Comparison between IRAF/NEBULAR/Temden and PyNeb

[Zixuan Peng]

Hi,

I have one simple question about the comparison between Temden and PyNeb. When I assume the electron temperature to be 10k and the line ratio of SII spectrum (I(6716)/I(6731))  to be 0.75, then I get ~1400 cm^(-3) for PyNeb and ~1740 cm^(-3) for temden. 

Code for PyNeb: S2.getTemDen(0.75, tem = 10000,to_eval="I(3, 1) / I(2, 1)")

Code for Temden: temden density 0.75 atom=sulfur spectrum=2 assume=10000

However, after I check the paper released in 2014 "PyNeb: a new tool for analyzing emission lines", I find their results (Table 4 row 2) actually match with each other in the paper (both around 1740 cm^(-3)). Therefore, I am wondering if I miss any important information or any condition for PyNeb that caused this difference. Or, is it related to the version of PyNeb I use (in the 2014 paper, the version is 1.0.1, but I use the version 1.1.10 ). Thank you very much.

[Christophe Morisset]

Hi Zixuan,

Atomic data have been updated since the 2014 version. It seems to me that the iraf temden program is using the following data:'s_ii_atom_VVF96-KHOC93.dat' and 's_ii_coll_RBS96.dat'.

The big advantage of PyNeb is that you can easily change the atomic data and see the effects they have:

In [1]: import pyneb as pn                                                                                                                                

In [2]: S2 = pn.Atom('S',2)                                                                                                                              

In [3]: S2.printSources()                                                                                                                                
S2: All A-values for levels 1-8: Podobedova, Kelleher, & Wiese 2009, JPCRD, Vol. 3:
S2: Energy levels:
    Ref. 7237 of NIST 2014 (try this: http://physics.nist.gov/cgi-bin/ASBib1/get_ASBib_ref.cgi?db=el&db_id=7237&comment_code=&element=S&spectr_charge=2&):
S2: collision strengths: Tayal & Zatsarinny 2010, ApJ 188, 32:

In [4]: pn.atomicData.getAllAvailableFiles('S2')                                                                                                          
Out[4]:
['s_ii_atom.chianti',
 's_ii_atom_KKFBL14.dat',
 's_ii_atom_PKW09.dat',
 's_ii_atom_TZ10-PKW09.dat',
 's_ii_atom_VVF96-KHOC93.dat',
 's_ii_atom_VVF96-M82a.dat',
 's_ii_coll.chianti',
 's_ii_coll_RBS96.dat',
 's_ii_coll_TZ10.dat']

In [5]: pn.atomicData.setDataFile('s_ii_coll_RBS96.dat')                                                                                                  

In [6]: pn.atomicData.setDataFile('s_ii_atom_VVF96-KHOC93.dat')                                                                                          

In [7]: S2_iraf = pn.Atom('S',2)                                                                                                                          

In [8]: S2.getTemDen(0.75, tem = 10000,to_eval="I(3, 1) / I(2, 1)")                                                                                      
Out[8]: 1377.5903602488895

In [9]: S2_iraf.getTemDen(0.75, tem = 10000,to_eval="I(3, 1) / I(2, 1)")                                                                                  
Out[9]: 1739.7116203754206

Hope it helps,

Chrisotphe