论文标题
EVO-SETI：一种用于甲板，演变和seti的数学工具
Evo-SETI: A Mathematical Tool for Cladistics, Evolution, and SETI
论文作者
论文摘要
新系外行星的发现使我们想知道每个新系外行星在地球上所知道的那样发展生命的途中。我们的EVO-Seti理论是面对这个问题的一种数学方法。我们通过基于对数正态概率密度函数（PDF）的一些统计方程来描述cladistics和进化。我们称b-cognormal在瞬间b（出生）开始为对数正态PDF。然后，任何生物的生命在当时成为合适的B-识别。接下来，我们的“峰值 - 局限性定理”翻译了cradistics：通过进化产生的每个物种都是B-识别性的，其峰值在于呈指数增长的活物种。该指数是称为“几何布朗运动”（GBM）的随机过程的平均值。过去的大量灭绝是该GBM的全低。此外，每个B-沟通型的香农熵（带有反向的符号）是该物种如何进化的度量，我们称其为Evoentropy。每当平均值完全是GBM指数时，“分子时钟”被重新解释为Evoentropy直线。我们还能够将峰值定理扩展到指数以外的任何平均值。例如，我们在本文中首次得出了与马尔可夫·科洛塔耶夫（Markov-Korotayev（2007）“立方”进化：对数增加的曲线的相对应。
The discovery of new exoplanets makes us wonder where each new exoplanet stands along its way to develop life as we know it on Earth. Our Evo-SETI Theory is a mathematical way to face this problem. We describe cladistics and evolution by virtue of a few statistical equations based on lognormal probability density functions (pdf) in the time. We call b-lognormal a lognormal pdf starting at instant b (birth). Then, the lifetime of any living being becomes a suitable b-lognormal in the time. Next, our "Peak-Locus Theorem" translates cladistics: each species created by evolution is a b-lognormal whose peak lies on the exponentially growing number of living species. This exponential is the mean value of a stochastic process called "Geometric Brownian Motion" (GBM). Past mass extinctions were all-lows of this GBM. In addition, the Shannon Entropy (with a reversed sign) of each b-lognormal is the measure of how evolved that species is, and we call it EvoEntropy. The "molecular clock" is re-interpreted as the EvoEntropy straight line in the time whenever the mean value is exactly the GBM exponential. We were also able to extend the Peak-Locus Theorem to any mean value other than the exponential. For example, we derive in this paper for the first time the EvoEntropy corresponding to the Markov-Korotayev (2007) "cubic" evolution: a curve of logarithmic increase.
