Skip to main content

non-parametric gas-phase metallicity and electron temperature estimation

Project description

genesis-metallicity

LICENSE arXiv

non-parametric gas-phase metallicity and electron temperature estimation

  • strong-line metallicity etstimation when temperature-sensitive emission lines are unavailable
  • direct-method metallicity measurement when the temperature-sensetive [O III]4363 line is detected (can also include [O II]7320,30 if available)
  • O⁺ electron temperature estimation from that of the O⁺⁺ zone when direct measurements of the former are unavailable
  • dust reddening correction of the observed emission line fluxes when multiple Balmer lines are detected

Calibration data: The calibration data will be publicly released upon the journal publication of the associated paper. In the meantime, do not hesitate to get in touch if you are interested in using this data in your work: danial.langeroodi@nbi.ku.dk

Real-valued 5D and 4D images of our electron temperature and gas-phase metallicity KDEs are available in the images/ directory.

Installation

genesis_metallicity is pip installable:

pip install genesis_metallicity

It is recommended to keep the package up to date to use the largest available calibration sample. If you have an older version installed, you can install the most recent version by:

pip uninstall -y genesis_metallicity
pip install --upgrade genesis_metallicity

You can check the installed version by

import genesis_metallicity
print(genesis_metallicity.__version__)

Examples

strong-line metallcitiy estimation

The following is an example of "strong-line" metallicity estimation. The emission line measurements are imported into a Python dictionary, where a Python list with two items is entered for each emission line: the first item corresponds to the measured line flux, and the second item corresponds to the flux uncertainty. Note that providing the object ID and redshift, as done below, is optional and intended only to assist with bookkeeping.

Providing EW(Hβ) measurements is recommended but not strictly required. If EW(Hβ) measurements are not available, simply do not provide them in the dictionary below; the metallicity estimator will instead adopt an EW(Hβ)-independent calibration. This applies to other modules as well.

from genesis_metallicity.genesis_metallicity import genesis_metallicity

object = '1180_40000170'

input_dict = {}
input_dict['redshift'] = 9.43
input_dict['OII']      = [7.269250230638606e-20, 5.7108025103430405e-21]
input_dict['Hdelta']   = [1.592676517913214e-19, 4.405126486743839e-21]
input_dict['Hgamma']   = [2.6671788939798604e-19, 5.274969458136735e-21]
input_dict['Hbeta']    = [6.447421960287729e-19, 6.48899753642406e-21]
input_dict['O4959']    = [1.0763985148795857e-18, 8.773228322203986e-21]
input_dict['O5007']    = [3.0628160287038502e-18, 1.0895841873808477e-20]
input_dict['Hbeta_EW'] = [158.728418552416, 13.991218097105634]

galaxy = genesis_metallicity(input_dict, object=object)
print(' -> strong-line metallicity:', galaxy.metallicity)
print(' -> strong-line metallicity (nominal value):', galaxy.metallicity.n)
print(' -> strong-line metallicity (standard deviation):', galaxy.metallicity.s)

direct-method metallicity measurement

If the temperature-sensitive [O III]4363 emission line is detected, the gas-phase metallicity can be measured directly. This is demonstrated in the example below, where the input emission lines remain the same as in the previous example, but with the addition of the [O III]4363 flux.

from genesis_metallicity.genesis_metallicity import genesis_metallicity

object = '1180_40000170'

input_dict = {}
input_dict['redshift'] = 9.43
input_dict['OII']      = [7.269250230638606e-20, 5.7108025103430405e-21]
input_dict['Hdelta']   = [1.592676517913214e-19, 4.405126486743839e-21]
input_dict['Hgamma']   = [2.6671788939798604e-19, 5.274969458136735e-21]
input_dict['O4363']    = [7.1092219385595e-20, 5.0986852540807764e-21]
input_dict['Hbeta']    = [6.447421960287729e-19, 6.48899753642406e-21]
input_dict['O4959']    = [1.0763985148795857e-18, 8.773228322203986e-21]
input_dict['O5007']    = [3.0628160287038502e-18, 1.0895841873808477e-20]
input_dict['Hbeta_EW'] = [158.728418552416, 13.991218097105634]

