Related papers: Towards next-generation optical potentials for nuc…
Optical-model potentials (OMPs) continue to play a key role in nuclear reaction calculations. However, the uncertainty of phenomenological OMPs in widespread use -- inherent to any parametric model trained on data -- has not been fully…
We review recent progress and motivate the need for further developments in nuclear optical potentials that are widely used in the theoretical analysis of nucleon elastic scattering and reaction cross sections. In regions of the nuclear…
Background: Recent high-precision measurements of alpha-induced reaction data below the Coulomb barrier have pointed out questions of the alpha-particle optical-model potential (OMP) which are yet open within various mass ranges. Purpose:…
The optical potential is a powerful instrument for calculations on a wide variety of nuclear reactions, in particular, for quasi-elastic lepton-nucleus scattering. Phenomenological optical potentials are successful in the description of…
Machine learning potentials have revolutionised the field of atomistic simulations in recent years and are becoming a mainstay in the toolbox of computational scientists. This paper aims to provide an overview and introduction into machine…
This chapter presents an overview of the optical model description of nucleon-nucleus scattering and reactions based on fundamental nuclear two-body and many-body forces. The chapter begins with a historical review followed by a discussion…
The introduction of modern Machine Learning Potentials (MLP) has led to a paradigm change in the development of potential energy surfaces for atomistic simulations. By providing efficient access to energies and forces, they allow to perform…
The recent high-precision measurements of alpha-particle induced reaction data below the Coulomb barrier (B) make possible the understanding of limits and possible improvement of a previous optical model potential (OMP) for alpha-particles…
Over the past decade inter-atomic potentials based on machine-learning (ML) techniques have become an indispensable tool in the atomic-scale modeling of materials. Trained on energies and forces obtained from electronic-structure…
Optical potentials are a standard tool in the study of nuclear reactions, as they describe the interaction between a target nucleus and a projectile. The use of phenomenological optical potentials built using experimental data on stable…
Recent years have witnessed the fast development of machine learning potentials (MLPs) and their widespread applications in chemistry, physics, and material science. By fitting discrete ab initio data faithfully to continuous and…
The nuclear optical model potential (OMP) is generally assumed to be independent of the orbital angular momentum, $l$, of the interacting nuclei. Nucleon-nucleus and nucleus-nucleus interactions are customarily $l$ independent in…
Background: Challenging questions of the $\alpha$-particle optical-model potential (OMP) are still pointed out by recent high-precision measurements of $\alpha$-induced reaction data below the Coulomb barrier. Moreover, the reliability of a…
The reliability of a previous $\alpha$-particle optical-model potential (OMP) on nuclei with mass number 45$\leq$$A$$\leq$209 was proved for emitted $\alpha$ particles as well, for proton--induced reactions on Zn isotopes [Phys. Rev. C {\bf…
In recent years, there has been an increasing need for Nuclear Power Plants (NPPs) to improve flexibility in order to match the rapid growth of renewable energies. The Operator Assistance Predictive System (OAPS) developed by Framatome…
In the past two decades, machine learning potentials (MLP) have reached a level of maturity that now enables applications to large-scale atomistic simulations of a wide range of systems in chemistry, physics and materials science. Different…
Background: Further studies of high-precision measurements of alpha-induced reaction data below the Coulomb barrier have still raised questions about the alpha-particle optical model potential (OMP) within various mass ranges, i.e. for…
Recent advances in machine-learning interatomic potentials have enabled the efficient modeling of complex atomistic systems with an accuracy that is comparable to that of conventional quantum mechanics based methods. At the same time, the…
In several processes of stellar nucleosynthesis, like the astrophysical gamma-process, nuclear reactions involving alpha particles play an important role. The description of these reactions necessitates the knowledge of the alpha-nucleus…
Solvent environments play a central role in determining molecular structure, energetics, reactivity, and interfacial phenomena. However, modeling solvation from first principles remains difficult due to the complex interplay of interactions…