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en:praktikum:sternspektren [2024/12/06 08:30] – [Execution of the script] rhainichen:praktikum:sternspektren [2024/12/10 11:00] (current) – rhainich
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 ====== N1 - Stellar spectra of different spectral types (DADOS) ====== ====== N1 - Stellar spectra of different spectral types (DADOS) ======
  
-<WRAP center round important 60%> +<WRAP center round info 60%> 
-This manual is being revised due to the change to the 900 lines/mm grating and the change to enhanced evaluation software. However, DADOS is fully functional and ready to use. During analysis, the supervisors will assist with some steps that differ slightly from the current version of this manual.   +These instructions are currently being revised as part of the move to enhanced evaluation software. However, the manual is currently complete. It can be used without further ado to evaluate the data. Just don't be surprised if you see "transition" or "transition_version" somewhere. 
 </WRAP> </WRAP>
- 
  
 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.  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.  
-*/ 
- 
- 
-/*The aim of this observation is to obtain an overview of different spectral types. Thus, choose at least one star of each spectral type (O, B, A, F, G, K, M, special classes after consultation) that is well visible ($m_\mathrm{V} \le 9\,$mag). Take spectra of these stars in order to classify them by means of the spectral lines and the shape of the continua. 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]].*/ 
  
 ===== Observation ===== ===== Observation =====
-Nightly observations at the OST in Golm with the DADOS spectrograph are required. The scientific and technical background for this observation are presented in the seminary talks. A list with objects will be provided by us.+Nightly observations at the OST in Golm with the DADOS spectrograph are required. The //DADOS// with a 900 lines/mm grid is currently used in combination with the //QHY 268M//. The scientific and technical background for this observation are presented in the seminary talks. A list with objects will be provided by us.
  
 **Note**: The following exposures are needed //for every// star: **Note**: The following exposures are needed //for every// star:
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   * calibration spectra with a discrete light source   * calibration spectra with a discrete light source
   * calibration spectra with a continuous light source (flatfield)   * calibration spectra with a continuous light source (flatfield)
-  * darkframes for the exposures of the stellar spectra and the continuous light source+  * darkframes
  
 The calibration exposures are needed to calculate the pixel scale (wavelength calibration) and to remove the instrument signatures and possible artifacts. The calibration exposures are needed to calculate the pixel scale (wavelength calibration) and to remove the instrument signatures and possible artifacts.
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 The following variables need to be set in the script: The following variables need to be set in the script:
-<code>+<code Python>
 ### ###
 #   Path to the directories with the images #   Path to the directories with the images
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 There are several tools for viewing 2D images in FITS format. //ds9// is easy to use and can be started from the terminal: There are several tools for viewing 2D images in FITS format. //ds9// is easy to use and can be started from the terminal:
  
-   ds9 filename.fit +  ds9 filename.fit 
  
 Tasks: Tasks:
-  * determine the range of CCD rows that contains the stellar spectrum (master_spectrum.fit). +  * determine the range of camera chip rows that contains the stellar spectrum (master_spectrum.fit). 
-  * determine the range of CCD rows that can be used as background. Important: The background region must be outside the spectrum, but still within the used slit of the spectrograph. If the latter cannot be distinguished from the black background, compare with the images of the lamp spectra (master_wave.fit).+  * determine the range of camera chip rows that can be used as background. Important: The background region must be outside the spectrum, but still within the used slit of the spectrograph. If the latter cannot be distinguished from the black background, compare with the images of the lamp spectra (master_wave.fit).
  
  
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 === Basic principle === === Basic principle ===
-The script searches for the maxima in the calibration spectrum, marks them and notes the pixel number where the intensity maxima are located. It then assigns a wavelength to each of these values. This creates a pixel-wavelength mapping that is used to analyse the star's spectrum. +The script searches for the maxima in the calibration spectrum, marks them and notes the pixel number where the intensity maxima are located. It then assigns a wavelength to each of these values. This creates a pixel-wavelength mapping that is used to analyze the star's spectrum. 
  
