A molecular spectral line survey of the high-massstar-forming clump NGC 6334I

Contact: Oskari Miettinen (room 221, e-mail: oskari@phy.hr)

1 Background

The purpose of this exercise work is to give students a hands-on introduction to how to reduce andanalyse spectroscopic data obtained with radio telescopes.

The observations analysed here were performed with the single-dish 12-metre APEX (AtacamaPathfinder EXperiment) telescope in Chile (see Fig. 1)1. The spectral line receiver used was APEX-1of the Swedish Heterodyne Facility Instrument (SHeFI), which is an SIS (superconductor-insulator-superconductor) heterodyne receiver operating in the frequency range of 213–275 GHz. The observedfrequencies were centred on 221 GHz and 225 GHz, that is the present work deals with λ ∼ 1.3 mmspectral line observations.

The target source is the Galactic high-mass star-forming clump NGC 6334I (see Fig. 2), whichcontains so-called hot molecular cores (HMCs), and hence exhibits a very rich gas-phase chemistry.The most recent studies (Reid et al. 2014; Chibueze et al. 2014) suggest that the distance of NGC6334I from the Earth is about ∼ 1.3 kpc (∼ 4 240 light years), which makes this source one of thenearest high-mass star-forming regions.

2 Data

The data sets needed in this exercise work can be downloaded from www.phy.pmf.unizg.hr/~vs/

MAT/Vjezbe_files/Vjezba_3_Spec_Lines. The folder contains four .tar files that you can copy toyour own folder. After uncompressing the files, you can find files with a .apex extension; these arethe actual data files to be used. Moreover, the observation log files can be found in these folders.

3 The data reduction software

The data reduction here is done using the CLASS90 program of the GILDAS software package2.This software is commonly used to reduce spectral line observations performed with single-dish radiotelescopes.

The CLASS90 program is installed on krampus, and you should be able to start CLASS90 by justtyping class on the command line. Alternatively, you can download the software package andinstall it on your own computer; just go to the download page on the GILDAS webpage and followthe instructions (besides UNIX, both Mac and Windows are also supported).

4 The data reduction steps

The CLASS manual, available on the GILDAS website, contains all the relevant information to re-duce the data. In particular, the manual’s Cookbook section contains a nice summary of a typical(CLASSic) session. Here, the main reduction steps are described for clarity.

1www.apex-telescope.org2www.iram.fr/IRAMFR/GILDAS/

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4.1 Reading data

The .apex data files can be read using the command file in, followed by the name of the file. Afterthis, you need to write find, which tells CLASS90 to find the data files. The command list can thenbe used to check the content of the files. Note that besides the science observations towards NGC6334I, there are also calibration measurements included in the files. To list only the data we areinterested in, you can write set source NGC−6334−I, and list the data again as above. To select the221 GHz (225 GHz) data, you can write set line LINE1 (LINE2), and select the different subbandswith the command set tel AP-H201-X201 or set tel AP-H201-X202.

4.2 Summing the individual spectra

To create the sum spectrum from individual measurements, we can first define the weighting to bethat based on the integration time: type the command set weight time (CLASS90 also understandsabbreviated commands; e.g. set weight time can be written as set weight t). After this, thecommand average will average the individual measurements to yield a single spectrum. By typingplot, you can see how the spectrum looks. By default, the x-axis is frequency in MHz, but you canchange this to the local standard of rest (LSR) velocity by typing set unit v; the latter conventionis commonly used in radio astronomy. The header information can be printed by typing header.

4.3 Creating the final spectrum

As you can see from the spectrum created above, the baseline of the spectrum lies above 0 (note:the intensity scale on the y-axis is the antenna temperature corrected for atmospheric losses). Tomeasure the absolute intensities of the spectral lines, we need to remove the baseline. This can bedone interactively by first typing set curs on, which activates the interactive cursor. After this,write set win, and define windows by clickling the left mouse button (or spacebar) on both sidesof the visible spectral lines; exit by clickling the right mouse button. To subtract a linear baseline,write base /plot, where the option plot will show the result as a red line on the spectrum. If thebaseline looks complex, you can try a polynomial baseline: base n /plot, where n is the degree ofthe polynomial function. After this, type plot, and you should see a spectrum where the baseline isat y = 0.

Repeating the aforementioned steps for all the data taken on different days will result in the spectrafrom which we can start to identify the detected spectral lines. If the spectrum looks noisy, you cantry to smooth it by the command smooth to increase the signal-to-noise ratio. Note, however, thatsmoothing will reduce the number of channels, and hence degrades the frequency/velocity resolutionof the data.

