Tutorials

In NMMA, it is possible to use the results from GRB, kilonova and GRB afterglow inferences to get estimates on the binary properties. This is based on phenomenological relations, i.e., via fits based on numerical-relativity relations. The dynamical ejecta mass, \(M_{ej}^{dyn}\), is connected to the binary properties through quasi-universal relations.

For the GW-EM resampling, the following input files are required:

• EMsamples - is the posterior sample file from a previous Bayesian inference (e.g. Kilonova+GRB inference) on electromagnetic (EM) signals,
• EMprior - is the prior file that was used for the previous EM inference
• EOS - number of equation of state (EOS) files used in the resampling,
• EOSpath - path to the folder of all EOS files,
• GWsamples - some fiducial randomly generated posterior samples for masses \(m_{1,2}\), chirp mass \(\mathcal{M}_{c}\), mass ratio \(q\), luminosity distance \(D_{L}\), and EOS samples,
• GWprior - a prior file for sources observed via gravitational waves

Here, we illustrate the resampling on the example of a previous Bayesian inference on the observed data of the event GRB211211A, see section Combined light curve inference.

For the GWsamples input file, we need to generate some fiducial dummy GW samples. A script for the generation can be found here.

Finally, to run the GW-EM-resampling, we can use this command:

mpiexec -np 6 gwem_resampling --outdir outdir --GWsamples ./GWsamples.dat --GWprior ./GW.prior --EMsamples ./GRB211211A_posterior_samples.dat --EOSpath ./15nsat_cse_uniform_R14/macro/ --Neos 5000 --EMprior ./Bu2019lm_TrPi2018GRB211211A.prior --nlive 1024