 === Parameter === === Parameter ===
 The corresponding script is called **2_findcaliblines.py**. In this file, using an editor of your choice (e.g. //Kate//), you only need to edit the line region where the calibration spectrum is to be found (''specRegionStart'' and ''specRegionEnd''; can be the same as the one you want to extract the star spectrum from) and a line region that is **outside the slits** (''bgRegionStart'', ''bgRegionEnd''): The corresponding script is called **2_findcaliblines.py**. In this file, using an editor of your choice (e.g. //Kate//), you only need to edit the line region where the calibration spectrum is to be found (''specRegionStart'' and ''specRegionEnd''; can be the same as the one you want to extract the star spectrum from) and a line region that is **outside the slits** (''bgRegionStart'', ''bgRegionEnd''):
-   + 
-  # name of the file with the wavelength calibration spectrum  +<code Python> 
-  calibFileName   = "calib_wave.FIT" +# region (rows on the image) containing the calibration spectrum 
-   +specRegionStart = 495 
-  # region (rows on the image) containing the calibration spectrum +specRegionEnd   = 600
-  specRegionStart = 495 +
-  specRegionEnd   = 600 +
-   +
-  # background region (rows on the image), which needs to be outside of the slits +
-  bgRegionStart   = 0 +
-  bgRegionEnd     = 200+
    
 +# background region (rows on the image), which needs to be outside of the slits
 +bgRegionStart   = 0
 +bgRegionEnd     = 200
 +</code>
 +
 The calibration is designed such that lines of mercury and argon are identified. The strongest lines that can be expected are marked in the following plot. The calibration is designed such that lines of mercury and argon are identified. The strongest lines that can be expected are marked in the following plot.
  
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 [{{ :ost:spektrograph:spectra:calib_lines_dados.jpg?direct&800 | Emission spectrom of our calibration lamp. The strongest mercury and argon lines are identified.}}] [{{ :ost:spektrograph:spectra:calib_lines_dados.jpg?direct&800 | Emission spectrom of our calibration lamp. The strongest mercury and argon lines are identified.}}]
 ++++ ++++
 +
 === Execution of the script === === Execution of the script ===
 Now run the script by executing: Now run the script by executing:
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 === Basic principle === === Basic principle ===
-The next step after the determination of the calibration curve is the reduction of the stellar spectrum. First, the darkframe is subtracted from the spectrum, then the spectrum is divided by the flatfield, and, lastly, the wavelength calibration is performed. It also exist the possibility to mark spectral lines in the spectrum.+Once the wavelength-pixel mapping has been determined, the actual star spectrum can be evaluated. By default, the spectrum is divided by the flat field and then the wavelength calibration is performed. It is also possible to normalize the spectrum and mark the spectral lines identified in the spectrum.
  
 === Parameters === === Parameters ===
-This associated script is named ''2_extractspectrum.py''. The script has a number of parameters, similar to the previous scripts, along with some additional parameters. The parameter section usually looks similar to this:+This associated script is named ''3_extractspectrum.py''. The script has a number of parameters, similar to the previous scripts, along with some additional parameters. The parameter section usually looks like this:
  
-   ### science spectrum file ### +<code Python> 
-   # file with stellar spectrum +#   Name of the object 
-   science        =  'star.FIT' +object_name: str = "star"
-   # directory of the darkframe for the stellar spectrum +
-   darkframe_dir  =  'darks/??s/' +
-   # flatfield directory +
-   flatfield_dir  =  'flats/' +
-   # directory of the darkframe for the flats +
-   flatdark_dir   =  'darks/??s/' +
-    +
-    +
-   ### Data that should be extracted  ### +
-   # region containing the science spectrum +
-   specRegionStart = 495 +
-   specRegionEnd   = 590 +
-    +
-   # sky background region (inside the slit) +
-   bgSkyStart   = 96 +
-   bgSkyEnd     = 104 +
-    +
-    +
-   ### Plot range ### +
-   # set the variables to '?' for an automatic resizing +
-   lambdamin = '?' +
-   lambdamax = '?' +
-   #lambdamin = 3500. +
-   #lambdamax = 5000.+
  
