论文标题

部分可观测时空混沌系统的无模型预测

Relationships Between Stellar Velocity Dispersion and the Atmospheres of Early-Type Galaxies

论文作者

Frisbie, R. L. S., Donahue, M., Voit, G. M., Lakhchaura, K., Werner, N., Sun, M.

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。

The Voit et al. (2020) black hole feedback valve model predicts relationships between stellar velocity dispersion and atmospheric structure among massive early-type galaxies. In this work, we test that model using the Chandra archival sample of 49 early-type galaxies from Lakhchaura et al. (2018). We consider relationships between stellar velocity dispersion and entropy profile slope, multiphase gas extent, and the ratio of cooling time to freefall time. We also define subsamples based on data quality and entropy profile properties that clarify those relationships and enable more specific tests of the model predictions. We find that the atmospheric properties of early-type galaxies generally align with the predictions of the Voit et al. (2020) model, in that galaxies with greater stellar velocity dispersion tend to have radial profiles of pressure, gas density, and entropy with steeper slopes and less extended multiphase gas. Quantitative agreement with the model predictions improves when the sample is restricted to have low central entropy and stellar velocity dispersion of between 220 and 300 km/s.

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