MAPPINGS V Ionization Models
Description
MAPPINGS V v5.2.1 Ionization Models
File Names
File names are meant to be intuitive and indicate the ionization source with a
prefix and the contents with a suffix. A full list of prefixes is provided here.
| Model | Prefix |
|---|---|
| AGN Jin+ 2012 | agn-jin12 |
| AGN OXAF isobaric bubble | agn-oxaf-cpr |
| AGN OXAF isochoric bubble | agn-oxaf-cdn |
| BPASS isobaric bubble | bpass-cpr-shl |
| BPASS isobaric filled sphere | bpass-cpr-sph |
| BPASS isobaric plane | bpass-cpr-ppl |
| BPASS isochoric bubble | bpass-cdn-shl |
| BPASS isochoric plane | bpass-cdn-ppl |
| STARBURST99 isobaric bubble | sb99-cpr-shl |
| STARBURST99 isochoric bubble | sb99-cdn-shl |
| shocks | shck |
| precursor | prec |
| shock + precursor | shckprec |
| dusty shocks | shck-dst |
| dusty precursor | prec-dst |
| dusty shock + precursor | shckprec-dst |
Files ending in _fluxes.csv contain the line fluxes relative to Hβ.
Files ending in _propts.csv contain nebular properties of the model ionized
region.
Table Formats
Formatting is by comma-separated values. The first column will always be the
model identifier, or key. This key is specific to a row in both the flux and
properties tables of the same prefix. Tables are sorted by key identifier, which
can be used to ensure that fluxes and properties are properly matched.
The next few subsequent columns contain the unique assumptions regarding that
particular model, including ionization parameter, metallicity, velocity,
density, magnetic field strength, and ionizing SED.
Future work will enable use of keys to join tables via SQL. Presently, we
recommend users join tables using pandas as in the following example for the
shock+precursor models, eliminating any duplicate column headings.
>> import pandas as pd
>> fluxes = pd.read_csv('shock-precursor_fluxes.csv')
>> propts = pd.read_csv('shock-precursor_propts.csv)
>> joiner = [k for k in fluxes.keys() if k in propts.keys()]
>> shkprc = fluxes.merge(propts, how='inner', on=joiner)
Multiple model sets can also be combined using pandas as in the following
example for BPASS isobaric and isochoric models:
>> import pandas as pd
>> bpass_cpr = pd.read_csv('bpass-cpr_fluxes.csv')
>> bpass_cdn = pd.read_csv('bpass-cdn_fluxes.csv')
>> bpass_tot = pd.concat([bpass_cpr,bpass_cdn])
>> bpass_tot.reset_index(inplace=True)
Lines Included
We include a large suite of lines spanning FUV through the MIR. Only a subset of
these lines were considered for our inaugural publication, which focused on the
stronger FUV lines. These lines include emission from various species of the
following elements:
H, He, C, N, O, S, Ne, Ar, Si, Mg, Ca, and Fe.
Lines are labeled following PyNeb formatting:
EI_WaveU
where E is the element (e.g., O for oxygen), I is the ion species as an Arabic
numeral, Wave is the wavelength, and U is the unit of the wavelength. If the
line is a recombination line, it will contain the ‘r’ suffix. For wavelengths
less than 1 um, we express Wave in A as a whole number. For wavelengths greater
than 1 um, we express Wave in um with two decimal places. Some
examples:
| Emission Line | Column |
|---|---|
| C III] 1909 Å | C3_1909A |
| He II 4686 Å | He2r_4686A |
| [Ar II] 6.98 µm | Ar2_0698um |
| [O IV] 24.89 µm | O4_2489um |
The full set of lines in this release is included in the aa_line_list.md file
in this repository. If a line of interest is not included, please let us know,
and we will add it as soon as we are able.
Properties Included
Total Hβ flux, metallicity as $\zeta_{\rm O}$, and gas density $\rm n_H$.
For photoionization models, ionization parameter and assumed luminosity
($Q(\rm H)$ for stellar populations, $L_{tot}$ for AGN)
For shock models, shock velocity and magnetic field.
Total and dust-depleted abundances as 12+log(X/H)
Relative ionic abundances as $\chi_i/\chi$
Ionic temperatures and densities in units of K and cm$^{-3}$,
respectively.
Files
aa_line_list.md
Files
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Additional details
Identifiers
- arXiv
- arXiv:2412.06763
- Bibcode
- 2025MNRAS.543.3367F
- DOI
- 10.1093/mnras/staf1615
Related works
- Is supplement to
- Journal article: arXiv:2412.06763 (arXiv)
- Publication: 2025MNRAS.543.3367F (Bibcode)
- Publication: 10.1093/mnras/staf1615 (DOI)
Dates
- Submitted
-
2024-12-02
- Accepted
-
2025-08-20
- Issued
-
2025-10-28
References
- Flury, S. R., Arellano-Córdova, K. Z., Moran, E. C., et al. 2025, MNRAS, 543, 4, 3367