-Comments on these parameters:: +### 
-  * The variables ''specRegionStart'' and ''specRegionEnd'' define the range of CCD rows that will be extracted. These rows need to be chosen such that the stellar spectrum is completely covered.  +#   Extraction regions 
-  * The sky background needs to be subtracted. So, as before, a range of rows **within the slit** but **outside the spectrum** must be chosen. If possible, the number of rows should be the same for both, i.e. (specRegionStart - specRegionEnd) = (bgSkyStart - bgSkyEnd). +# 
-  * The options ''lambdamin'' and ''lambdamax'' can be used to restrict the plot range. If these variables contain a ''?'' the plot range will be determined automatically. +#   Region containing the science spectrum 
 +spec_region_start: int = 759 
 +spec_region_end: int = 772
  
 +#   Sky background region (inside the slit)
 +background_sky_start: int = 710
 +background_sky_end: int = 730
  
-++++ Additional parameter |+### 
 +#   Plot range 
 +# 
 +#   Set the variables to '?' for an automatic resizing 
 +lambda_min: str | float = '?' 
 +lambda_max: str | float = '?' 
 +flux_min: str | float = '?' 
 +flux_max: str | float = '?'
  
-**Reduction method:**  +### 
-The variable ''mode'' allows to specify the reduction method. An average over all extracted CCD rows will be calculated, if the method //mean// is set. A median function will be applied, if //median// is selected.  The latter method should be used as the default. +#   Normalization ? 
 +#   Possibilities: True or False 
 +# 
 +normalize: bool = False 
 +</code>
  
-   ### Image reduction mode ### +Comments on these parameters:: 
-   #mode = 'mean' +The name of the observed star can be specified in ''object_name''. The variables ''spec_region_start'' and ''spec_region_end'' define the lines of the camera chip containing the spectrum to be read out. From this star spectrum the sky background has to be subtracted. This is done by selecting a region that lies **within the slit** but **does not contain a spectrum**. This region is defined by the variables ''background_sky_start'' and ''background_sky_end''. The options ''lambda_min'' and ''lambda_max'' as well as ''flux_min'' and ''flux_max'' can be used to restrict the plot area on the X or Y axis. If ''?'' is written in these variables, the plot range is automatically defined.
-   mode = 'median' +
- +
-**Line identifications:** +
-The line identifications can be switched on and off via the variable ''plotident'':+
  
-   ### Idents ### 
-   # plot idents yes or no 
-   plotident = 'yes' 
-   #plotident = 'no' 
- 
-The file with line identifications, which by default is simply denoted by ''absorption_lines'', is not required for a successful script run, i.e. the variable ''lineFile'' can be an empty string or point to an empty file: 
- 
-   # file containing line identifications 
-   lineFile = "" 
-   # or 
-   lineFile = "directory/empty_file.dat" 
- 
-See below for an explanation how to adjust the line identification file for the individual stars.  
- 
-**File names:** 
-It also exists the possibility to change the names of the output files as well as to adjust the names of the files from the first step of the data reduction that are now needed as input for the wavelength calibration. 
- 
-++++ 
  
 === Execution of the script === === Execution of the script ===
 Now run the script: Now run the script:
  
-   python 2_extractspectrum.py+   python 3_extractspectrum.py
  
-The following files are then created: +The following files are generated by default:
- +
-  * stern_spectrum.dat - with the tabulated spectrum +
-  * stern_spectrum.pdf - showing the plotted spectrum +
-  * flatfield.pdf - showing the plotted flatfield (please add this plot to your report)+
  
 +  * ''spectrum_panels_{object_name}.pdf'' - with the spectrum in several panels (zoom version)
 +  * ''spectrum_total_{object_name}.pdf'' - with the spectrum displayed in a single panel
 +  * ''{object_name}_spectrum_total.dat'' - with the spectrum in tabular form 
 +  * ''{object_name}_spectrum_total.csv'' - with the tabulated spectrum in CSV format
  
  
 === Identification of spectral lines === === Identification of spectral lines ===
  
