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MARKOVIAN APPROACH: FROM ISING MODEL TO STOCHASTIC RADIATIVE TRANSFER

机译:马尔可夫方法:从伊辛模型到随机辐射转移

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The origin of the Markovian approach can be traced back to 1906; however, it gained explicit recognition in the last few decades. This overview outlines some important applications of the Markovian approach, which illustrate its immense prestige, respect, and success. These applications include examples in the statistical physics, astronomy, mathematics, computational science and the stochastic transport problem. In particular, the overview highlights important contributions made by Pomraning and Titov to the neutron and radiation transport theory in a stochastic medium with homogeneous statistics. Using simple probabilistic assumptions (Markovian approximation), they have introduced a simplified, but quite realistic, representation of the neutron/radiation transfer through a two-component discrete stochastic mixture. New concepts and methodologies introduced by these two distinguished scientists allow us to generalize the Markovian treatment to the stochastic medium with inhomogeneous statistics and demonstrate its improved predictive performance for the downwelling shortwave fluxes.
机译:马尔可夫方法的起源可以追溯到1906年。然而,它在最近的几十年中得到了明确的认可。本概述概述了马尔可夫方法的一些重要应用,说明了其巨大的声望,尊重和成功。这些应用包括统计物理学,天文学,数学,计算科学和随机运输问题中的示例。特别是,概述着重介绍了Pomraning和Titov在具有均一统计量的随机介质中对中子和辐射输运理论的重要贡献。他们使用简单的概率假设(马尔可夫近似)引入了一种简化的但非常现实的表示形式,该表示形式是通过两组分离散随机混合物进行的中子/辐射传输的。两位杰出的科学家引入的新概念和方法论使我们可以将马尔可夫方法推广到具有非均匀统计量的随机介质,并证明其对下降流短波通量具有更好的预测性能。

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