# HCN Model¶

HCN is a molecule with hyperfine lines. It uses the hyperfine wrapper.

This is an HCN fitter… ref for line params: http://www.strw.leidenuniv.nl/~moldata/datafiles/hcn@hfs.dat

## Module API¶

pyspeckit.spectrum.models.hcn.aval_dict = {'10-01': 2.4075e-05, '11-01': 2.4075e-05, '12-01': 2.4075e-05}

Line strengths of the 15 hyperfine components in J = 1 - 0 transition. The thickness of the lines indicates their relative weight compared to the others. Line strengths are normalized in such a way that summing over all initial J = 1 levels gives the degeneracy of the J = 0 levels, i.e., for JF1F = 012, three for JF1F = 011, and one for JF1F = 010. Thus, the sum over all 15 transitions gives the total spin degeneracy

pyspeckit.spectrum.models.hcn.hcn_radex(xarr, density=4, column=13, xoff_v=0.0, width=1.0, grid_vwidth=1.0, grid_vwidth_scale=False, texgrid=None, taugrid=None, hdr=None, path_to_texgrid='', path_to_taugrid='', temperature_gridnumber=3, debug=False, verbose=False, **kwargs)[source] [github] [bitbucket]

Use a grid of RADEX-computed models to make a model line spectrum

The RADEX models have to be available somewhere. OR they can be passed as arrays. If as arrays, the form should be: texgrid = ((minfreq1,maxfreq1,texgrid1),(minfreq2,maxfreq2,texgrid2))

xarr must be a SpectroscopicAxis instance xoff_v, width are both in km/s

grid_vwidth is the velocity assumed when computing the grid in km/s this is important because tau = modeltau / width (see, e.g., Draine 2011 textbook pgs 219-230) grid_vwidth_scale is True or False: False for LVG, True for Sphere