Related papers: Bayesian optimization and nonlocal effects method …
Half-life estimates for neutrinoless double beta decay depend on particle physics models for lepton flavor violation, as well as on nuclear physics models for the structure and transitions of candidate nuclei. Different models considered in…
The existence of long lived superheavy nuclei (SHN) is controlled mainly by spontaneous fission and $\alpha$-decay processes. According to microscopic nuclear theory, spherical shell effects at Z=114, 120, 126 and N=184 provide the extra…
The fully consistent relativistic proton-neutron quasiparticle random phase approximation (PN-RQRPA) is employed in the calculation of beta-decay half-lives of neutron-rich nuclei in the N$\approx$50 and N$\approx$82 regions. A new…
The structure of heavy nuclei is difficult to disentangle in high-energy heavy-ion collisions. The deep convolution neural network (DCNN) might be helpful in mapping the complex final states of heavy-ion collisions to the nuclear structure…
Nuclear beta decay rates are an essential ingredient in simulations of the astrophysical r-process. Most of these rates still rely on theoretical modeling. However, modern radioactive ion-beam facilities have allowed to measure beta half…
Using the time-of-flight technique, we measured the beta-delayed neutron emission of $^{132}$Cd. From our large-scale shell model (LSSM) calculation using the N$^3$LO interaction [Z.Y. Xu et al., Phys. Rev. Lett. 131, 022501 (2023)], we…
Convolutional neural networks (CNNs) work well on large datasets. But labelled data is hard to collect, and in some applications larger amounts of data are not available. The problem then is how to use CNNs with small data -- as CNNs…
We analyze parameter sensitivities of the mapped interacting boson model (IBM) and boson-fermion-fermion model (IBFFM) in the description of $\beta$-decay properties of the even-mass neutron-deficient Ge and As, and neutron-rich Zr and Mo…
Bayesian neural networks (BNNs) are a principled approach to modeling predictive uncertainties in deep learning, which are important in safety-critical applications. Since exact Bayesian inference over the weights in a BNN is intractable,…
The relativistic proton-neutron quasiparticle random phase approximation (PN-RQRPA) is applied in the calculation of beta-decay half-lives of neutron-rich nuclei in the $Z\approx 28$ and $Z\approx 50$ regions. The study is based on the…
We calculate nuclear matrix elements (NME) of neutrinoless double beta decay in four different candidate nuclei (Ge-76, Se-82, Mo-100, Te-130) within the quasiparticle random phase approximation (QRPA) and its uncertainties. We assume (up…
A selfconsistent approach based on a deformed HF+BCS+QRPA method with density-dependent Skyrme forces is used to describe beta+ decay properties in even-even deformed proton rich nuclei. Residual spin-isospin forces are included in the…
We investigate {\alpha}-decay half-lives for 74 {\le} Z {\le} 92 even-even nuclei within the semiclassical WKB approximation in deformed relativistic Hartree-Bogoliubov theory in continuum (DRHBc). The {\alpha}-particle preformation factors…
A measurement of neutrinoless double beta decay in one isotope does not allow to determine the underlying physics mechanism. We discuss the discrimination of mechanisms for neutrinoless double beta decay by comparing ratios of half life…
Neutrinoless double beta decay ($\znbb$) induced by superparticle exchange is investigated. Such a supersymmetric (SUSY) mechanism of $\znbb$ decay arises within SUSY theories with R-parity non-conservation (\rp). We consider the minimal…
We approach the calculation of the nuclear matrix element of the neutrinoless double-beta decay process, considering the light-neutrino-exchange channel, by way of the realistic shell-model. In particular the focus of our work is spotted on…
The $(\beta ^{-}\beta ^{-})_{0\nu}$ decay of $^{94,96}$Zr, $^{98,100}$Mo, $^{104}$Ru, $^{110}$Pd, $^{128,130}$Te and $^{150}$Nd isotopes for the $0^{+}\to 0^{+}$ transition is studied in the Projected Hartree-Fock-Bogoliubov framework. In…
Nuclear $\beta$ decay is a key element of the astrophysical rapid neutron capture process ($r$-process). In this paper, we present state-of-the-art global $\beta$-decay calculations based on the quantified relativistic nuclear energy…
Physics-Informed Neural Networks (PINNs) provide a framework for integrating physical laws with data. However, their application to Prognostics and Health Management (PHM) remains constrained by the limited uncertainty quantification (UQ)…
Deep Bayesian neural networks (BNNs) are a powerful tool, though computationally demanding, to perform parameter estimation while jointly estimating uncertainty around predictions. BNNs are typically implemented using arbitrary…