论文标题
部分可观测时空混沌系统的无模型预测
Iterating sum of power divisor function and New equivalence to the Riemann hypothesis
论文作者
论文摘要
储层计算是预测湍流的有力工具，其简单的架构具有处理大型系统的计算效率。然而，其实现通常需要完整的状态向量测量和系统非线性知识。我们使用非线性投影函数将系统测量扩展到高维空间，然后将其输入到储层中以获得预测。我们展示了这种储层计算网络在时空混沌系统上的应用，该系统模拟了湍流的若干特征。我们表明，使用径向基函数作为非线性投影器，即使只有部分观测并且不知道控制方程，也能稳健地捕捉复杂的系统非线性。最后，我们表明，当测量稀疏、不完整且带有噪声，甚至控制方程变得不准确时，我们的网络仍然可以产生相当准确的预测，从而为实际湍流系统的无模型预测铺平了道路。
We were able in this paper to give a negative answer to the reverse question of Graeme L. Cohen and Herman J. J. te Riele such that we showed that there is no fixed integer $m $ for which $σ^k(m) = 0 \bmod m$ for all iterations $k$ of sum divisor function using H.Lenstra problem result for Aliquot sequence and we showed that there exists some integers $m$ such that $σ_k(m) \bmod m$ is periodic with small period $L=2$(periodicity with small period dividing $L$ the lcm the least common multiple of $1$+each exponents in the prime factorization of $m$ ).A new equivalence to the Riemann hypothesis has been added using congruence and divisibility among sum of power divisor function where some numerical evidence in the stochastic (Random matrix theory) and statistics context are presented such that we were able to derive new fit distribution model from the behavior of the sequence $σ_k(m) \bmod m$
