Software Open Access
H0LiCOW cosmological parameter sampling software
Martin Millon;
Vivien Bonvin
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<dct:title>H0LiCOW cosmological parameter sampling software</dct:title>
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<dct:description><p>Python notebook for H<sub>0</sub> inference using H0LiCOW collaboration&#39;s 6-lens distance measurements.&nbsp; The python notebook is also available here:<br> https://github.com/shsuyu/H0LiCOW-public/tree/master/H0_inference_code<br> <br> The posterior distributions of the time-delay distances and angular diameter distances for five of the six lens systems can be downloaded here:<br> https://github.com/shsuyu/H0LiCOW-public/tree/master/h0licow_distance_chains<br> The remaining lens (B1608+656) has an analytical fit to the PDF.</p> <p>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:</p> <ul> <li><a href="https://ui.adsabs.harvard.edu/abs/2010ApJ...711..201S/abstract">Suyu et al. 2010</a> (B1608+656 time-delay distance fit)</li> <li><a href="https://ui.adsabs.harvard.edu/abs/2019Sci...365.1134J/abstract">Jee et al. 2019</a> (B1608+656 angular diameter distance fit)</li> <li><a href="https://ui.adsabs.harvard.edu/abs/2019MNRAS.490.1743C/abstract">Chen et al. 2019</a>, <a href="https://ui.adsabs.harvard.edu/abs/2017MNRAS.465.4895W/abstract">Wong et al. 2017</a> (HE0435-1223 distance posterior)</li> <li><a href="https://ui.adsabs.harvard.edu/abs/2019MNRAS.484.4726B/abstract">Birrer et al. 2019</a> (J1206+4332 distance posterior)</li> <li><a href="https://ui.adsabs.harvard.edu/abs/2019MNRAS.490.1743C/abstract">Chen et al. 2019</a>, <a href="https://ui.adsabs.harvard.edu/abs/2014ApJ...788L..35S/abstract">Suyu et al. 2014</a> (RXJ1131-1231 distance posterior)</li> <li><a href="https://ui.adsabs.harvard.edu/abs/2019MNRAS.490.1743C/abstract">Chen et al. 2019</a> (PG1115+080 distance posterior)</li> <li><a href="https://arxiv.org/abs/1905.09338">Rusu et al. 2019</a> (WFI2033-4723 distance posterior)</li> <li><a href="https://arxiv.org/abs/1907.04869">Wong et al. 2019</a> (combined inference)</li> </ul> <p>The H<sub>0</sub> inference from these posteriors can be obtained following the python notebook.&nbsp; The cosmological parameter chains from running the python notebook are available here:<br> https://github.com/shsuyu/H0LiCOW-public/tree/master/cosmo_parameter_chains</p></dct:description>
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| Data volume | 17.6 MB | 17.6 MB |
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Indexed in
- Publication date:
- February 5, 2020
- DOI:
-
- Keyword(s):
- H0LiCOW Cosmology Hubble constant
- Grants:
-
European Commission:
- COSMICLENS - Cosmology with Strong Gravitational Lensing (787886)
- COSMOGRAIL: Cosmology with Time Delays in Gravitationally Lensed Quasars (200020_172712)
- Related identifiers:
- Derived from
- License (for files):
- Creative Commons Attribution 4.0 International