Related papers: Decoding Beta-Decay Systematics: A Global Statisti…
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…
Evaluated $2\beta^{-}(2\nu)$ half-lives and their systematics were reexamined in the framework of a phenomenological approach. Decay rate dependence on nuclear deformation, decay energy, shape coexistence, and forbidden transitions was…
Frequentist statistical methods, such as hypothesis testing, are standard practice in papers that provide benchmark comparisons. Unfortunately, these methods have often been misused, e.g., without testing for their statistical test…
A novel machine learning approach is used to provide further insight into atomic nuclei and to detect orderly patterns amidst a vast data of large-scale calculations. The method utilizes a neural network that is trained on ab initio results…
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…
Vertex centrality measures are a multi-purpose analysis tool, commonly used in many application environments to retrieve information and unveil knowledge from the graphs and network structural properties. However, the algorithms of such…
Nuclear double $\beta$-decay with two neutrinos is a rare and important process for natural radioactivity of unstable nuclei. The experimental data of nuclear double $\beta^{-}$-decay with two neutrinos are analyzed and a systematic law to…
The non-parametric bootstrap method is used to evaluate the uncertainties of two $\alpha$ decay formulas, the universal decay law (UDL) and the new Geiger-Nuttall law (NGNL). Such a method can simultaneously obtain the uncertainty of each…
Ab-initio calculations of nuclear masses, the binding energy and the $\alpha$ decay half-lives are intractable for heavy nucleus, because of the curse of dimensionality in many body quantum simulations as proton number($\mathrm{N}$) and…
This paper reports the first application of a new technique to measure the beta-decay half -lives of exotic nuclei in complex background conditions. Since standard tools were not adapted to extract the relevant information, a new analysis…
We combine nonlocal effects with Bayesian Neural Network (BNN) methods to enhance the prediction accuracy of $\alpha$ decay half-lives. The results indicate that accounting for nonlocal effects significantly impacts the half-life…
Multiple high precision $\beta$-decay measurements are being carried out these days on various nuclei, in search of beyond the Standard Model signatures. These measurements necessitate accurate standard model theoretical predictions to be…
Accurately predicting industrial aging processes makes it possible to schedule maintenance events further in advance, ensuring a cost-efficient and reliable operation of the plant. So far, these degradation processes were usually described…
Statistic modeling and data-driven learning are the two vital fields that attract many attentions. Statistic models intend to capture and interpret the relationships among variables, while data-based learning attempt to extract information…
Bound-state $\beta^-$-decay is a rare radioactive process where the created electron is trapped in an atomic orbital instead of being emitted. It can be observed in highly ionized atoms in particular when normal beta decay is energetically…
Statistical learning algorithms are finding more and more applications in science and technology. Atomic-scale modeling is no exception, with machine learning becoming commonplace as a tool to predict energy, forces and properties of…
Beta-decay rates of extreme neutron-rich nuclei remain largely unknown experimentally, while they are critical inputs for $r$-process nucleosynthesis. We present first ab initio calculations of total beta-decay half-lives, with a focus on…
Latent space models are effective tools for statistical modeling and exploration of network data. These models can effectively model real world network characteristics such as degree heterogeneity, transitivity, homophily, etc. Due to their…
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…
Compartmental models based on tracer mass balance are extensively used in clinical and pre-clinical nuclear medicine in order to obtain quantitative information on tracer metabolism in the biological tissue. This paper is the second of a…