论文标题

部分可观测时空混沌系统的无模型预测

Fraction of Stars in Clusters for the LEGUS Dwarf Galaxies

论文作者

Cook, D. O., Lee, J. C., Adamo, A., Calzetti, D., Chandar, R., Whitmore, B. C., Aloisi, A., Cignoni, M., Dale, D. A., Elmegreen, B. G., Fumagalli, M., Grasha, K., Johnson, K. E., Kennicutt, R. C., Kim, H., Linden, S. T., Messa, M., Östlin, G., Ryon, J. E., Sacchi, E., Thilker, D. A., Tosi, M., Wofford, A.

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 study the young star cluster populations in 23 dwarf and irregular galaxies observed by the HST Legacy ExtraGalactic Ultraviolet Survey (LEGUS), and examine relationships between the ensemble properties of the cluster populations and those of their host galaxies: star formation rate (SFR) density ($Σ_{\rm SFR}$). A strength of this analysis is the availability of SFRs measured from temporally resolved star formation histories which provide the means to match cluster and host-galaxy properties on several timescales (1-10, 1-100, and 10-100~Myr). Nevertheless, studies of this kind are challenging for dwarf galaxies due to the small numbers of clusters in each system. We mitigate these issues by combining the clusters across different galaxies with similar $Σ_{\rm SFR}$ properties. We find good agreement with a well-established relationship ($M_{V}^{brightest}$-SFR), but find no significant correlations between $Σ_{\rm SFR}$ and the slopes of the cluster luminosity function, mass function, nor the age distribution. We also find no significant trend between the the fraction of stars in bound clusters at different age ranges ($Γ_{1-10}$, $Γ_{10-100}$, and $Γ_{1-100}$) and $Σ_{\rm SFR}$ of the host galaxy. Our data show a decrease in $Γ$ over time (from 1-10 to 10-100~Myr) suggesting early cluster dissolution, though the presence of unbound clusters in the youngest time bin makes it difficult to quantify the degree of dissolution. While our data do not exhibit strong correlations between $Σ_{\rm SFR}$ and ensemble cluster properties, we cannot rule out that a weak trend might exist given the relatively large uncertainties due to low number statistics and the limited $Σ_{\rm SFR}$ range probed.

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