相关论文: The accuracy of post-processing nucleosynthesis
The quasi-steady state approximation and time-scale separation are commonly applied methods to simplify models of biochemical reaction networks based on ordinary differential equations (ODEs). The concentrations of the "fast" species are…
The neutron-rich isotopes with 30 $\leq$ Z $\leq$ 45 are thought to be synthesised in neutrino-driven winds after the collapse of a massive star. This nucleosynthesis scenario, called the weak r-process, is studied using nuclear reaction…
It is a well-established fact that intranuclear-cascade models generally fail to consistently reproduce the cross sections for one-proton and one-neutron removal from stable nuclei by a high-energy proton beam. We use simple shell-model…
One of the robust features found in simulations of core-collapse supernovae (SNe) is the prompt neutronization burst, i.e. the first $\sim 25$ milliseconds after bounce when the SN emits with very high luminosity mainly $\nu_e$ neutrinos.…
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…
We study the role of light neutron-rich nuclei during r-process nucleosynthesis in supernovae. Most previous studies of the r-process have concentrated on the reaction flow of heavy unstable nuclei. Although the nuclear reaction network…
The nucleosynthetic characteristics of various explosion mechanisms of Type Ia supernovae (SNe Ia) is explored based on three two-dimensional explosion simulations representing extreme cases: a pure turbulent deflagration, a delayed…
We propose a unified model for the nucleosynthesis of heavy (A > 57) elements in stars. The neutron flux can be set to describe neutron capture in arbitrary neutron flux. Our approach solves the coupled differential equations, that describe…
The explosion energy of thermonuclear (Type Ia) supernovae is derived from the difference in nuclear binding energy liberated in the explosive fusion of light 'fuel' nuclei, predominantly carbon and oxygen, into more tightly bound nuclear…
We present a method to extrapolate nuclear binding energies from known values for neighbouring nuclei. We select four specific mass relations constructed to eliminate smooth variation of the binding energy as function nucleon numbers. The…
We explore the sensitivity of the nucleosynthesis of intermediate mass elements (28 < A < 80) in supernovae derived from massive stars to the nuclear reaction rates employed in the model. Two standard sources of reaction rate data (Woosley…
A unified description of full reaction channels in low-energy heavy-ion collisions is a great challenge. Although the theoretical models based on the dinuclear system (DNS) concept have been successfully employed in multinucleon transfer…
Explosive nuclear burning in astrophysical environments produces unstable nuclei which again can be targets for subsequent reactions. In addition, it involves a large number of stable nuclides which are not fully explored by experiments,…
A simulation of the thermonuclear explosion of a Chandrasekhar-mass C+O white dwarf, the most popular scenario of a type Ia supernova (SN Ia), is presented. The underlying modeling is pursued in a self-consistent way, treating the…
Spiking neural networks (SNNs) offer an inherent ability to process spatial-temporal data, or in other words, realworld sensory data, but suffer from the difficulty of training high accuracy models. A major thread of research on SNNs is on…
This work targets the automated minimum-energy optimization of Quantized Neural Networks (QNNs) - networks using low precision weights and activations. These networks are trained from scratch at an arbitrary fixed point precision. At…
We study the efficiency and sensitivity of r-process nucleosynthesis to 18 light-element nuclear reaction rates. We adopt empirical power-law relations to parameterize the reaction sensitivities. We utilize two different hydrodynamic models…
Biochemical networks are used in computational biology, to model the static and dynamical details of systems involved in cell signaling, metabolism, and regulation of gene expression. Parametric and structural uncertainty, as well as…
The production cross sections of superheavy nuclei with charge numbers $114-117$ are predicted in the $(5-9)n$-evaporation channels of the $^{48}$Ca-induced complete fusion reactions for future experiments. The estimates of synthesis…
Given the importance of nuclear mass predictions, numerous models have been developed to extrapolate the measured data into unknown regions. While neural networks -- the core of modern artificial intelligence -- have been recently suggested…