Tutorials

NMMA enables to perform parameter estimation in different electromagnetic regimes such as for kilonovae and gamma-ray burst afterglows. Similarly to light curve generation, the following models are available for kilonova inference: Bu2019nsbh (BH-NS model), Bu2019lm (BNS model), Me2017 (BNS model), and Ka2017 (BNS model).

Example: Me2017 Model

This generates a file called injection.json that includes an injection file drawn from the prior file with a number of injections specified by –n-injection.

The injection file generated for a certain kilonova model (see here) can be used to start a Bayesian inference analysis for a kilonovae. An example analysis is as follows:

light_curve_analysis --model Me2017 --svd-path ./svdmodels --outdir outdir --label injection --prior priors/Me2017.prior --tmin 0.1 --tmax 20 --dt 0.5 --error-budget 1 --nlive 512 --Ebv-max 0 --injection ./injection.json --injection-num 0 --injection-outfile outdir/lc.csv --generation-seed 42 --filters u,g,r,i,z,y,J,H,K --plot --remove-nondetections