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H0LiCOW cosmological parameter sampling software

Martin Millon; Vivien Bonvin


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        "affiliation": "Ecole Polytechnique F\u00e9d\u00e9rale de Lausanne", 
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    "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>\nhttps://github.com/shsuyu/H0LiCOW-public/tree/master/H0_inference_code<br>\n<br>\nThe posterior distributions of the time-delay distances and angular diameter distances for five of the six lens systems can be downloaded here:<br>\nhttps://github.com/shsuyu/H0LiCOW-public/tree/master/h0licow_distance_chains<br>\nThe remaining lens (B1608+656) has an analytical fit to the PDF.</p>\n\n<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>\n\n<ul>\n\t<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>\n\t<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>\n\t<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>\n\t<li><a href=\"https://ui.adsabs.harvard.edu/abs/2019MNRAS.484.4726B/abstract\">Birrer et al. 2019</a> (J1206+4332 distance posterior)</li>\n\t<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>\n\t<li><a href=\"https://ui.adsabs.harvard.edu/abs/2019MNRAS.490.1743C/abstract\">Chen et al. 2019</a> (PG1115+080 distance posterior)</li>\n\t<li><a href=\"https://arxiv.org/abs/1905.09338\">Rusu et al. 2019</a> (WFI2033-4723 distance posterior)</li>\n\t<li><a href=\"https://arxiv.org/abs/1907.04869\">Wong et al. 2019</a> (combined inference)</li>\n</ul>\n\n<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>\nhttps://github.com/shsuyu/H0LiCOW-public/tree/master/cosmo_parameter_chains</p>"
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