论文标题
使用线排放了解分子云运动学测量的偏差
Understanding biases in measurements of molecular cloud kinematics using line emission
论文作者
论文摘要
使用多种示踪剂的分子线观测通常用于研究分子云的运动学结构。但是，即使在同一区域中，云速度分散体的测量也常常产生不一致的结果。这种分歧的原因尚不完全清楚，因为分子线观测值遭受许多偏见。在本文中，我们解开并研究了各种因素，这些因素通过构建一组分子云的自我填充磁性水力动力学模拟的多种示踪剂的合成位置位置位置偏差来驱动线宽测量偏差。我们将这些数据立方体的合成观察结果得出的线宽与模拟中的真实值进行了比较。我们发现，通过不同示踪剂测量的线宽差异是由密度依赖性激发的组合驱动的，这些示踪剂对较高密度敏感的示踪剂采样较小的区域，具有较小的速度分散，不透明度扩展，尤其是对于高度光学上的较厚较厚的示踪剂，例如CO，以及诸如CO，有限的分辨率和敏感性，以抑制排放量的固定线。我们发现，按固定信号与噪声比，三个常用的示踪剂，j = 4-> 3线，j = 1-> 0的c^{18} o的j = 1-> 0和（1,1）反转NH_3的反转过渡，通常提供了这些竞争偏见之间的最佳折衷，并在这些竞争偏见之间提供了反映的kinem kinem的估算，以估算kinem kinem的估算。 10％的云磁场强度，进化状态或视线相对于磁场的方向。
Molecular line observations using a variety of tracers are often used to investigate the kinematic structure of molecular clouds. However, measurements of cloud velocity dispersions with different lines, even in the same region, often yield inconsistent results. The reasons for this disagreement are not entirely clear since molecular line observations are subject to a number of biases. In this paper, we untangle and investigate various factors that drive linewidth measurement biases by constructing synthetic position-position-velocity cubes for a variety of tracers from a suite of self-gravitating magnetohydrodynamic simulations of molecular clouds. We compare linewidths derived from synthetic observations of these data cubes to the true values in the simulations. We find that differences in linewidth as measured by different tracers are driven by a combination of density-dependent excitation, whereby tracers that are sensitive to higher densities sample smaller regions with smaller velocity dispersions, opacity broadening, especially for highly optically thick tracers such as CO, and finite resolution and sensitivity, which suppress the wings of emission lines. We find that, at fixed signal to noise ratio, three commonly-used tracers, the J=4->3 line of CO, the J=1->0 line of C^{18}O and the (1,1) inversion transition of NH_3, generally offer the best compromise between these competing biases, and produce estimates of the velocity dispersion that reflect the true kinematics of a molecular cloud to an accuracy of about 10% regardless of the cloud magnetic field strengths, evolutionary state, or orientations of the line of sight relative to the magnetic field.