-Line identifications for known spectral lines can be plotted by means of a file containing these information. An example file (''absorption_lines'') can be found in the ''scripts'' directory. This file **contains some but not all important spectral lines** that are visible in the variety of stars, which we observe. **Therefore, it is required to search for additional spectral lines** and the corresponding transitions for example in the  [[http://physics.nist.gov/PhysRefData/ASD/index.html|NIST Database]]. A how-to for this can be found [[en:praktikum:nist|here]]. Moreover, it is recommended to create an individual line-identification file for each of the observed stars.  +Line identifications for known spectral lines can be plotted by means of a file containing these information. The **ions** that are to be identified via the line identifications **must be specified in the variable** ''ions''. **If this is not done, no line identifications will be displayed!** The script reads the line information from the file ''atomic_lines.tsv''. **But since this file contains only a selection of spectral lines**, which are found in the many different stars, **it is necessary to search for additional spectral lines** and their transitions, e.g., in the [[http://physics.nist.gov/PhysRefData/ASD/index.html|NIST data base]] as already mentioned, we also have a [[en:praktikum:nist|tutorial]] for this database. The extracted line information need to be entered into the variable ''manual_lines''. 
- +
-To identify lines in the stellar spectrum, copy the relevant lines into the separate file. The format of that file should look like (wavelength in Å | identifier): +
- +
-   3888.052 HI +
-   3970.075 HI +
-   4861.38 HI +
-   6562.88 HI +
-   5801.33 5811.98 CIV +
- +
-As can be seen from the last entry, also ions with multiplet transitions can be included. **Line identifications that can be not assigned to any spectral line need to be removed from the corresponding file.** +
- +
-The file can then be referenced in the Python script: +
- +
-   # file containing line identifications +
-   lineFile = "directory/line_list_for_starname.dat" +
- +
-Rerun the script to obtain a plot with adjusted line identifications.  +
- +
-/* +
- +
-==== 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. +
-Please, ask the supervisors to create fits files of you spectra, first. +
-We need to plot the fully calibrated spectrum in MIDAS. +
-   $inmidas +
-   crea/graph +
-   plot stern_spectrum +
- +
-The following commands can be used to select a certain range in x (xlow < x < xhigh) or y (ylow < y < yhigh) in the plot to zoom in on one spectral line: +
-   set/gra xa=xlow,xhigh +
-   set/gra ya=ylow,yhigh +
-While determining the spectral type you already identified several absorption lines. For those we want to measure the central wavelength. This can be done by fitting the line with a Gaussian function. +
-   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'').  +
- +
-*/ +
- +
-/*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” +
-(Full Width at Half Maximum, Halbwertsbreite in Å) werden in der Konsole angezeigt. Beenden +
-mit Rechtsklick im Plotfenster.*/+
  
 +The following options must be set in the //Python// script:
  
 +|< 100% - >|
 +^ Variable ^ Description  ^
 +| ''radial_velocity'' | Measured radial velocity in km/s (without barycentric correction) |
 +| ''ions'' | Ions to be considered for line identification |
 +| ''manual_lines'' | By means of this variable further line identifications can be added manually. An identification string such as "HeI", the wavelength and the alignment parameter ("center", "left" or "right") must be set for each line. |
 +| ''percentage_line_flux_must_be_below_continuum'' | This variable determines how deep lines must be in comparison to the continuum so that line identifications are displayed for the corresponding lines. The higher this value, the fewer line identifications are displayed, since only the stronger lines then fulfill this criterion. **Note:** If the radial velocity is wrong and a value greater than zero is set here, then the line identification often does not work. Therefore this variable should be set to zero if the radial velocity is unknown. |
  
  
 ===== Report ===== ===== Report =====
- 
- 
 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]]. 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]].
  
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 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.  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?+Finally, the results are discussed and placed in a wider context. This includes, for example, a comparison with the literature where possible. Possible sources of error should also be discussed. Are there inconsistencies in the data or deviations from what is expected? Or are there structures and anomalies in the spectra that cannot be explained? Describe possible solutions and explanations for the problems found.
  
 //**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]].// //**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]].//
 +
 +//**Note:** The plots of each order of the spectra can be large files, often too large for an email attachment. You can upload the report to the [[https://boxup.uni-potsdam.de/index.php/login|University Cloud Service (BoxUP)]] and send us the link or file path to the plots if you have saved them on the lab computer.//
  
 [1] [[https://ui.adsabs.harvard.edu/abs/1959elas.book.....S/abstract|Struve, O. (1959): Elementary Astronomy (Oxford University Press, New York) p. 259]] [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: Laboratory Courses]]
  
  
  • en/praktikum/sternspektren.1733473848.txt.gz
  • Last modified: 2024/12/06 08:30
  • by rhainich