Bayesian inference of multimessenger astrophysical data: Joint and coherent inference of gravitational waves and kilonovae

We release the set of about 10M equations of state (EOS) used in the paper Bayesian inference of multimessenger astrophysical data: Joint and coherent inference of gravitational waves and kilonovae Breschi et al. The EOS set is generated with a Markov Chain Monte Carlo approach by fixing the crust EOS and assuming i) general relativity; ii) causality at higher densities. Hence, it is agnostic on nuclear physics and not affected by nuclear physics uncertainties. The set includes EOS with and without first order phase transition. Please see On the maximum mass of neutron stars and GW190814 Godzieba et al. (also arxiv link) The EOS are four-pieces piecewise polytropes. There are 4 adiabatic indices and three transition densities where the adiabatic index changes. The first index is for the crust EOS and is fixed for all EOSs. The columns of the original txt files are arranged as follows: column 1: G0 (crust adiabatic index) \ column 2: G1 |__________ four adiabatic indices column 3: G2 | column 4: G3 / column 5: log(rho0) \ column 6: log(rho1) |------- log of the three transition densities column 7: log(rho2) / column 8: central density of M = 1.4 Msun neutron star column 9: radius of M = 1.4 Msun neutron star column 10: lambda_2 of M = 1.4 Msun neutron star column 11: central density of maximum mass neutron star column 12: radius of maximum mass neutron star column 13: mass of maximum mass neutron star column 14: maximum sound speed squared divided by the speed of light squared (max(c_s^2)/c^2) of the maximum mass neutron star Each of these columns a dataset of the HDF5. Please cite the two references above if you use the dataset.