On Measuring Divergence for Magnetic Field Modeling
On Measuring Divergence for Magnetic Field Modeling
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DOI：
10.3847/1538-4357/aba752
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发表时间：
2020-08
期刊：
影响因子：
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通讯作者：
S. Gilchrist;K. Leka;G. Barnes;M. Wheatland;M. DeRosa
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文献类型：
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作者：
S. Gilchrist;K. Leka;G. Barnes;M. Wheatland;M. DeRosa
物理磁场的发散度为零。然而，构建模型场和计算散度时的数值误差在这些计算中引入了有限散度。测量散度的一个流行指标是平均分数通量。我们表明，它随着计算网格的大小而缩放，并且可能是散度的一个不好的衡量标准，因为它会随着网格分辨率的增加而变得任意小，而散度实际上并没有减少。我们定义了该指标的修改版本，该版本不随网格大小而缩放。我们将新的度量标准应用到 DeRosa 等人的结果中，他们根据不同空间分辨率下的太阳边界数据测量了一系列非线性无力场模型的日冕磁场。我们计算了 DeRosa 等人的一些分歧指标。数据并使用非参数方法分析空间分辨率对这些指标的影响。我们发现 DeRosa 等人报告的一些趋势。是由于 的固有缩放比例造成的。我们还发现，对于同一数据集，不同的指标会给出不同的结果，因此通过多个指标来衡量差异是有价值的。
A physical magnetic field has a divergence of zero. Numerical error in constructing a model field and computing the divergence, however, introduces a finite divergence into these calculations. A popular metric for measuring divergence is the average fractional flux . We show that scales with the size of the computational mesh, and may be a poor measure of divergence because it becomes arbitrarily small for increasing mesh resolution, without the divergence actually decreasing. We define a modified version of this metric that does not scale with mesh size. We apply the new metric to the results of DeRosa et al., who measured for a series of nonlinear force-free field models of the coronal magnetic field based on solar boundary data binned at different spatial resolutions. We compute a number of divergence metrics for the DeRosa et al. data and analyze the effect of spatial resolution on these metrics using a nonparametric method. We find that some of the trends reported by DeRosa et al. are due to the intrinsic scaling of . We also find that different metrics give different results for the same data set and therefore there is value in measuring divergence via several metrics.