GPry efficiently obtains marginal quantities from computationally expensive likelihoods. It works best with smooth (continuous) likelihoods and posteriors that are slow to converge by other methods, which is dependent on the number of dimensions and expected shape of the posterior distribution. The likelihood should be low-dimensional (d<20 as a rule of thumb), though the code may still provide considerable improvements in speed in higher dimensions, despite an increase in the computational overhead of the algorithm. GPry is an alternative to samplers such as MCMC and Nested Sampling with a goal of speeding up inference in cosmology, though the software will work with any likelihood that can be called as a python function. It uses Cobaya's (ascl:1910.019) model framework so all of Cobaya's inbuilt likelihoods work, too.

The SIGWAY data analysis pipeline computes second-order, scalar induced gravitational wave signals emitted by curvature perturbations in the early universe. The package solves the Mukhanov-Sasaki equation for single field ultra-slow roll inflationary models and computes the primordial scalar power spectrum P_ζ. SIGWAY also computes the second order gravitational wave power spectrum Ω_GW from P _ζ for reentry during radiation domination or a phase of early matter domination.