Subjects: Physics >> Nuclear Physics submitted time 2024-03-19
Abstract： The exploration of exotic shapes and properties of atomic nuclei, e.g., α cluster and toroidal shape, is a
fascinating field in nuclear physics. To study the decay of these nuclei, a novel detector aimed at detecting
multiple alpha-particle events was designed and constructed. The detector comprises two layers of double-sided
silicon strip detectors (DSSD) and a cesium iodide scintillator array coupled with silicon photomultipliers array
as light sensors, which has the advantages of their small size, fast response, and large dynamic range. DSSDs
couple with cesium iodide crystal arrays are used to distinguish multiple alpha hits. The detector array has a
compact and integrated design that can be adapted to different experimental conditions. The detector array was
simulated using Geant4, and the excitation energy spectra of some alpha-clustering nuclei were reconstructed
to demonstrate the performance. The simulation results show that the detector array has excellent angular
and energy resolutions, enabling effective reconstruction of the nuclear excited state by multiple alpha particle
events. This detector offers a new and powerful tool for nuclear physics experiments and has the potential to
discover interesting physical phenomena related to exotic nuclear structures and their decay mechanisms
Subjects: Physics >> Nuclear Physics submitted time 2024-03-19
Abstract： In recent years, the gap between the supply and demand of medical radioisotopes has increased, necessitating new methods for producing medical radioisotopes. Photonuclear reactions based on gamma sources have unique advantages in terms of producing high specific activity and innovative medical radioisotopes. However, the lack of experimental data on reaction cross sections for photonuclear reactions of medical radioisotopes of interest has severely limited the development and production of photonuclear transmutation medical radioisotopes. In this study, the entire process of the generation, decay, and measurement of medical radioisotopes was simulated using online gamma activation and offline gamma measurements combined with a shielding gammaray spectrometer. Based on a quasi-monochromatic gamma beam from the Shanghai Laser Electron Gamma Source (SLEGS), the feasibility of the measurement of production cross section for surveyed medical isotopes was simulated, and specific solutions for measuring medical radioisotopes with low production cross sections were provided. The feasibility of this method for high precision measurements of the reaction cross section of medical radioisotopes was demonstrated.
Subjects: Physics >> Nuclear Physics Subjects: Physics >> Interdisciplinary Physics and Related Areas of Science and Technology submitted time 2024-01-10
Abstract： Traditional particle identification methods are time consuming, experience-dependent, and poor repeatability challenges in heavy-ion collisions at low and intermediate energies. Researchers urgently need solutions to the dilemma of traditional particle identification methods. This study explores the possibility of applying intelligent learning algorithms to the particle identification of heavy-ion collisions at low and intermediate energies. Multiple intelligence algorithms, including XgBoost and TabNet, were selected to test datasets from the neutron ion multi-detector for reaction-oriented dynamics (NIMROD–ISiS) and Geant4 simulation. Machine learning algorithms based on tree structures and deep learning algorithms e.g. TabNet show excellent performance and generalization ability. Adding additional data features besides energy deposition can improve the algorithm's identification ability when the data distribution is nonuniform. Intelligent learning algorithms can be applied to solve the particle identification problem in heavy-ion collisions at low and intermediate energies.
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