可列斯基分解
随机微分方程
数学
应用数学
布朗运动
协方差
微分方程
随机偏微分方程
协方差矩阵
随机微积分
欧拉法
欧拉公式
数学分析
特征向量
统计
物理
量子力学
作者
Daniel Suescún-Díaz,Maria Ibáñez-Paredes,Jesús A. Chala-Casanova
标识
DOI:10.1016/j.physa.2023.129109
摘要
This study presents a novel approach to analyzing radioactive decay by incorporating stochastic fluctuations into Bateman equations using Itô calculus. This results in a stochastic differential equation that describes the temporal evolution of radionuclide concentrations. The model not only calculates expected values, but also estimates uncertainties through the standard deviations of random variables. The stochastic differential equation is solved numerically using the explicit and implicit Euler–Maruyama methods considering 5000 Brownian trajectories. The computational cost of the proposed method is reduced by finding an analytical expression for the square root of the covariance matrix by Cholesky decomposition. The study found that the approximations for expected values agree with the analytical solution of Bateman Equations, and reported standard deviations associated with different radioactive substances.
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