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Bayesian estimation of the specific shear and bulk viscosity of the quark-gluon plasma

<p>This repository contains all data necessary to reproduce Bayesian parameter estimates of a computational model of relativistic heavy-ion collisions.</p> <p>The computational collision model which generated the raw data is available at&nbsp;<a href="https://github.com/Duke-QCD/hic-eventgen">https://github.com/Duke-QCD/hic-eventgen</a>.&nbsp; The analysis code which postprocessed the raw data and performed the parameter estimation is available at&nbsp;<a href="https://github.com/jbernhard/hic-param-est">https://github.com/jbernhard/hic-param-est</a>.</p> <p>For more information, see the author&#39;s dissertation,&nbsp;<a href="https://arxiv.org/abs/1804.06469">Bayesian parameter estimation for relativistic heavy-ion collisions (arXiv:1804.06469 [nucl-th])</a>.&nbsp; In particular, chapter 3 describes the computational collision model, chapter 4 describes the parameter estimation method, and section 5.3 presents the results based on this dataset.</p> <p><strong>Usage</strong></p> <p>hic-param-est-cache.tar.gz is designed to be used with the analysis code (<a href="https://github.com/jbernhard/hic-param-est">https://github.com/jbernhard/hic-param-est</a>).<br> See the documentation at&nbsp;<a href="http://qcd.phy.duke.edu/hic-param-est">http://qcd.phy.duke.edu/hic-param-est</a>.&nbsp; After downloading the code, extract the data archive in the hic-param-est folder.&nbsp; This will create the cache directory containing the parameter design files, model calculations, and experimental data.&nbsp; Note that this data archive includes Python pickle files created by <a href="https://joblib.readthedocs.io/en/latest/persistence.html">joblib</a>, which is included with <a href="https://scikit-learn.org">scikit-learn</a>, a dependency of the analysis code.</p> <p>alternate-format.hdf contains the same data&nbsp;in HDF5 format.&nbsp; This is not intended for use directly with the analysis code, but may be more convenient for other purposes.</p> <p>chain.hdf contains the posterior distribution sample (the &quot;chain&quot;) generated by MCMC sampling in HDF5 format.&nbsp; It may be used with the analysis code by placing it in a subfolder &quot;mcmc&quot; in the hic-param-est folder.&nbsp; It can also be regenerated by the analysis code, although this can take a long time.</p>

ShareScore

28/100

Overall dataset sharing score

Score breakdown

These five areas show where the dataset supports — or may limit — practical reuse.

Stewardship
8
Harmonization
4
Access
16
Reuse readiness
0
Engagement
0

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