    $inmidas
    crea/graph    crea/graph
-   indisk/ascii stern_spectrum.dat stern_spectrum 
    plot stern_spectrum    plot stern_spectrum
  
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    center/gauss gcursor,2 ? absorption    center/gauss gcursor,2 ? absorption
 To do the fit of the function click left and right of the absorption line with the left mouse button, to quit press the right mouse button. In the terminal you will find the fit parameters like "CENTER" (central wavelength of the line core) or "FWHM" (Full Width at Half Maximum), which gives you the width of the Gaussian function. Re-do the measurement several times to be sure to set good limits for the Gaussian fit and to get a feeling of the error in the measurement. This should be done for at least five single absorption lines. Do you see a difference in the accuracy of the measurent of the central wavelength of different lines? Discuss the reason in the report. With the help of the Doppler formula you can then calculate the relative velocity of the star from the shift of the central wavelength of the absorption lines in respective to their rest wavelength given in the linelist (''absorption_lines'').  To do the fit of the function click left and right of the absorption line with the left mouse button, to quit press the right mouse button. In the terminal you will find the fit parameters like "CENTER" (central wavelength of the line core) or "FWHM" (Full Width at Half Maximum), which gives you the width of the Gaussian function. Re-do the measurement several times to be sure to set good limits for the Gaussian fit and to get a feeling of the error in the measurement. This should be done for at least five single absorption lines. Do you see a difference in the accuracy of the measurent of the central wavelength of different lines? Discuss the reason in the report. With the help of the Doppler formula you can then calculate the relative velocity of the star from the shift of the central wavelength of the absorption lines in respective to their rest wavelength given in the linelist (''absorption_lines''). 
 +
 +*/
 +
 /*Dazu klickt man die beiden Punkte an, an denen der linke und rechte Linienflügel ins Kontinuum /*Dazu klickt man die beiden Punkte an, an denen der linke und rechte Linienflügel ins Kontinuum
 übergehen. Die Fitparameter wie “CENTER” (Wellenlänge des Linienkerns in Å) oder “FWHM” übergehen. Die Fitparameter wie “CENTER” (Wellenlänge des Linienkerns in Å) oder “FWHM”
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 ===== Report ===== ===== Report =====
  
-A usual report is to be handed in. It needs to describe the theoretical basics (spectral types & formation of stellar spectra & Doppler effect), identify distinctive spectral lines for each spectral type, and (shortly) describe and discuss the typical characteristics (i.e. the specific lines per spectral type) of each spectral type. Estimate the spectral type of the stars. Discuss your results and compare them to the known features for a certain spectral type from the literature. Address shortcomings in your results and discuss possible causes. **Please include all plots from the data reduction /* ,** including the plot for the spectral resolution and the original images showing the 2d spectra, ** */ in the appendix of your report**. /* For each star, the plot showing the spectra of the individual orders should be also attached to the report. Only the characteristic orders (individual panels from the masterplot) for each star should be included in the main part of the report.*/  
  
-After identifying the spectral type, the radial velocity of the star towards us should be measured (including an error calculation) and discussed. **In the appendix of your report** you should include a table with the rest wavelength, the measured wavelength, the wavelength shift and the resulting radial velocity of at least five absorption lines as well as an averaged radial velocity together with an error.+A usual report is to be handed in. See a general overview about the required structure and content [[https://polaris.astro.physik.uni-potsdam.de/wiki/doku.php?id=en:praktikum:protocol|here]].
  
-**Remark:** This [[http://ned.ipac.caltech.edu/level5/Gray/frames.html | web page]] can be helpful in the process of the identification and the classification of spectra and their characteristics. /*Furthermore, this {{en:labcourse:n1:spectral_identification.pdf|classification flowchart}} might be helpful.*/ Here  you can also find another {{en:labcourse:n1:atlas.pdf|spectral atlas}}, which helps to identify the spectral type. This {{en:labcourse:n1:abb85karttunen_en.pdf|figure}} taken from Fundamental Astronomy by Karttunen et al. can also be helpful to classify the spectra.+For this experiment, the theoretical overview in the report should describe the formation of stellar spectra, the different spectral types with their main characteristics and properties, and the concepts behind radial velocity measurements.
  
-[[en:praktikum:index|Overview: Laborytory Courses]]+In the methods section describe the observations and the data reduction, highlight points that deviate from general description in here and list all the parameters you set for the extraction. Further, include all the plots of the data reduction in the report (a few in the text, most of them in the appendix). 
  
-/*A usual report has to be handed in. It needs to describe the theoretical basics (spectral types & formation of stellar spectra), identify distinctive spectral lines for each spectral type, and (shortly) describe and discuss the typical characteristics (i.e. the specific lines per spectral type) of each spectral type. Please include all plots from the data reduction in the appendix of your report. +The results part presents and describes the calibrated spectra of the stars.
  
-**Remark:** This [[http://ned.ipac.caltech.edu/level5/Gray/frames.html | web page]] can be helpful in the process of the identification and the classification of spectra and their characteristics.+The analysis of the spectra contains the estimation of the spectral type for your target stars based on the characteristics that you have described in the theoretical background section.  
 + 
 +Finally, discuss your findings. Bring your results into a larger context and make a literature comparison when possible. This also includes that you identify potential problems with the data, the data reduction, or the analysis and possible solutions for them. Are their inconsistencies? Do you see specific and obvious features in the spectra you cannot explain? 
 + 
 +//**Note:** This {{en:labcourse:n1:abb85karttunen_en.pdf|figure}} [1] can be helpful to classify the spectra. You may also compare your spectra to the {{en:labcourse:n1:atlas.pdf|spectral atlas}} and look up the [[http://ned.ipac.caltech.edu/level5/Gray/frames.html | NIST web page]] to identify individual spectral features. Another guide to the classification of stellar spectra can be found [[https://www.handprint.com/ASTRO/specclass.html|here]].// 
 + 
 +[1] [[https://ui.adsabs.harvard.edu/abs/1959elas.book.....S/abstract|Struve, O. (1959): Elementary Astronomy (Oxford University Press, New York) p. 259]] 
 + 
 +[[en:praktikum:index|Overview: Laborytory Courses]]
  
-[[en:praktikum:index|Overview: Laborytory Courses]]*/ 
  
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  • Last modified: 2018/11/06 14:51
  • by schaffenroth