Skip to main content

Faraday rotation measurement for pulsars and FRBs

Project description

ascl:2204.008 PyPI Python License

RMNest

RMNest is an open source python package for estimating both standard and generalised rotation measures via direct fits to Stokes Q, U and V spectra.

Installation

The latest release of RMNest can be installed from PyPi by running the following

pip install rmnest

Note that while a working installation of the PSRCHIVE Python-3 bindings is not necessary for using RMNest, it is strongly recommended.

Requirements

The following packages are required to running RMNest.

  • numpy: Array manipulation

  • matplotlib: Modules for plotting

  • bilby: Inference calculations framework

  • dynesty: Modules for nested sampling

Usage

RMNest can be run directly from the command line within using rmnest. As an example, the below command would run a standard rotation-measure fit on the provided test data after frequency-averaging to 128 channels within a [pulse] phase window between phase = 0.45 to 0.55

rmnest archive test/2020-03-16-18\:12\:00.calib.ST -o test/output/ -l testrun --window 0.45:0.55 -f 128

Alternatively, fitting for the generalised form of Faraday rotation, sometimes referred to as Faraday conversion (see e.g. Kennett & Melrose 1998), can be performed by adding the --gfr and --free_alpha flags as

rmnest <archive>.ar -o <outdir> -l testrun --window 0.45:0.55 --gfr --free_alpha

Omitting the --free_alpha flag will result in the spectral exponent being fixed to 3. Details of the underlying phenomenological model can be found in a technical document by Lower (2021).

The likelihood and Faraday rotation models, as well as the general RMFit class in fit_RM.py, can also be imported like any other API.

Issues and Contributing

If you encounter any issues with RMNest, or have in mind a feature that currently does not exist, then you can contribute by openning a Github Issue and outlining the feature.

Referencing RMNest

If you make use of RMNest in your research, we would greatly appreciate it if you cite both the ASCL entry (Lower et al. 2022) and the papers behind its development.

@software{2022ascl.soft04008L,
       author = {{Lower}, Marcus E. and {Kumar}, Pravir and {Shannon}, Ryan M.},
        title = "{RMNest: Bayesian approach to measuring Faraday rotation and conversion in radio signals}",
     keywords = {Software},
 howpublished = {Astrophysics Source Code Library, record ascl:2204.008},
         year = 2022,
        month = apr,
          eid = {ascl:2204.008},
        pages = {ascl:2204.008},
archivePrefix = {ascl},
       eprint = {2204.008},
       adsurl = {https://ui.adsabs.harvard.edu/abs/2022ascl.soft04008L},
      adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}

For standard rotation measure fitting, then please cite Bannister et al. (2019).

@ARTICLE{2019Sci...365..565B,
       author = {{Bannister}, K.~W. and {Deller}, A.~T. and {Phillips}, C. and {Macquart}, J. -P. and {Prochaska}, J.~X. and {Tejos}, N. and {Ryder}, S.~D. and {Sadler}, E.~M. and {Shannon}, R.~M. and {Simha}, S. and {Day}, C.~K. and {McQuinn}, M. and {North-Hickey}, F.~O. and {Bhandari}, S. and {Arcus}, W.~R. and {Bennert}, V.~N. and {Burchett}, J. and {Bouwhuis}, M. and {Dodson}, R. and {Ekers}, R.~D. and {Farah}, W. and {Flynn}, C. and {James}, C.~W. and {Kerr}, M. and {Lenc}, E. and {Mahony}, E.~K. and {O'Meara}, J. and {Os{\l}owski}, S. and {Qiu}, H. and {Treu}, T. and {U}, V. and {Bateman}, T.~J. and {Bock}, D.~C. -J. and {Bolton}, R.~J. and {Brown}, A. and {Bunton}, J.~D. and {Chippendale}, A.~P. and {Cooray}, F.~R. and {Cornwell}, T. and {Gupta}, N. and {Hayman}, D.~B. and {Kesteven}, M. and {Koribalski}, B.~S. and {MacLeod}, A. and {McClure-Griffiths}, N.~M. and {Neuhold}, S. and {Norris}, R.~P. and {Pilawa}, M.~A. and {Qiao}, R. -Y. and {Reynolds}, J. and {Roxby}, D.~N. and {Shimwell}, T.~W. and {Voronkov}, M.~A. and {Wilson}, C.~D.},
        title = "{A single fast radio burst localized to a massive galaxy at cosmological distance}",
      journal = {Science},
     keywords = {ASTRONOMY, Astrophysics - High Energy Astrophysical Phenomena, Astrophysics - Cosmology and Nongalactic Astrophysics},
         year = 2019,
        month = aug,
       volume = {365},
       number = {6453},
        pages = {565-570},
          doi = {10.1126/science.aaw5903},
archivePrefix = {arXiv},
       eprint = {1906.11476},
 primaryClass = {astro-ph.HE},
       adsurl = {https://ui.adsabs.harvard.edu/abs/2019Sci...365..565B},
      adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}

If you used RMNest for generalised Faraday rotation measure fitting, please include a citation to Lower (2021).

@ARTICLE{2021arXiv210809429L,
       author = {{Lower}, Marcus E.},
        title = "{A phenomenological model for measuring generalised Faraday rotation}",
      journal = {arXiv e-prints},
     keywords = {Astrophysics - High Energy Astrophysical Phenomena},
         year = 2021,
        month = aug,
          eid = {arXiv:2108.09429},
        pages = {arXiv:2108.09429},
archivePrefix = {arXiv},
       eprint = {2108.09429},
 primaryClass = {astro-ph.HE},
       adsurl = {https://ui.adsabs.harvard.edu/abs/2021arXiv210809429L},
      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

rmnest-0.3.1.tar.gz (13.7 kB view details)

Uploaded Source

Built Distribution

rmnest-0.3.1-py3-none-any.whl (11.8 kB view details)

Uploaded Python 3

File details

Details for the file rmnest-0.3.1.tar.gz.

File metadata

  • Download URL: rmnest-0.3.1.tar.gz
  • Upload date:
  • Size: 13.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.18

File hashes

Hashes for rmnest-0.3.1.tar.gz
Algorithm Hash digest
SHA256 c30feeaf1f5b78008f98d3507990de01f2b6370ee56a8d1679993a87804a2f4b
MD5 97920ab49fadd317fd25c45bbbe1096a
BLAKE2b-256 8a44c4137abb681cec92adcc551118fb3ba7404ad1212b33fef4d2fc2e30a931

See more details on using hashes here.

File details

Details for the file rmnest-0.3.1-py3-none-any.whl.

File metadata

  • Download URL: rmnest-0.3.1-py3-none-any.whl
  • Upload date:
  • Size: 11.8 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.18

File hashes

Hashes for rmnest-0.3.1-py3-none-any.whl
Algorithm Hash digest
SHA256 3b2f1fbeee76c04fc5da3519aacfeeb8d59ed59be6d81b3c06b5881e3a0c61fd
MD5 0e62d6dfc347696efea3b12fb43602bc
BLAKE2b-256 fcbd00e785631b6584d84bb9bb4c2fa4e3fb48eddddb3e00f670c9cfdd3acf3d

See more details on using hashes here.

Supported by

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