基于物理的方法利用随机矩阵方法生成概率表
Physics-based method for generating probability table using random-matrix approach
AI总结：
本文提出基于随机矩阵方法的物理方法，用于生成概率表，并通过实验验证其与传统方法的比较。
摘要：
我们开发了一种基于坚实理论基础的新方法，用于生成概率表。通过GOE-S矩阵模型计算波动截面，其中Gaussian Orthogonal Ensemble（GOE）被纳入散射（S）矩阵的计算中。计算出的截面随后以与NJOY相同的方式转换为概率表。使用^{238}U和^{239}Pu作为靶核，我们根据平均截面的收敛行为确定最优模型参数。我们研究了概率表的统计不确定性作为阶梯数函数。我们证明了在0 K下计算出的概率表在定性上与传统单能级Breit-Wigner公式计算的结果相当，尽管由于S矩阵的必要单位性，我们观察到一些局部差异。
英文摘要：
We develop a new method for generating probability tables based on a solid theoretical foundation. The fluctuating cross sections are calculated using the GOE-$S$-matrix model, in which the Gaussian Orthogonal Ensemble (GOE) is incorporated into the calculation of the scattering ($S$) matrix. The calculated cross sections are then converted into the probability tables in the same manner as in NJOY. Using $^{238}$U and $^{239}$Pu as target nuclei, we determine the optimal model parameters based on the convergence behavior of the average cross sections. The statistical uncertainty of the probability tables is examined as a function of the number of ladders. We demonstrate that the probability tables calculated at 0 K are qualitatively comparable with those calculated using the conventional single-level Breit-Wigner formalism, albeit we observe some local differences due to requisite unitality for the $S$ matrix.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
