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Credit:
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When making use of the data inside this archive, please cite:

Gratier et al., 2017, A&A, doi:10.1051/0004-6361/201629847

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Archive URL:
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The original version of this archive is available at

    https://www.iram.fr/~pety/ORION-B/data/orionb-2017-gratier.tar.xz

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Contents:
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This archive contains the data used in Gratier et al. (2017). These data
are mostly derived from observations with the IRAM-30m telescope in the
context of the ORION-B project, cf., https://www.iram.fr/~pety/ORION-B/

All the maps are gridded in a custom set of coordinates, with the origin
set on the PDR of the Horsehead Nebula (RA-Dec coordinates provided in the
header), and with an axis position angle rotated by 14 degrees with respect
to the North-South orientation [1]. The FITS file headers are WCS
compliant, and our custom set of coordinates should be understood by any
standard FITS reader.

The archive constains:

- The spatial distribution of the signal from 12 different lines gathered
  in a single fits cube, named signal-raw.fits. Each plane contains the
  signal averaged over 3 contiguous channels around 10.5 km/s. In details:

      Plane   Linename   Freq. [MHz]    Array unit  Beam [arcsec]
      #1      12CN10    113490.97020    K (Tmb)     29.7
      #2        32SO     99299.87000    K (Tmb)     29.7
      #3      12CS21     97980.95330    K (Tmb)     29.7
      #4      C18O10    109782.17300    K (Tmb)     29.7
      #5       HCN10     88631.84750    K (Tmb)     29.7
      #6       CH3OH     96741.37500    K (Tmb)     29.7
      #7         CCH     87316.89800    K (Tmb)     29.7
      #8      N2H+10     93173.76400    K (Tmb)     29.7
      #9       HNC10     90663.56800    K (Tmb)     29.7
      #10     HCO+10     89188.52500    K (Tmb)     29.7
      #11     13CO10    110201.35430    K (Tmb)     29.7
      #12     12CO10    115271.20200    K (Tmb)     29.7

- The spatial distribution of the projection of the data on the ith
  eigenvector of the PCA analysis. The corresponding file names are

      projection-on-eigenvector-00.fits
      projection-on-eigenvector-01.fits
      projection-on-eigenvector-02.fits
      projection-on-eigenvector-03.fits
      projection-on-eigenvector-04.fits
      projection-on-eigenvector-05.fits
      projection-on-eigenvector-06.fits
      projection-on-eigenvector-07.fits
      projection-on-eigenvector-08.fits
      projection-on-eigenvector-09.fits
      projection-on-eigenvector-10.fits
      projection-on-eigenvector-11.fits

  The files are sorted by decreasing percentage of the data correlation
  explained by the associated eigenvector (see Fig. 5 of [2])

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References:
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[4] Schneider et al., 2013, ApJ, doi:10.1088/2041-8205/766/2/L17
[3] Orkisz et al., 2017, A&A, doi:10.1051/0004-6361/201629220
[2] Gratier et al., 2017, A&A, doi:10.1051/0004-6361/201629847
[1] Pety et al. 2017, A&A doi:10.1051/0004-6361/201629862

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