The ES Log-normal Distribution Determined by the Einstein Median as the Scale Parameter and the Shannon Shape Parameter

J. Stávek
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引用次数: 2

Abstract

The guiding principle of this contribution is the mutual interplay between the Solar gravitational field and the Maxwell-Boltzmann distribution of speeds of atoms and the observed Fraunhofer lines. We know from numerous experiments that the Newtonian gravitational constant does not depend on the atomic mass, temperature, pressure and many other particle parameters. Therefore, we should discover a universal distribution function that could be used for all atoms and their properties for a given gravitational field. We have introduced the ES log-normal distribution fully determined by the Einstein median as the scale parameter and the Shannon shape parameter σ = 1/√6. Shannon formulated this shape parameter for the log-normal distribution describing systems with the maximum entropy formation. This ES log-normal distribution function determines the most effective mutual interactions between the gravitational field and the Maxwell-Boltzmann particles. In order to make the Einstein median formula more general, we have introduced the model of the active solid angle of the source of gravity with values 1 ≤ Ω ≤ 4 steradians. We have tested this ES log-normal distribution with three datasets measured on the Solar disc and two datasets measured on the surface of the Earth using the Mössbauer effect. There were predicted some new properties of those datasets. This model might stimulate and promote new initiatives to collect new better datasets for the Solar disc and the Mössbauer effect.
由爱因斯坦中位数作为尺度参数和香农形状参数决定的ES对数正态分布
这一贡献的指导原则是太阳引力场与麦克斯韦-玻尔兹曼原子速度分布和观测到的弗劳恩霍夫线之间的相互作用。我们从大量的实验中知道,牛顿引力常数不依赖于原子质量、温度、压力和许多其他粒子参数。因此,我们应该发现一个通用的分布函数,它可以用于所有原子及其在给定引力场下的性质。我们引入了完全由爱因斯坦中位数决定的ES对数正态分布作为尺度参数和香农形状参数σ = 1/√6。Shannon为描述具有最大熵形成的系统的对数正态分布制定了这个形状参数。这个ES对数正态分布函数决定了引力场与麦克斯韦-玻尔兹曼粒子之间最有效的相互作用。为了使爱因斯坦中位数公式更具通用性,我们引入了重力源主动立体角模型,其值为1≤Ω≤4立体度。我们使用Mössbauer效应用在太阳盘上测量的三个数据集和在地球表面测量的两个数据集测试了这个ES对数正态分布。他们预测了这些数据集的一些新特性。这个模型可能会刺激和促进新的举措,以收集新的更好的数据集,为太阳盘和Mössbauer效应。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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