Related papers: BBNet: accurate neural network emulator for primor…
We describe a program for computing the abundances of light elements produced during Big Bang Nucleosynthesis which is publicly available at http://parthenope.na.infn.it/. Starting from nuclear statistical equilibrium conditions the program…
In the primordial Big Bang nucleosynthesis (BBN), only the lightest nuclides (D, $^3$He, $^4$He, and $^7$Li) were synthesized in appreciable quantities, and these relics provide us a unique window on the early universe. Currently, BBN…
Big Bang nucleosynthesis (BBN) theory predicts the abundances of the light elements D, $^3$He, $^4$He and $^7$Li produced in the early universe. The primordial abundances of D and $^4$He inferred from observational data are in good…
Training deep learning networks involves continuous weight updates across the various layers of the deep network while using a backpropagation algorithm (BP). This results in expensive computation overheads during training. Consequently,…
We present a neural-network emulator for the thermal and chemical evolution in Population III star formation. The emulator accurately reproduces the thermochemical evolution over a wide density range spanning 21 orders of magnitude…
It has been proposed that the apparent discrepancies between the inferred primordial abundances of 6Li and 7Li and the predictions of big bang nucleosynthesis (BBN) can be resolved by the existence of a negatively-charged massive unstable…
Primordial or big bang nucleosynthesis (BBN) is one of the three historical strong evidences for the big bang model. The recent results by the Planck satellite mission have slightly changed the estimate of the baryonic density compared to…
This paper addresses the challenges of power flow calculation in large scale power systems with high renewable penetration, focusing on computational efficiency and generalization. Traditional methods, while accurate, struggle 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,…
We present new upper and lower bounds to the primordial abundances of deuterium and helium-3 based on observational data from the solar system and the interstellar medium. Independent of any model for the primordial production of the…
We present the Big-Bang Nucleosynthesis (BBN) simulation with a bubble universe scenario around a rotating black hole (BH) in Kerr-AdS$_5$ spacetime to explain recently updated observations of light elements such as the primordial helium…
While deep learning is transforming data analysis in high-energy physics, computational challenges limit its potential. We address these challenges in the context of collider physics by introducing EveNet, an event-level foundation model…
Cosmic microwave background (CMB) determinations of the baryon-to-photon ratio $\eta \propto \Omega_{\rm baryon} h^2$ will remove the last free parameter from (standard) big bang nucleosynthesis (BBN) calculations. This will make BBN a much…
Einstein-Boltzmann Solvers (EBSs) are run on a massive scale by the cosmology community when fitting cosmological models to data. We present a new concept for speeding up such codes with neural networks. The originality of our approach…
Binary Neural Networks (BNNs) show promising progress in reducing computational and memory costs but suffer from substantial accuracy degradation compared to their real-valued counterparts on large-scale datasets, e.g., ImageNet. Previous…
Bayesian Neural Networks (BNNs) offer a principled and natural framework for proper uncertainty quantification in the context of deep learning. They address the typical challenges associated with conventional deep learning methods, such as…
Big Bang Nucleosynthesis (BBN) and the Cosmic Background Radiation (CBR) provide complementary probes of the early evolution of the Universe and of its particle content. Neutrinos play important roles in both cases, influencing the…
We assess the status of big-bang nucleosynthesis (BBN) in light of the final Planck data release and other recent developments, and in anticipation of future measurements. Planck data fix the cosmic baryon density to 0.9% precision, and…
We describe AlterBBN, a public C program for evaluating the abundances of the elements generated by Big-Bang nucleosynthesis (BBN). This program enables the user to compute the abundances of the elements in the standard model of cosmology,…
Modeling and simulating a power distribution network (PDN) for printed circuit boards (PCBs) with irregular board shapes and multi-layer stackup is computationally inefficient using full-wave simulations. This paper presents a new concept…