Related papers: What to expect from microscopic nuclear modelling …
In this paper, we study how to predict the results of LTL model checking using some machine learning algorithms. Some Kripke structures and LTL formulas and their model checking results are made up data set. The approaches based on the…
In the study of optical transients, parameter inference is the process of extracting physical information, i.e. constraints on the source's characteristics, by comparing the observed lightcurves to the predictions of different models and…
The demand for clean energy is ever increasing, with new nuclear technologies presenting a complementary solution to renewable energies. However, designing and operating these systems is exceptionally difficult, given the complexity of the…
We discuss applications of previously computed nuclear structure functions (SF) to inclusive cross sections, compare predictions with recent CEBAF data and perform two scaling tests. We mention that the large $Q^2$ plateau of scaling…
We consider a model where, for a finite disintegrating system, yields of composites can be calculated to arbitrary accuracy. An analytic answer for yields is also known in the thermodynamic limit. In the range of temperature and density…
Total reaction cross sections are predicted for nucleons scattering from various nuclei. Projectile energies to 300 MeV are considered. So also are mass variations of those cross sections at selected energies. All predictions have been…
A new screening model for astrophysical thermonuclear reactions was derived recently which improved Salpeter's weak-screening one. In the present work we prove that the new model can also give very reliable screening enhancement factors…
The neutron distribution of neutron-rich nuclei provides critical information on the structure of finite nuclei and neutron stars. Parity violating experiments -- such as PREX and CREX -- provide a clean and largely model-independent…
Astrophysical models studying the origin of the p-nuclei require knowledge of the reaction rates of photodisintegrations and capture reactions. Since experimental data at astrophysically relevant energies are limited, reaction rate…
Nuclear data is critical for many modern applications from stockpile stewardship to cutting edge scientific research. Central to these pursuits is a robust pipeline for nuclear modeling as well as data assimilation and dissemination. We…
In a previous publication [Atomic Data and Nuclear Data Tables 75, 1 (2000)], we had given seven parameter analytical fits to theoretical reaction rates derived from nuclear cross sections calculated in the statistical model…
Quantum neural network (QNN) models have received increasing attention owing to their strong expressibility and resistance to overfitting. It is particularly useful when the size of the training data is small, making it a good fit for…
A recently introduced analytical model for the nuclear density profile[1] is implemented in the Extended Thomas-Fermi (ETF) energy density functional. This allows to (i) shed a new light on the issue of the sign of surface symmetry energy…
The radiative thermal neutron capture cross sections over the range of thermal energies from 1 keV to 1 MeV are studied in statistical Hauser-Feshbach formalism. The optical model potential is constructed by folding the density dependent…
Predicting structural and energetic properties of a molecular system is one of the fundamental tasks in molecular simulations, and it has use cases in chemistry, biology, and medicine. In the past decade, the advent of machine learning…
Over the past few decades, a vast amount of information on the structure of atomic nuclei has been collected, compiled, and evaluated. Accurate and reliable data are essential for the understanding of the behavior of atomic nuclei.…
Nuclear physics advances in the US and Britain, from 1939-1945, are described. The Manhattan Project's work led to an explosion in our knowledge of nuclear science. A conference in April 1943 at Los Alamos provided a simple formula used to…
In the light of the JEF(F) European project longstanding story according to the determination of the most exact shape of the 239Pu(n, 2n)238Pu reaction cross section and a recent measurement by Meot et al., this paper aims to shed another…
This study is devoted to the inference problem of extracting the nuclear matter properties directly from a set of mass-radius observations. We employ Bayesian neural networks (BNNs), which is a probabilistic model capable of estimating the…
Background: At the forefront of the nuclear science, production of new neutron-rich isotopes is continuously pursued at accelerator laboratories all over the world. To explore the currently-unknown territories in the nuclear chart far away…