Related papers: The accuracy of post-processing nucleosynthesis
The sensitivity of underground experiments searching for rare events such as dark matter, neutrino interactions or several beyond the standard model phenomena is often limited by the background caused by neutrons from spontaneous fission…
Interpreting the spectral energy distributions (SEDs) of astrophysical objects with physically motivated models is computationally expensive. These models require solving coupled differential equations in high-dimensional parameter spaces,…
The radioactive isotopes of 44Ti and 56Ni are important products of explosive nucleosynthesis, which play a key role for supernova (SN) diagnostics and were detected in several nearby young SN remnants. However, most SN models based on…
In a previously presented proof-of-principle study, we established a parametrized spherically symmetric explosion method (PUSH) that can reproduce many features of core-collapse supernovae for a wide range of pre-explosion models. The…
We present a novel method of classifying Type Ia supernovae using convolutional neural networks, a neural network framework typically used for image recognition. Our model is trained on photometric information only, eliminating the need for…
With presently known input physics and computer simulations in 1D, a self-consistent treatment of core collapse supernovae does not yet lead to successful explosions, while 2D models show some promise. Thus, there are strong indications…
The majority of nuclear reactions in astrophysics involve unstable nuclei which are not fully accessible by experiments yet. Therefore, there is high demand for reliable predictions of cross sections and reaction rates by theoretical means.…
If the neutrino luminosity from the proto-neutron star formed during a massive star core collapse exceeds a critical threshold, a supernova (SN) results. Using spherical quasi-static evolutionary sequences for hundreds of progenitors over a…
Numerous phenomenological nuclear models have been proposed to describe specific observables within different regions of the nuclear chart. However, developing a unified model that describes the complex behavior of all nuclei remains an…
Advances in Deep Learning bring further investigation into credibility and robustness, especially for safety-critical engineering applications such as the nuclear industry. The key challenges include the availability of data set (often…
Hyper spectral images (HSI) provide rich spectral and spatial information across a series of contiguous spectral bands. However, the accurate processing of the spectral and spatial correlation between the bands requires the use of…
A large fraction of core-collapse supernovae (CCSNe), 30-50%, are expected to originate from the low-mass end of progenitors with $M_{\rm ZAMS}~= 8-12~M_\odot$. However, degeneracy effects make stellar evolution modelling of such stars…
The thermonuclear explosion of massive white dwarfs is believed to explain at least a fraction of Type Ia supernovae (SNIa). After thermal runaway, electron captures on the ashes left behind by the burning front determine a loss of…
Multimessenger observations of the neutron star merger event GW170817 have re-energized the debate over the astrophysical origins of the most massive elements via the r-process nucleosynthesis. A key aspect of such studies is comparing…
As the ultimate stage of stellar nucleosynthesis, and the source of the iron peak nuclei, silicon burning is important to our understanding of the evolution of massive stars and supernovae. Our reexamination of silicon burning, using…
Purpose: Our objective is to apply an improved statistical global model of beta^- decay half-life systematics [1] generated by machine-learning techniques to the prediction of beta half-lives relevant to r-process nuclei. The primary aim of…
The precise measurement of the antineutrino spectra produced by isotope fission in reactors is of great significance for studying neutrino oscillations, refining nuclear databases, and addressing the reactor antineutrino anomaly. In this…
We investigate $r$-process nucleosynthesis and kilonova emission resulting from binary neutron star (BNS) mergers based on a three-dimensional (3D) general-relativistic magnetohydrodynamic (GRMHD) simulation of a hypermassive neutron star…
Ensemble weather predictions require statistical post-processing of systematic errors to obtain reliable and accurate probabilistic forecasts. Traditionally, this is accomplished with distributional regression models in which the parameters…
Neurophysiologists are nowadays able to record from a large number of extracellular electrodes and to extract, from the raw data, the sequences of action potentials or spikes generated by many neurons. Unfortunately these ''many neurons''…