Differences

This shows you the differences between two versions of the page.

--- en:praktikum:sternspektren [2018/11/06 14:51] – [Radial velocity determination] schaffenroth
+++ en:praktikum:sternspektren [2024/12/10 11:00] (current) – rhainich
@@ Line 1: / Line 1: @@
 ====== N1 - Stellar spectra of different spectral types (DADOS) ======
-/*
+<WRAP center round info 60%>
-<WRAP center round alert 60%>
+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.
-This manual is currently under revision. Please use the german one instead. Sorry for any inconvenience this may cause.
 </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. /*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.
-/*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 =====
-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:
-  * the stellar spectra
+  * stellar spectra
   * calibration spectra with a discrete light source
   * 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.
@@ Line 26: / Line 22: @@
 ===== Data reduction =====
-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/transition_version''.
-==== 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:
+{{section>deng:praktikum:a12:python#English&noheader}}
+=== Preparations ===
+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/''.
+=== Data reduction ===
+The **1_masterimages.py** script is available for data reduction. This script combines the individual images into corresponding 'master' files. For example, the individual dark images are combined into //masterdarks// according to exposure time by calculating the median of all images for each pixel.
+The following variables need to be set in the script:
+<code Python>
+###
+#   Path to the directories with the images
+#
+#   Darks:
+path_darks: str = '?'
+#   Flat darks:
+path_flat_darks: str = '?'
+#   Flats:
+path_flats: str = '?'
+#   Darks for wavelength calibration exposures:
+path_wavelength_darks: str = '?'
+#   Wavelength calibration exposures:
+path_wavelength: str = '?'
+#   Spectra:
+path_spectra: str = '?'
+</code>
+''path_darks'' is the path to the dark images with the same exposure time as the spectra images. The path to the latter must be specified in ''path_spectra''. The flats must be specified in ''path_flats'' and the corresponding darks in ''path_flat_darks''. The same applies to the images for the wavelength calibration, which must be specified under ''path_wavelength'' and ''path_wavelength_darks''.
+In addition, the variable ''trim_image'' should be set to **False**.
+==== Selection and inspection of the data ====
+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:
-  * determine the range of CCD rows that contains the stellar spectrum
+  * 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.
+  * 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).
@@ Line 42: / Line 75: @@
 === Basic principle ===
-This script finds the maxima of the emission lines in the discrete calibration spectrum, marks them, and identifies their pixel number (i.e. position of the maximum). These numbers are correlated to the wavelengths of those emission lines to have the conversion scale between the pixel and the wavelength.
+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 ===
-The required script (''1_findcaliblines.py'') is written in Python. Edit the file using a text editor of your choice (i.e. //kate// or //emacs//) and adjust the path to the exposure of the discrete light source (the black lamp that emits the line spectrum) as well as the CCD rows that should be extracted. Two row ranges are requested. One that contains the calibration spectrum and hence should lie **within** the slit, while the second one is designated for a background region and therefore needs to lie **outside** the slit:
+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.
-[{{ :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:dados_calib_900lines_ne-ar.jpg?direct&800 | Emission spectrom of our Ne-Ar calibration lamp. The strongest lines are identified.}}]
-/*
+++++ Old Hg & Ar calibration |
-The five strong lines of mercury in the used wavelength range can be cross-correlated with the pixel positions of these lines. Our ST-8 camera usually covers a wide spectral range such that not only the strong Hg lines but also some weak Ar lines are visible in the obtained calibration spectra. While these lines can be also use for the wavelength calibration, this might be not possible or desirable in some cases. In these situations the range where the script is looking for lines can be restricted with the parameters ''xstart'' and ''xend''.
+[{{ :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 ===
 Now run the script by executing:
-   ./1_findcaliblines.py
+   python 2_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.
