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We present the first joint-likelihood analysis of Big Bang Nucleosynthesis (BBN) and Cosmic Microwave Background (CMB) data. Bayesian inference is performed on the baryon abundance and the effective number of neutrino species, $N_{\rm…
Since its debut by John Skilling in 2004, nested sampling has proven a valuable tool to the scientist, providing hypothesis evidence calculations and parameter inference for complicated posterior distributions, particularly in the field of…
The Big Bang Nucleosynthesis (BBN) model is a cornerstone for the understanding of the evolution of the early universe, making seminal predictions that are in outstanding agreement with the present observation of light element abundances in…
Big Bang Nucleosynthesis (BBN), as one of the earliest processes in the universe accessible to direct observation, offers a powerful and independent probe of the cosmic expansion history. With recent advances in both theory and observation,…
Big Bang Nucleosynthesis (BBN) is an important stage of a homogeneous and isotropic expanding universe. The results of calculation of the synthesis of light elements during this epoch can then be compared with the abundances of the light…
Big Bang Nucleosynthesis (BBN), the process of creation of lightest elements in the early universe, is a highly robust, precise, and ultimately successful theory that forms one of the three pillars of the standard hot-Big-Bang cosmological…
Primordial nucleosynthesis, or big bang nucleosynthesis (BBN), is one of the three evidences for the big bang model, together with the expansion of the universe and the cosmic microwave background. There is a good global agreement over a…
A simple Java applet is presented which allows quick and easy computation and plotting of the predictions of light element abundances in SBBN, including errors in the predictions propagated from input reaction rates correlated and…
Big Bang Nucleosynthesis (BBN) offers one of the most strict evidences for the Lambda-CDM cosmology at present, as well as the Cosmic Microwave Background (CMB) radiation. In this work, our main aim is to present the outcomes of our…
Primordial nucleosynthesis, or Big-Bang Nucleosynthesis (BBN), is one of the three evidences for the Big-Bang model, together with the expansion of the Universe and the Cosmic Microwave Background. There is a good global agreement over a…
Large reasoning models achieve strong performance on complex tasks by generating extended chains of thought, but they often "overthink": continuing to reason long after they have enough information to answer correctly. This wastes…
This paper is superseded by Arxiv:1911.07334. Big-bang nucleosynthesis (BBN) is a valuable tool to constrain the physics of the early universe and is the only probe of the radiation-dominated epoch. A fundamental assumption in BBN is that…
Big-bang nucleosynthesis (BBN) describes the production of the lightest nuclides via a dynamic interplay among the four fundamental forces during the first seconds of cosmic time. We briefly overview the essentials of this physics, and…
A key pillar of modern cosmology, Big Bang Nucleosynthesis (BBN) offers a probe of the particle content and expansion rate of the Universe a mere few minutes after the beginning. When compared with the BBN predictions, the observationally…
Big bang nucleosynthesis (BBN), an epoch of primordial nuclear transformations in the expanding Universe, has left an observable imprint in the abundances of light elements. Precision observations of such abundances, combined with…
Big Bang Nucleosynthesis (BBN), along with the cosmic background radiation and the Hubble expansion, is one of the pillars ofthe standard, hot, big bang cosmology since the primordial synthesis of the light nuclides (D, $^3$He, $^4$He,…
The conventional Big Bang model successfully anticipates the initial abundances of 2H(D), 3He, and 4He, aligning remarkably well with observational data. However, a persistent challenge arises in the case of 7Li, where the predicted…
jinns is an open-source Python library for physics-informed neural networks, built to tackle both forward and inverse problems, as well as meta-model learning. Rooted in the JAX ecosystem, it provides a versatile framework for efficiently…
We consider Big Bang Nucleosynthesis (BBN) with long lived charged massive particles. Before decaying, the long lived charged particle recombines with a light element to form a bound state like a hydrogen atom. This effect modifies the…
BlackJAX is a library implementing sampling and variational inference algorithms commonly used in Bayesian computation. It is designed for ease of use, speed, and modularity by taking a functional approach to the algorithms' implementation.…