Related papers: The nuclear reaction network WinNet
In this work, we explore the use of deep learning techniques to learn how nuclear cross sections change as we add or remove protons and neutrons. As a proof of principle, we focus on the neutron-induced reactions in the fast energy regime.…
This work belongs to a series of articles which have been dedicated to the combination of signed particles and neural networks to speed up the time-dependent simulation of quantum systems. More specifically, the suggested networks are…
Motivation: A Chemical Reaction Network (CRN) is a set of chemical reactions, which can be very complex and difficult to analyze. Indeed, dynamical properties of CRNs can be described by a set of non-linear differential equations that…
Nucleon self-energies and interaction potentials in supernova (SN) matter, which are known to have an important effect on nucleosynthesis conditions in SN ejecta are investigated. Corresponding weak charged-current interaction rates with…
In this and a companion paper we outline a general framework for the thermodynamic description of open chemical reaction networks, with special regard to metabolic networks regulating cellular physiology and biochemical functions. We first…
Heavy elements like gold, platinum or uranium are produced in the r-process, which needs neutron-rich and explosive environments. Neutron star mergers are a promising candidate for an r-process site. They exhibit three different channels…
We explore the sensitivity of the nucleosynthesis of intermediate mass elements (28 < A < 80) in supernovae derived from massive stars to the nuclear reaction rates employed in the model. Two standard sources of reaction rate data (Woosley…
The theoretical predictions of the primordial abundances of elements in the big-bang nucleosynthesis (BBN) are dominated by uncertainties in the input nuclear reaction rates. We investigate the effect of modifying these reaction rates on…
A study of the inelastic scattering of neutrons with an energy of $14.1$~MeV on the nuclei of oxygen, phosphorus and sulfur was carried out at the TANGRA facility at JINR (Dubna). The purpose of the experiment was to refine existing and…
Nucleosynthesis beyond Fe poses additional challenges not encountered when studying astrophysical processes involving light nuclei. Generally higher temperatures and nuclear level densities lead to stronger contributions of transitions on…
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…
Reaction virtual screening and discovery are fundamental challenges in chemistry and materials science, where traditional graph neural networks (GNNs) struggle to model multi-reactant interactions. In this work, we propose ChemHGNN, a…
Single-step retrosynthesis aims to predict a set of reactions that lead to the creation of a target molecule, which is a crucial task in molecular discovery. Although a target molecule can often be synthesized with multiple different…
Chemical reaction network theory is a powerful framework to describe and analyze chemical systems. While much about the concentration profile in an equilibrium state can be determined in terms of the graph structure, the overall reaction's…
Interatomic potentials learned using machine learning methods have been successfully applied to atomistic simulations. However, accurate models require large training datasets, while generating reference calculations is computationally…
Neutrino flow is the dominant mechanism of energy transfer in the latest stages of supernovae explosions and in compact stars. The Standard Model of particle physics and accelerator data, provide a satisfactory description of neutrino…
We review the present status of the theory of high energy reactions with semi-exclusive nucleon electro-production from nuclear targets. We demonstrate how the increase of transferred energies in these reactions opens a complete new window…
Experimental and theoretical results of the $P_{\mathrm{CN}}$ fusion probability of reactants in the entrance channel and the $W_{\mathrm{sur}}$ survival probability against fission at deexcitation of the compound nucleus formed in…
Network inference approaches are widely used to shed light on regulatory interplay between molecular players such as genes and proteins. Biochemical processes underlying networks of interest (e.g. gene regulatory or protein signalling…
This paper is concerned with the utilization of deterministically modeled chemical reaction networks for the implementation of (feed-forward) neural networks. We develop a general mathematical framework and prove that the ordinary…