Abstract: Primordial black holes (PBHs) are compact objects proposed to have formed in the early Universe from the collapse of small-scale over-densities. Their existence may be detected from the observation of gravitational waves (GWs) emitted by PBH mergers, if the signals can be distinguished from those produced by the merging of astrophysical black holes. In this work, we forecast the capability of the Einstein Telescope, a proposed third-generation GW observatory, to identify and measure the abundance of a subdominant population of distant PBHs, using the difference in the redshift evolution of the merger rate of the two populations as our discriminant. We carefully model the merger rates and generate realistic mock catalogues of the luminosity distances and errors that would be obtained from GW signals observed by the Einstein Telescope. We use two independent statistical methods to analyse the mock data, finding that, with our more powerful, likelihood-based method, PBH abundances as small as fPBH approximate to 7 x 10(-6) ( fPBH approximate to 2 x 10(-6)) would be distinguishable from f(PBH) = 0 at the level of 3 sigma with a one year (ten year) observing run of the Einstein Telescope. Our mock data generation code, darksirens, is fast, easily extendable and publicly available on GitLab.

Abstract: The extraction of the neutrino mass ordering is one of the major challenges in particle physics and cosmology, not only for its implications for a fundamental theory of mass generation in nature, but also for its decisive role in the scale of future neutrinoless double beta decay experimental searches. It has been recently claimed that current oscillation, beta decay and cosmological limits on the different observables describing the neutrino mass parameter space provide robust decisive Bayesian evidence in favor of the normal ordering of the neutrino mass spectrum [1]. We further investigate these strong claims using a rich and wide phenomenology, with different sampling techniques of the neutrino parameter space. Contrary to the findings of Jimenez et al. [1], no decisive evidence for the normal mass ordering is found. Neutrino mass ordering analyses must rely on priors and parameterizations that are ordering-agnostic: robust results should be regarded as those in which the preference for the normal neutrino mass ordering is driven exclusively by the data, while we find a difference of up to a factor of 33 in the Bayes factors among the different priors and parameterizations exploited here. An ordering-agnostic prior would be represented by the case of parameterizations sampling over the two mass splittings and a mass scale, or those sampling over the individual neutrino masses via normal prior distributions only. In this regard, we show that the current significance in favor of the normal mass ordering should be taken as 2.7 sigma (i.e. moderate evidence), mostly driven by neutrino oscillation data. Let us stress that, while current data favor NO only mildly, we do not exclude the possibility that this may change in the future. Eventually, upcoming oscillation and cosmological data may (or may not) lead to a more significant exclusion of IO.

Abstract: This work presents the methodology used to expand the capabilities of the Monte Carlo code OpenMC for the calculation of reactor kinetic parameters: effective delayed neutron fraction beff and neutron generation time L. The modified code, OpenMC(Time-Dependent) or OpenMC(TD), was then used to calculate the effective delayed neutron fraction by using the prompt method, while the neutron generation time was estimated using the pulsed method, fitting L to the decay of the neutron population. OpenMC(TD) is intended to serve as an alternative for the estimation of kinetic parameters when licensed codes are not available. The results obtained are compared to experimental data and MCNP calculated values for 18 benchmark configurations.