Tutorials

To run efficiently, parallel bilby requires some preparatory work, just as efficient construction work requires some preparatory logistical planning. Fortunately, you do not need to do this on your own. Instead, you can outsource this task to a parallel_bilby_generation command, which will meet your initial demands if they are well specified in a configuration file. You will find this mostly referred to as config.ini. It should be used to specify non-default arguments that are taken by parallel_bilby_generation. Several default values are taken from bilby_pipe, too. Find below some recommended configurations that should comprise your .ini, but see the parallel_bilby-[https://lscsoft.docs.ligo.org/parallel_bilby/examples.html|docs]], too.

trigger_time = 0

For realistic data, this should be set to GPS time, e.g. 1187008882.43 for GW170817. For injection studies, it will mostly suffice to set the value to 0.

detectors = [ET1, ET2, ET3]
psd_dict = {ET1=bilby/bilby/gw/detector/noise_curves/ET_D_psd.txt,   
ET2=bilby/bilby/gw/detector/noise_curves/ET_D_psd.txt,   
ET3=bilby/bilby/gw/detector/noise_curves/ET_D_psd.txt}

The power spectral density (PSD) characterises the assumed noise level in the detectors. It needs to be adopted to the detectors in use, in this example the Einstein Telescope. Other PSDs can be found in the same directory bilby/bilby/gw/detector/noise_curves/. If you already have a signal available, you would need to submit it in a data_dict.

distance-marginalization=False 
phase-marginalization=True
time-marginalization=False
likelihood-type = ROQGravitationalWaveTransient
roq-folder = [SOME_PATH]/roqs

We can marginalise our likelihood over some parameters, simply by integrating over their support. This makes sense when we are not really interested in them, e.g. because they have no intrinsing meaning to the system.

Using Reduced-order quadratures (ROQs) will speedup your inference significantly. The idea is to reduce the cost of likelihood evaluations by including a data-dependent basis for the computation of the likelihood integration. Their use is thefore highly encouraged. However, they require a lot of memory and should be adapted to the expected parameter space, implying constraints on the prior. As of 2022, constructing advanced ROQs is a global community effort. Some early ROQs can be found here. Ask your supervisor for up-to-date repositories.

=== Prior arguments===
prior-file = bilby/bilby/gw/prior_files/aligned_spins_bns.prior

You will need to specify the prior from which samples are drawn. This needs to be compatible with the bilby.Prior-class.

label = inj
outdir = outdir

You may want to assign unique labels and directory names do quickly identify different runs.