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重核的断前粒子发射与鞍点后摩擦的探测
引用本文:王宁,叶巍. 重核的断前粒子发射与鞍点后摩擦的探测[J]. 原子核物理评论, 2020, 37(3): 600-604. DOI: 10.11804/NuclPhysRev.37.2019CNPC16
作者姓名:王宁  叶巍
作者单位:东南大学物理学院,南京 210096
基金项目:国家自然科学基金资助项目(11975074)
摘    要:基于考虑了粒子发射的随机Langevin模型,计算了重裂变核240Am在 鞍点后发射的中子、质子和$ alpha $粒子多重性作为鞍点后摩擦强度($ beta $)的函数。结果表明在高激发能($ E^* $)和高角动量($ ell $)条件下,这些轻粒子发射对摩擦的敏感性变强。进而,比较了在(高$ E^* $,低$ ell $)和(低$ E^* $,高$ ell $)这两个不同初始条件下,240Am核在鞍点后蒸发的粒子随$ beta $的演化。发现前者不但能增强核摩擦对粒子发射的影响,也显著提高了带电粒子对$ beta $的敏感性。在实验方面,我们建议可以用中能重离子碰撞的方式产生高激发的重裂变系统,来更精确地用粒子发射(尤其是轻带电粒子)来探测鞍点后的摩擦强度。

关 键 词:鞍点后摩擦   轻粒子多重性   重核   中能重离子碰撞   随机模型
收稿时间:2019-12-16

Prescission Particle Emission of Heavy Nuclei and the Probe of Postsaddle Friction
Ning WANG,Wei YE. Prescission Particle Emission of Heavy Nuclei and the Probe of Postsaddle Friction[J]. Nuclear Physics Review, 2020, 37(3): 600-604. DOI: 10.11804/NuclPhysRev.37.2019CNPC16
Authors:Ning WANG  Wei YE
Affiliation:Department of Physics, Southeast University, Nanjing 210096, China
Abstract:The stochastic Langevin model is applied to calculate the evolution of postsaddle emitted neutrons, protons and $ alpha $ particles of heavy 240Am nuclei with the postsaddle friction strength($ beta $). A significantly enhanced sensitivity of these particles to $ beta $ has been observed at a high energy($ E^* $) and a large angular momentum($ ell $). Moreover, the postsaddle emission as a function of $ beta $ is compared under two contrasting initial conditions of (high $ E^* $, low $ ell $) and (low $ E^* $, high $ ell $) for the populated 240Am system. It is shown that for the former type of conditions, the influence of friction on particle evaporation is amplified and the sensitivity of light charged particles to friction is significantly increased. These results suggest that in experiment, to precisely probe the postsaddle friction through the measurement of particle multiplicity, in particular light charged-particle multiplicities, it is best to choose intermediate-energy heavy-ion collisions to produce highly excited heavy fissioning nuclei.
Keywords:
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