A Time-Slicing Method for Capturing Neutron Source Locations for Initializing Dynamic Monte Carlo Simulations
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The evolution of thermonuclear runaways is examined in two models of white dwarfs with extreme enhancements of C-12 in their envelopes to test the predictions of Hoyle and Clayton (1974) that novae will result from such stars and a large neutron flux will be produced. In agreement with these predictions, it is assumed that the large amount of C-12 is due to the accretion of hydrogen-rich material from a disk surrounding a carbon-oxygen white dwarf. The evolution of the two models is described in detail, and the results suggest that accretion of hydrogen-rich material will always result in a thermonuclear runaway, although mass ejection will not occur unless CNO nuclei are enhanced. It is noted that one model produces a substantial neutron flux for a short time which is sufficient to drive an intermediate neutron-capture process.
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We describe the ongoing efforts to apply Machine Learning techniques to improve the performance of our accelerator and target. Specially, we are looking to minimize halo beam losses in the absence of a proper physics model, automatically detect and log anomalies in the target support systems such as cooling, and detect and prevent errant beam pulses in the linac. We also describe the infrastructure we use to acquire and stream data to the GPU cluster for training, our code development cycle, and edge computing for model inference. To minimize halo beam losses, we use a Reinforcement Learning technique tested on a virtual accelerator. The target anomaly detection is trained on archived data using incomplete physics models and is made part of the existing target reporting system. The errant beam prevention analyzes beam current and beam phase waveforms as well as accelerator configuration data to predict errant pulses. We also develop continual learning to adapt to changes in the accelerator.
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The importance of actinides for science, technology, and medicine is widely recognized and does not require a lengthy introduction. However, the fundamental understanding of actinides and their chemical and physical properties lags behind the knowledge of most other elements in the periodic table. Most actinides (89 ≤ Z ≤ 103) are man-made and were produced in particle accelerators or nuclear reactors in the second half of the 20th century. Although trends in bonding and electronic structure are well characterized and documented across the periodic table, fundamental questions remain regarding the chemistry and physics of the actinides. This lack of knowledge is largely because most isotopes of actinides are intensely radioactive, which greatly increases the difficultly in handling them.
SOURCES-4C has some significant deficiencies that are mostly due to problems with the default data libraries that it uses. Some research groups have modified these libraries to fix most of the problems, but not all of them. Adding modern data libraries to SOURCES-4C is one of the most promising approaches to resolving these issues. Other promising options include using either NEDIS or a GEANT4 tool. Both of these codes approximately match the accuracy of the modified SOURCES-4C code. The NEDIS code is Russian. The GEANT4 tool might be computationally slow and it might also no longer be actively maintained. There are a handful of other (α,n) codes, but they are not accurate.