+After running the script, the following window will appear, showing the emission line spectrum of neon and argon, with all lines identified by the script marked with a red circle. All emission lines with a known wavelength must now be selected in this window. The example spectrum above with the identified lines is very helpful here. The script specifies the possible lines, so all you need to do is left-click to select the corresponding red circles. The wavelength of the current line is displayed in red at the top of each window. If the wavelength of a line not marked with a red circle is displayed, it can be skipped by right-clicking. Successfully marked lines will then appear in blue and the corresponding wavelength will be written next to the emission peak (see below). At least four lines must be marked for a successful wavelength calibration. Once all possible lines have been marked, the process can be completed by pressing the 'Q' key on the keyboard.
 <WRAP group>
 <WRAP half column>
-[{{ :ost:spektrograph:dados:dados_select_line.png?direct&600 | Calibration plot without marked lines}}]
+[{{ :ost:spektrograph:dados:dados_calib_ne-ar_lines_detected.png | Calibration plot detected lines}}]
+</WRAP>
+<WRAP half column>
+[{{ :ost:spektrograph:dados:dados_calib_ne-ar_lines_marked.png | Calibration plot with the most prominent lines selected}}]
+</WRAP>
+</WRAP>
+++++ Old Hg & Ar calibration |
+<WRAP group>
+<WRAP half column>
+[{{ :ost:spektrograph:dados:dados_select_line.png?direct&600 | Calibration plot detected lines}}]
 </WRAP>
@@ Line 82: / Line 125: @@
 </WRAP>
 </WRAP>
+++++
+/*
 ++++ Error output |
@@ Line 94: / Line 139: @@
 This message can be ignored, since it has no impact on the calibration result.
 ++++
+*/
 Subsequently, the calibration curve will be plotted by the script (see below). If the calibration procedure is successful, the calibration curve will be nearly linear.
-[{{ :ost:spektrograph:dados:calibration_fit_dados.jpg?direct&400 |Calibration curve for our DADOS spectrograph }}]
+[{{ :ost:spektrograph:dados:dados_calib_wave_pixel_relation.png?direct&400 | Relation between wavelength and pixel for our DADOS spectrograph }}]
+++++ Old Hg & Ar calibration |
+[{{ :ost:spektrograph:dados:calibration_fit_dados.jpg?direct&400 | Relation between wavelength and pixel for our DADOS spectrograph }}]
+++++
 By default the following files are then created:
@@ Line 114: / Line 164: @@
 === 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 ===
-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 ===
 Now run the script:
-   ./3_createspectrum.py
+   python 3_extractspectrum.py
-The following files are then created:
-  * stern_spectrum.dat - with the tabulated spectrum
+The following files are generated by default:
-  * 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 ===
-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):
+The following options must be set in the //Python// script:
-.052	HI
+|< 100% - >|
-.075	HI
+^ Variable ^ Description  ^
-.38	HI
+| ''radial_velocity'' | Measured radial velocity in km/s (without barycentric correction) |
-.88	HI
+| ''ions'' | Ions to be considered for line identification |
-.33	5811.98	CIV
+| ''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. |
-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:
+===== 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]].
-   # file containing line identifications
+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.
-   lineFile = "directory/line_list_for_starname.dat"
-Rerun the script to obtain a plot with adjusted line identifications.
+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).
-==== Radial velocity determination ====
+The results part presents and describes the calibrated spectra of the stars.
-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.
-   $inmidas
-   crea/graph
-   indisk/ascii stern_spectrum.dat stern_spectrum
-   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:
+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.
-   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.*/
-===== 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.*/
+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.
-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.
+//**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]].//
-**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.
+//**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.//
-[[en:praktikum:index|Overview: Laborytory Courses]]
+[1] [[https://ui.adsabs.harvard.edu/abs/1959elas.book.....S/abstract|Struve, O. (1959): Elementary Astronomy (Oxford University Press, New York) p. 259]]
-/*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.
-**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.
+[[en:praktikum:index|Overview: Laboratory Courses]]
-[[en:praktikum:index|Overview: Laborytory Courses]]*/