相关论文: SkyNet: A modular nuclear reaction network library
Hydrogen cyanide (HCN) is a critical reactive source of nitrogen for building key biomolecules relevant for the origin of life. Still, many HCN reactions remain uncharacterized by experiments and theory, and the complete picture of HCN…
Deep learning models have gained increasing prominence in recent years in the field of solar pho-tovoltaic (PV) forecasting. One drawback of these models is that they require a lot of high-quality data to perform well. This is often…
A necessary condition for the reliable modelling of the structure or evolution of the stars and of their concomitant nucleosynthesis is the availability of good quality nuclear data in a very wide area of the chart of nuclides. This short…
Galaxy appearances reveal the physics of how they formed and evolved. Machine learning models can now exploit galaxies' information-rich morphologies to predict physical properties directly from image cutouts. Learning the relationship…
BioNetGen is an open-source software package for rule-based modeling of complex biochemical systems. Version 2.2 of the software introduces numerous new features for both model specification and simulation. Here, we report on these…
We investigate a class of universes in which the weak interaction is not in operation. We consider how astrophysical processes are altered in the absence of weak forces, including Big Bang Nucleosynthesis (BBN), galaxy formation, molecular…
This paper presents the results of calculation of element overproduction in the S-Cl region during helium and carbon burning in massive stars (25 Ms). Calculations for a given set of differential equations were performed using integrated…
Nuclear star clusters represent some of the most extreme collisional environments in the Universe. A nuclear star cluster like that of the Milky Way harbors a supermassive black hole at its center, which accelerates stars to high speeds…
Some metal-poor stars have abundance patterns which are midway between the slow (s) and rapid (r) neutron capture processes. We show that the helium shell of a fast rotating massive star experiencing a jet-like explosion undergoes two…
Heavy elements are synthesized by the r-process in neutron star mergers and potentially in rare supernovae linked to strong magnetic fields. Expensive hydrodynamic simulations of these extreme environments are usually post-processed to…
Nuclear fusion is the process that powers the sun, and it is one of the best hopes to achieve a virtually unlimited energy source for the future of humanity. However, reproducing sustainable nuclear fusion reactions here on Earth is a…
We construct a new reduced nuclear reaction network able to reproduce the energy production due to the photo-disintegration of heavy elements such as Ru, which are believed to occur during superbursts in mixed H/He accreting systems. We use…
High energy neutrinos can be produced by interactions of ultra-high energy cosmic rays (UHECRs) in the dense radiation fields of their sources as well as off the cosmic backgrounds when they propagate through the universe. Multi-messenger…
Modeling binary neutron star merger (BNSM) ejecta evolution requires simulations involving hydrodynamics, nuclear reactions, and radiative processes. The impact of nuclear burning and atomic opacity is poorly understood and often treated…
We present the novel wide & deep neural network GalaxyNet, which connects the properties of galaxies and dark matter haloes, and is directly trained on observed galaxy statistics using reinforcement learning. The most important halo…
In the scheme of chemonuclear reaction, bulk of itinerant s-electrons revealing the thermodynamical liquid activity in metallic systems undergo contact interaction with atomic nuclei and therein nucleons, inducing contagiously…
Assuming a Salpeter initial mass function and taking the solar abundances as a representative sample, we explore the sensitivity of nucleosynthesis in massive stars to the truncation of supernova explosions above a certain mass. It is…
Observations of type Ia supernovae include information about the characteristic nucleosynthesis associated with these thermonuclear explosions. We consider observational constraints from iron-group elemental and isotopic ratios, to compare…
SchNetPack is a toolbox for the development and application of deep neural networks to the prediction of potential energy surfaces and other quantum-chemical properties of molecules and materials. It contains basic building blocks of…
Molecular dynamics simulations demand an unprecedented combination of accuracy and scalability to tackle grand challenges in catalysis and materials design. To bridge this gap, we present AlphaNet, a local-frame-based equivariant model that…