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arXiv 2103.12741astro-ph.SRphysics.flu-dynphysics.geo-ph
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低阶发电机系统的直接统计模拟

Direct statistical simulation of low-order dynamo systems

Kuan Li, J. B. Marston, Steven M. Tobias

摘要:

在本文中,我们调查的有效性直接统计模拟(DSS)的两个低阶模型的发电机行动。第一个模型,这是一个简单的太阳能和恒星发电机行动的模型,是三阶和立方非线性,而第二个只有二次非线性,并描述了对流和非周期性逆转磁场的相互作用。我们展示了如何DSS可以用来解决这些系统的统计方程的存在和不存在的随机项,截断的累积量层次在第二或第三阶。我们比较了两种不同的技术来解决的统计,时间步长-这是能够找到只有稳定的解决方案的方程的统计和直接检测的固定点。我们在Python中开发了一个完整的方法和符号包,用于推导控制累积展开中低阶动态系统的统计方程。我们证明,虽然直接检测的不动点是有效的和准确的DSS截断在二阶,高阶项的增加导致包括许多不稳定的不动点,可以发现通过直接检测的不动点迭代方法。在这些情况下,时间步进是一个更强大的协议,为DSS找到有意义的解决方案。

英文摘要:

In this paper we investigate the effectiveness of direct statistical simulation (DSS) for two low-order models of dynamo action. The first model, which is a simple model of solar and stellar dynamo action, is third-order and has cubic nonlinearities whilst the second has only quadratic nonlinearities and describes the interaction of convection and an aperiodically reversing magnetic field. We show how DSS can be utilised to solve for the statistics of these systems of equations both in the presence and the absence of stochastic terms, by truncating the cumulant hierarchy at either second or third order. We compare two different techniques for solving for the statistics, timestepping -- which is able to locate only stable solutions of the equations for the statistics and direct detection of the fixed points. We develop a complete methodology and symbolic package in Python for deriving the statistical equations governing the Low-order dynamic systems in cumulant expansions. We demonstrate that although direct detection of the fixed points is efficient and accurate for DSS truncated at second order, the addition of higher order terms leads to the inclusion of many unstable fixed points that may be found by direct detection of the fixed point by iterative methods. In those cases timestepping is a more robust protocol for finding meaninful solutions to DSS.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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