论文标题
人工神经网络对同位素钙同位素上光核反应的横截面的估计
Estimations of Cross-Sections for Photonuclear Reaction on Calcium Isotopes by Artificial Neural Networks
论文作者
论文摘要
光子诱导的核反应是研究原子核的重要工具之一。在反应中，目标材料在伽马射线能量范围内具有高氧气的光子轰击。在轰击过程中，光子可以在统计上被目标材料中的核吸收。然后激发的核可以通过排放质子，中子，α和光颗粒或光子来衰减。通过对目标进行光核反应，可以很容易地研究核的低洼激发态。在目前的工作中，（γ，n）使用人工神经网络方法估算了不同同位素的光核反应横截面。该方法是模仿生物的大脑功能的数学模型。该方法的训练和测试阶段的相关系数为0.99表明该方法非常适合此目的。
The nuclear reaction induced by photon is one of the important tools in the investigation of atomic nuclei. In the reaction, a target material is bombarded by photons with high-energies in the range of gamma-ray energy range. In the bombarding process, the photons can statistically be absorbed by a nucleus in the target material. Then the excited nucleus can decay by emitting proton, neutron, alpha and light particles or photons. By performing photonuclear reaction on the target, it can be easily investigated low-lying excited states of the nuclei. In the present work, (γ, n) photonuclear reaction cross-sections on different calcium isotopes have been estimated by using artificial neural network method. The method is a mathematical model that mimics the brain functionality of the creatures. The correlation coefficient values of the method for both training and test phases being 0.99 indicate that the method is very suitable for this purpose.
