software . 2020

H0LiCOW distance likelihoods in MontePython

Stefan Taubenberger; Sherry H. Suyu;
Open Access
  • Published: 05 Feb 2020
  • Publisher: Zenodo
Abstract
Implementation of the 6-lens likelihoods of the H0LiCOW lensing distance measurements in the MontePython software (tested in MontePython 3.1.0). The implementation is available at: https://github.com/shsuyu/H0LiCOW-public/tree/master/MontePython_cosmo_sampling If you make use of the distance measurements (time-delay distance and/or lens angular diameter distance) to the 6 lens systems from H0LiCOW, please cite the relevant publications: Suyu et al. 2010 (B1608+656 time-delay distance fit) Jee et al. 2019 (B1608+656 angular diameter distance fit) Chen et al. 2019, Wong et al. 2017 (HE0435-1223 distance posterior) Birrer et al. 2019 (J1206+4332 distance posterior) Chen et al. 2019, Suyu et al. 2014 (RXJ1131-1231 distance posterior) Chen et al. 2019 (PG1115+080 distance posterior) Rusu et al. 2019 (WFI2033-4723 distance posterior) Wong et al. 2019 (combined inference) For MontePython (Brinckmann & Lesgourgues 2019; Audren et al. 2013), please see: https://github.com/brinckmann/montepython_public
Subjects
free text keywords: H0LiCOW, Cosmology
Funded by
EC| LENSNOVA
Project
LENSNOVA
Cosmic Fireworks Première: Unravelling Enigmas of Type Ia Supernova Progenitor and Cosmology through Strong Lensing
  • Funder: European Commission (EC)
  • Project Code: 771776
  • Funding stream: H2020 | ERC | ERC-COG
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Software . 2020
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