分类： 物理学 >> 核物理学 分类： 物理学 >> 交叉学科物理及相关领域的科学与技术 提交时间： 2024-01-10
摘要： 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 (NIMRODISiS) 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.
分类： 光学 >> 量子光学 提交时间： 2023-02-19
摘要： We study the parity-symmetry-breaking quantum phase transition (QPT) in a cavity magnonic system driven by a parametric field, where the magnons in a ferrimagnetic yttrium-iron-garnet sphere strongly couple to a microwave cavity. With appropriate parameters, this cavity magnonic system can exhibit a rich phase diagram, including the parity-symmetric phase, parity-symmetry-broken phase, and bistable phase. When increasing the drive strength beyond a critical threshold, the cavity magnonic system undergoes either a first- or second-order nonequilibrium QPT from the parity-symmetric phase with microscopic excitations to the parity-symmetry-broken phase with macroscopic excitations, depending on the parameters of the system. Our work provides an alternate way to engineer the QPT in a hybrid quantum system containing the spin ensemble in a ferri- or ferromagnetic material with strong exchange interactions.
点击量
通过
点击量
下载量
评论
待评议
