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[ascl:1910.019]
Cobaya: Bayesian analysis in cosmology

Cobaya (Code for BAYesian Analysis) provides a framework for sampling and statistical modeling and enables exploration of an arbitrary prior or posterior using a range of Monte Carlo samplers, including the advanced MCMC sampler from CosmoMC (ascl:1106.025) and the advanced nested sampler PolyChord (ascl:1502.011). The results of the sampling can be analyzed with GetDist (ascl:1910.018). It supports MPI parallelization and is highly extensible, allowing the user to define priors and likelihoods and create new parameters as functions of other parameters.

It includes interfaces to the cosmological theory codes CAMB (ascl:1102.026) and CLASS (ascl:1106.020) and likelihoods of cosmological experiments, such as Planck, Bicep-Keck, and SDSS. Automatic installers are included for those external modules; Cobaya can also be used as a wrapper for cosmological models and likelihoods, and integrated it in other samplers and pipelines. The interfaces to most cosmological likelihoods are agnostic as to which theory code is used to compute the observables, which facilitates comparison between those codes. Those interfaces are also parameter-agnostic, allowing use of modified versions of theory codes and likelihoods without additional editing of Cobaya’s source.

[ascl:2212.006]
GPry: Bayesian inference of expensive likelihoods with Gaussian processes

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.

[submitted]
extrapops: fast simulation and analysis of extra-galactic binary GW sources

This package contains tools for simulating extra-galactic populations of gravitational waves sources (at the moment BBH only) and model their emission during the inspiral phase. It can approximately assess the detectability of individual sources by LISA, and compute the background due to unresolved sources in the LISA band using different methods. The simulated populations can be saved in a format compatible with LISA LDC.

The current BBH models are based on arXiv:2111.03634 and references therein, and the implementation is based on work in collaboration with Stanislav Babak, Chiara Caprini, Daniel Figueroa, Nikolaos Karnesis, Paolo Marcoccia, Germano Nardini, Mauro Pieroni, Angelo Ricciardone and Alberto Sesana.

Simulations are well calibrated to produce accurate background calculations and fair random generation at the tails of the distributions (important for accurate probability of detectable events). This code uses a number of ad-hoc techniques for rapid simulation (O(1min) for large LISA-relevant populations). There is a lot of room for further optimisation, up to almost 1 order of magnitude, if required (please, get in touch).