相关论文: FIER: Software for analytical modeling of delayed …
Infrared spectra obtained from cell or tissue specimen have commonly been observed to involve a significant degree of (resonant) Mie scattering, which often overshadows biochemically relevant spectral information by a non-linear,…
The GEneral description of Fission observables (GEF) model was developed to produce fission related nuclear data which are of crucial importance for basic and applied nuclear physics. The investigation of the performance of the GEF code is…
The understanding of the antineutrino production in fission and the theoretical calculation of their energy spectra in different types of fission reactors rely on the application of the summation method, where the individual contributions…
Reaction measurements on fission products are being planned at both Argonne National Lab and at the Facility for Rare Isotope Beams. These indirect experiments produce specific short-lived nuclei via beta decay, and the subsequent neutron…
This paper introduces the Bayesian Inference Engine (BIE), a general parallel, optimised software package for parameter inference and model selection. This package is motivated by the analysis needs of modern astronomical surveys and the…
Modern radio and multi-instrument astrophysical datasets are increasingly assembled from surveys with different sensitivities and selection effects. In such heterogeneous datasets, published measurement uncertainties are often incomplete,…
Detailed information on the fission process can be inferred from the observation, modeling and theoretical understanding of prompt fission neutron and $\gamma$-ray~observables. Beyond simple average quantities, the study of distributions…
Time-series forecasting is fundamental in industrial domains like manufacturing and smart factories. As systems evolve toward automation, models must operate on edge devices (e.g., PLCs, microcontrollers) with strict constraints on latency…
Protein sequence analysis underpins research in biophysics, computational biology, and bioinformatics. We introduce BEER, a crossplatform graphical interface that accepts FASTA or Protein Data Bank (PDB) files, or manual sequence entry, and…
We demonstrate that Bayesian machine learning can be used to treat the vast amount of experimental fission data which are noisy, incomplete, discrepant, and correlated. As an example, the two-dimensional cumulative fission yields (CFY) of…
We calculate fission $\gamma$ rays for neutron-induced reactions on $^{239}$Pu with the Hauser-Feshbach fission fragment decay model. By applying the calculated fission $\gamma$ rays as a background contribution, the historical…
Over the last decade, there has been significant improvement in the understanding and modeling of the decay of fission fragments by both prompt and delayed emission. These model improvements open the door for performing consistent…
Inverse problems are of great importance in astrophysics for deriving information about the physical characteristics of hot optically thin plasma sources from their EUV and X-ray spectra. We describe and test an iterative method developed…
The CGMF code implements the Hauser-Feshbach statistical nuclear reaction model to follow the de-excitation of fission fragments by successive emissions of prompt neutrons and $\gamma$ rays. The Monte Carlo technique is used to facilitate…
The use of active interrogation (AI) to induce delayed neutron emission is a well-established technique for the characterization of special nuclear materials (SNM). Delayed neutrons have isotope-characteristic spectral and temporal…
A role of \beta-delayed neutron emission and fission in r-process nucleosynthesis attracts a high interest. Although the number of study on them covering r-process nuclei is increasing recently, uncertainties of \beta-delayed neutron and…
The prevailing data-driven machine learning has been plagued by the absence of physics knowledge and the scarcity of data. We implement the physics-model informed prior into Bayesian machine learning to evaluate the energy dependence of…
The spectral energy distribution (SED) of a galaxy contains information on the galaxy's physical properties, and multi-wavelength observations are needed in order to measure these properties via SED fitting. In planning these surveys,…
Sustainable aviation fuels have the potential for reducing emissions and environmental impact. To help identify viable sustainable aviation fuels and accelerate research, several machine learning models have been developed to predict…
A wide variety of emulators have been developed for nuclear physics, particularly for use in quantifying and propagating parametric uncertainties to observables. Most of these methods have been used to emulate structure observables, such as…