galaxy = genesis_metallicity(input_dict, object=object)
print(' -> direct-method metallicity:', galaxy.metallicity)
print(' -> direct-method metallicity (nominal value):', galaxy.metallicity.n)
print(' -> direct-method metallicity (standard deviation):', galaxy.metallicity.s)

electron temperature estimation

It’s often desirable to estimate the O⁺ electron temperature (t2) from the directly measured O⁺⁺ electron temperature (t3). This is particularly the case at high redshifts, where the t3 can be measured directly from the [O III]4363 line, while the t2 cannot be measured directly because the [O II]7320,30 doublet is often too faint or redshifted out of coverage. In such cases, the t2 estimations are carried out automatically by genesis_metallicity; the measured electron temperatures can be accessed as shown below.

from genesis_metallicity.genesis_metallicity import genesis_metallicity

object = '1180_40000170'

input_dict = {}
input_dict['redshift'] = 9.43
input_dict['OII']      = [7.269250230638606e-20, 5.7108025103430405e-21]
input_dict['Hdelta']   = [1.592676517913214e-19, 4.405126486743839e-21]
input_dict['Hgamma']   = [2.6671788939798604e-19, 5.274969458136735e-21]
input_dict['O4363']    = [7.1092219385595e-20, 5.0986852540807764e-21]
input_dict['Hbeta']    = [6.447421960287729e-19, 6.48899753642406e-21]
input_dict['O4959']    = [1.0763985148795857e-18, 8.773228322203986e-21]
input_dict['O5007']    = [3.0628160287038502e-18, 1.0895841873808477e-20]
input_dict['Hbeta_EW'] = [158.728418552416, 13.991218097105634]

galaxy = genesis_metallicity(input_dict, object=object)
print('--------------------------------------------------------------------------')
print(' -> O++ electron temperature' )
print(' -> direct-method te(OIII) [K]:', galaxy.t3)
print(' -> direct-method te(OIII) [K] (nominal value):', galaxy.t3.n)
print(' -> direct-method te(OIII) [K] (standard deviation):', galaxy.t3.s)
print('--------------------------------------------------------------------------')
print(' -> O+ electron temperature' )
print(' -> direct-method te(OII) [K]:', galaxy.t2)
print(' -> direct-method te(OII) [K] (nominal value):', galaxy.t2.n)
print(' -> direct-method te(OII) [K] (standard deviation):', galaxy.t2.s)
print('--------------------------------------------------------------------------')

dust reddening correction

By default, genesis_metallicity assumes that the input emission line fluxes are the observed values without any reddening correction (this behavior can be modified by the user; see the end of the next paragraph). As such, the input line fluxes are automatically corrected for dust reddening. The meaured V-band attenuation as well as the reddening-corrected emission line fluxes can be accessed as shown below. If the line of interest is included in the data/lines.py script, its flux can be included in the input dictionary for reddening correction. Otherwise, the line ID and rest-wavelength have to be added to data/lines.py by the user.

Note that the galaxy.reddening_corrected_lines outpout is a dictionary, where the reddening-corrected line fluxes are stored. For instance, the reddening-corrected flux and flux uncertainty of Hbeta can be accessed as galaxy.reddening_corrected_lines['Hbeta'].n and galaxy.reddening_corrected_lines['Hbeta'].s, respectively. If the input emission lines are already reddening-corrected, the reddening correction can be switched off by setting correct_extinction=False in the main genesis_metallicity function call; i.e., by calling the main routine as genesis_metallicity(input_dict, object=object, correct_extinction=False).

