Related papers: Nuclear binding energy predictions based on BP neu…
Nuclear masses play a fundamental role in understanding how the heaviest elements in the Universe are created in the $r$-process. We predict $r$-process nucleosynthesis yields using neutron capture and photodissociation rates that are based…
Neural networks are being used to make new types of empirical chemical models as inexpensive as force fields, but with accuracy close to the ab-initio methods used to build them. Besides modeling potential energy surfaces, neural-nets can…
An artificial neural network (ANN) is investigated as a tool for estimating rate coefficients for the collisional excitation of molecules. The performance of such a tool can be evaluated by testing it on a dataset of collisionally-induced…
The effect of residual interaction between nucleons (quasiparticles) on shell oscillations of the masses of spherical nuclei is considered. The singularity of the ground state energy of the system in the vicinity of nucleon magic numbers is…
Rigid bodies, made of smaller composite beads, are commonly used to simulate anisotropic particles with molecular dynamics or Monte Carlo methods. To accurately represent the particle shape and to obtain smooth and realistic effective pair…
This paper describes the development of the Four Model Tree Ensemble (FMTE). The FMTE is a composite of machine learning models trained on experimental binding energies from the Atomic Mass Evaluation (AME) 2012. The FMTE predicts binding…
We use a finite range simple effective interaction to construct nuclear equations of state for the study of the density dependence of the nuclear symmetry energy. The EoSs provide good descriptions of the nuclear symmetry energy at a…
Twelve physics-informed machine learning models have been trained to model binding energy residuals. Our approach begins with determining the difference between measured experimental binding energies and three different mass models. Then…
The effects of nuclear re-interactions in quasi elastic and resonant neutrino interactions have been considered in the framework of the nuclear models of the DPMJET code. A preliminary investigation on the modifications induced on the final…
Machine-learning models in chemistry - when based on descriptors of atoms embedded within molecules - face essential challenges in transferring the quality of predictions of local electronic structures and their associated properties across…
The photonuclear reactions which is induced by high-energetic photon are one of the important type of reactions in the nuclear structure studies. In this reaction, a target material is bombarded by photons with the energies in the range of…
Nowadays, the Cosmic Microwave Background (CMB) anisotropies studies accurately determine the baryon fraction omega_b, showing an overall and striking agreement with previous determinations of omega_b obtained from Big Bang Nucleosynthesis…
Nuclear and neutron matters are investigated in the low density region, well below the nuclear saturation density. Microscopic calculations, based on the Bethe-Brueckner approach with a few realistic nucleon-nucleon potentials, are compared…
We perform an extensive study of the influence of nuclear weak interactions on core-collapse supernovae (CCSNe), paying particular attention to consistency between nuclear abundances in the equation of state (EOS) and nuclear weak…
A novel method for estimating Bayesian network (BN) parameters from data is presented which provides improved performance on test data. Previous research has shown the value of representing conditional probability distributions (CPDs) via…
Background: One-dimensional protein structures such as secondary structures or contact numbers are useful for three-dimensional structure prediction and helpful for intuitive understanding of the sequence-structure relationship. Accurate…
One of the goals of current particle physics research is to obtain evidence for new physics, that is, physics beyond the Standard Model (BSM), at accelerators such as the Large Hadron Collider (LHC) at CERN. The searches for new physics are…
The Nucleon-Nucleon interaction is the starting point for ab initio Nuclear Structure and Nuclear reactions calculations. Those are effectively carried out via effective interactions fitting scattering data up to a maximal center of mass…
One of the main challenges in modeling massive stars to the onset of core collapse is the computational bottleneck of nucleosynthesis during advanced burning stages. The number of isotopes formed requires solving a large set of…
Radio pulsar timing, X-ray pulse profile modeling or gravitational-wave detections of binary mergers involving at least one neutron star offer the opportunity to elucidate the properties of dense and neutron rich matter in thermodynamic…