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 <a href="https://github.com/Duke-QCD/hic-eventgen">https://github.com/Duke-QCD/hic-eventgen</a>. The analysis code which postprocessed the raw data and performed the parameter estimation is available at <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's dissertation, <a href="https://arxiv.org/abs/1804.06469">Bayesian parameter estimation for relativistic heavy-ion collisions (arXiv:1804.06469 [nucl-th])</a>. 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 <a href="http://qcd.phy.duke.edu/hic-param-est">http://qcd.phy.duke.edu/hic-param-est</a>. After downloading the code, extract the data archive in the hic-param-est folder. This will create the cache directory containing the parameter design files, model calculations, and experimental data. 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 in HDF5 format. 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 "chain") generated by MCMC sampling in HDF5 format. It may be used with the analysis code by placing it in a subfolder "mcmc" in the hic-param-est folder. 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