from genesis_metallicity.genesis_metallicity import genesis_metallicity

object = '1180_40000170'

input_dict = {}
input_dict['redshift'] = 9.43
input_dict['OII']      = [7.269250230638606e-20, 5.7108025103430405e-21]
input_dict['Hdelta']   = [1.592676517913214e-19, 4.405126486743839e-21]
input_dict['Hgamma']   = [2.6671788939798604e-19, 5.274969458136735e-21]
input_dict['O4363']    = [7.1092219385595e-20, 5.0986852540807764e-21]
input_dict['Hbeta']    = [6.447421960287729e-19, 6.48899753642406e-21]
input_dict['O4959']    = [1.0763985148795857e-18, 8.773228322203986e-21]
input_dict['O5007']    = [3.0628160287038502e-18, 1.0895841873808477e-20]
input_dict['Hbeta_EW'] = [158.728418552416, 13.991218097105634]

galaxy = genesis_metallicity(input_dict, object=object)
print(' -> Av:', galaxy.Av)
print(' -> reddening-corrected line fluxes:')
print(galaxy.reddening_corrected_lines)

Citation

If you use genesis-metallicity in your research, please reference the associated paper:

@ARTICLE{2024arXiv240907455L,
       author = {{Langeroodi}, Danial and {Hjorth}, Jens},
        title = "{Genesis-Metallicity: Universal Non-Parametric Gas-Phase Metallicity Estimation}",
      journal = {arXiv e-prints},
     keywords = {Astrophysics - Astrophysics of Galaxies},
         year = 2024,
        month = sep,
          eid = {arXiv:2409.07455},
        pages = {arXiv:2409.07455},
archivePrefix = {arXiv},
       eprint = {2409.07455},
 primaryClass = {astro-ph.GA},
       adsurl = {https://ui.adsabs.harvard.edu/abs/2024arXiv240907455L},
      adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}

If you use the direct-method module of genesis-metallicity, in addition to the above please also reference PyNeb:

@ARTICLE{2015A&A...573A..42L,
       author = {{Luridiana}, V. and {Morisset}, C. and {Shaw}, R.~A.},
        title = "{PyNeb: a new tool for analyzing emission lines. I. Code description and validation of results}",
      journal = {\aap},
     keywords = {methods: numerical, atomic data, Hii regions, planetary nebulae: general, ISM: abundances, Astrophysics - Instrumentation and Methods for Astrophysics, Astrophysics - Solar and Stellar Astrophysics},
         year = 2015,
        month = jan,
       volume = {573},
          eid = {A42},
        pages = {A42},
          doi = {10.1051/0004-6361/201323152},
archivePrefix = {arXiv},
       eprint = {1410.6662},
 primaryClass = {astro-ph.IM},
       adsurl = {https://ui.adsabs.harvard.edu/abs/2015A&A...573A..42L},
      adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

genesis_metallicity-1.2.101.tar.gz (185.6 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

genesis_metallicity-1.2.101-py3-none-any.whl (185.0 kB view details)

Uploaded Python 3

File details

Details for the file genesis_metallicity-1.2.101.tar.gz.

File metadata

  • Download URL: genesis_metallicity-1.2.101.tar.gz
  • Upload date:
  • Size: 185.6 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.9.19

File hashes

Hashes for genesis_metallicity-1.2.101.tar.gz
Algorithm Hash digest
SHA256 d28e3e2512f8a61b1d66ab4e9891ced712a2006836e1b84e13fff505d5f3d479
MD5 2e78ded1b7c157f89ad360d302f94690
BLAKE2b-256 7a77abb1c4d7756689cd7f2db1b1219f887a236ce7735d346dfc119897e5de10

See more details on using hashes here.

File details

Details for the file genesis_metallicity-1.2.101-py3-none-any.whl.

File metadata

File hashes

Hashes for genesis_metallicity-1.2.101-py3-none-any.whl
Algorithm Hash digest
SHA256 92ac555a6451f2d37b234c6ed3730d800894f32bdccbeab683b0fa6d9772a9aa
MD5 bd04bc574b6d559be5593261d82000c7
BLAKE2b-256 5a9ed13d47370238d05a393f2bfa51db8202b990ad9ebc93d241aaa0ad4c5d38

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page