标题： 条带82中光学浮云的分形维数 显示英文标题

标题： Fractal dimension of optical cirrus in Stripe82

摘要： 尘埃云的几何特性提供了有关形成此类云物理过程的重要信息。 其中一个特征是投射到天空平面的云的 $2D$ 分形维数 $D$。 在之前的研究中（大多数基于红外数据），发现单个云的分形维数范围在1.1到1.7之间，优选值为1.2至1.4。 在目前的工作中，我们使用斯隆数字巡天（SDSS）的Stripe82数据来测量薄雾云的分形维数。 这是第一次针对光学数据进行这样的测量，其分辨率显著高于红外数据。 为了确定分形维数，采用了周长-面积法。 我们还考虑了对应光学场的红外（IRAS和赫歇尔）对应物，以比较光学和红外之间的结果。 我们发现光学中所有云的平均分形维数为 $\langle D \rangle =1.69^{+0.05}_{-0.05}$，这明显大于其红外对应物的分形维数 $\langle D\rangle=1.38^{+0.07}_{-0.06}$。 我们研究了这种差异的几个原因（掩模选择和最小轮廓水平、图像和角度分辨率等）， 并发现对于我们大约一半的观测场，光学和红外数据的不同角度分辨率（点扩散函数）可以解释相应分形维数之间的差异。 对于其余一半的观测场，红外和可见光数据的分形维数仍然不一致，这可能与云的物理性质有关，但需要进一步的物理模拟来证明这一点。 显示英文摘要

摘要： The geometric characteristics of dust clouds provide important information on the physical processes that structure such clouds. One of such characteristics is the $2D$ fractal dimension $D$ of a cloud projected onto the sky plane. In previous studies, which were mostly based on infrared (IR) data, the fractal dimension of individual clouds was found to be in a range from 1.1 to 1.7 with a preferred value of 1.2--1.4. In the present work, we use data from Stripe82 of the Sloan Digital Sky Survey to measure the fractal dimension of the cirrus clouds. This is done here for the first time for optical data with significantly better resolution as compared to IR data. To determine the fractal dimension, the perimeter-area method is employed. We also consider IR (IRAS and Herschel) counterparts of the corresponding optical fields to compare the results between the optical and IR. We find that the averaged fractal dimension across all clouds in the optical is $\langle D \rangle =1.69^{+0.05}_{-0.05}$ which is significantly larger then the fractal dimension of its IR counterparts $\langle D\rangle=1.38^{+0.07}_{-0.06}$. We examine several reasons for this discrepancy (choice of masking and minimal contour level, image and angular resolution, etc.) and find that for approximately half of our fields the different angular resolution (point spread function) of the optical and IR data can explain the difference between the corresponding fractal dimensions. For the other half of the fields, the fractal dimensions of the IR and visual data remain inconsistent, which can be associated with physical properties of the clouds, but further physical simulations are required to prove it.