Molecular line intensities as measures of cloud masses - I. Sensitivity of CO emissions to physical parameter variations
Molecular line intensities as measures of cloud masses - I. Sensitivity of CO emissions to physical parameter variations
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DOI：
10.1111/j.1365-2966.2006.10817.x
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发表时间：
2006-07
影响因子：
4.8
通讯作者：
T. Bell;È. Roueff;S. Viti;D. Williams
中科院分区：
文献类型：
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作者：
T. Bell;È. Roueff;S. Viti;D. Williams
对星系中分子气体含量的可靠估计在确定其动力学和恒星形成特性方面起着至关重要的作用。然而，主要的分子种类H-2很难直接观察到，特别是在大多数分子气体被认为存在的区域。因此，其质量通常通过假定与（CO）-C-12（J = 1 -> 0）发射线的积分强度成正比，使用CO至H-2转换因子X来推断。虽然X的典型值被广泛用于此类估计，但越来越多的理论和观测证据表明，在不同于当地邻域的条件下，转换因子可能会变化超过一个数量级。为了了解不断变化的环境条件对转换因子的影响，我们使用光子主导区域（PDR）随时间变化的化学模型，对独立PDR代码的关键结果进行基准测试，以确保可靠性，推导出各种物理参数的X理论估计值。基于这些结果，X因子对每个物理参数变化的敏感性被解释为云内的化学和物理过程。除了确认以前的观测得出的趋势，我们发现，时间依赖性的化学，往往被忽视，在这样的模型，有相当大的影响值的转换因子。
A reliable estimate of the molecular gas content in galaxies plays a crucial role in determining their dynamical and star-forming properties. However, H-2, the dominant molecular species, is difficult to observe directly, particularly in the regions where most molecular gas is thought to reside. Its mass is therefore commonly inferred by assuming a direct proportionality with the integrated intensity of the (CO)-C-12(J = 1 --> 0) emission line, using a CO-to-H-2 conversion factor, X. Although a canonical value for X is used extensively in such estimates, there is increasing evidence, both theoretical and observational, that the conversion factor may vary by over an order of magnitude under conditions different from those of the local neighbourhood. In an effort to understand the influence of changing environmental conditions on the conversion factor, we derive theoretical estimates of X for a wide range of physical parameters using a photon-dominated region (PDR) time-dependent chemical model, benchmarking key results against those of an independent PDR code to ensure reliability. Based on these results, the sensitivity of the X factor to change in each physical parameter is interpreted in terms of the chemistry and physical processes within the cloud. In addition to confirming previous observationally derived trends, we find that the time-dependence of the chemistry, often neglected in such models, has a considerable influence on the value of the conversion factor.