4.4 A note on Gaussian fitting

The spectral lines can typically be fit using a Gaussian profile. For this purpose, one can writelines n, where n is the number of lines (n= 0 is ok if you have a single line visible). After this, theline(s) can be defined using the cursor. The commands min and vis will fit a Gaussian, show theresulting line parameters (radial velocity, FWHM linewidth, intensity, and integrated intensity), andoverplot the fit with a green line (by default). However, the main purpose of this exercise work is toidentify the lines, and Gaussian fitting is not necessary here. The line intensity is needed if you wantto quantify the significance (signal-to-noise ratio) of the detected line, and the line parameters areneeded for the calculation of the column densities of the identified chemical species (not the purposeof the present exercise).

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5 Line identification

The next step is to try to identify the detected spectral lines, that is the corresponding molecularspecies and transitions (here we are dealing with line emission arising from quantum mechanicaltransitions between rotational levels).

The line identification can be done by using Weeds, which is an extension of the CLASS soft-ware (try the command help weeds\). For this purpose, one needs to download a spectroscopicdatabase. Weeds can access the NASA Jet Propulsion Laboratory (JPL) database for molecularspectroscopy3 and the Cologne Database for Molecular Spectroscopy (CDMS)4. For example, thecommand use in cdms tells the program to select the CDMS database. You can download theentire database, but that will take some time. A better option is to download only the relevant fre-quency range, which you can see from the plotted spectrum. For example, downloading a frequencyrange from 219 GHz to 224 GHz can be done with the command select /freq 219e3 224e3. Notethat the frequency unit here is MHz.

By the command lid, you can now activate the cursor for line identification. Just go on top of aline, and click the left mouse button (or spacebar). You should now see the name of the moleculeappearing on the screen on top of the line, and some relevant spectroscopic parameters (such as theline transition and its frequency) printed on the command prompt screen. If you want to zoom-intowards a selected frequency/velocity range, you can write something like set mode x 221e3 222e3

followed by the command plot. You should now see the spectrum plotted from 221 GHz to 222 GHz.This way, you can see the separate lines much better (there can be many of them!; these are the so-called “interstellar weeds”). You can go back to the original plotting range by typing the commandset mode x auto.

The lid command has several options. For example, the command lid /energy 300 will onlysearch for transitions with upper-state energies Eu/kB < 300 K. See the CLASS manual and help

lid for further details.Note that sometimes the spectroscopic database in use does not contain the line you are trying

to identify. In this case, you can download the other catalogue (i.e. JPL instead of CDMS, or viceversa) and check whether the line can be found there. If not, the line will remain unidentified (thisis not unsual in spectral line survey studies). The Weeds program can also be used to model thedetected spectral lines, but this is beyond the scope of this exercise work. However, modelling thelines will result in a more reliable line identification compared to what can be done by frequencyanalysis only.

6 Tips for writing the report

After you are done with the data reduction and analysis, it is time to write a report of what you didand present the obtained results. For this purpose, you want pretty pictures showing the molecularline spectra towards NGC 6334I. By default, CLASS90 will also plot the header information abovethe spectrum, which is something we do not want to show. With the commands clear, box, spe,you can clear the screen, plot only the x- and y-axes, and finally plot the spectrum. An .eps figurecan be created with the command hardcopy spectrum.eps /dev eps color, where the examplefile name is spectrum.eps.

It is a good idea to show a table in your report that gives the names of the identified molecules andthe corresponding transitions and frequencies. This makes it easier for the reader to see what was

3http://spec.jpl.nasa.gov4www.astro.uni-koeln.de/cdms/catalog

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Figure 1: The APEX telescope (Credit: ESO).

found. NGC 6334I is a famous Galactic HMC that has been studied quite extensively in the past.You can find many papers on this source using the SAO/NASA Astrophysics Data System (ADS)5.

References

Chibueze, J. O., Omodaka, T., Handa, T., et al. 2014, ApJ, 784, 114Reid, M. J., Menten, K. M., Brunthaler, A., et al. 2014, ApJ, 783, 130

5http://adsabs.harvard.edu/abstract_service.html

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Figure 2: A VISTA (Visible and Infrared Survey Telescope for Astronomy) infrared image towardsthe NGC 6334 giant molecular cloud (the “Cat’s Paw Nebula”), which harbours the target source ofthe present exercise work – the massive clump NGC 6334I. The colour coding is as follows: Y -bandis blue, J-band is green, and Ks-band is red. The field of view is about one degree across. Credit:ESO/J. Emerson/VISTA.

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