{"title":"C","authors":"M. Charlebois, L. Drissen, A. Bernier, F. Grandmont, L. Binette","doi":"10.1515/9783110723922-072","DOIUrl":null,"url":null,"abstract":"It is generally believed that O stars, confined near the galactic midplane, are somehow able to photoionize a significant fraction of what is termed the “diffuse ionized gas” (DIG) of spiral galaxies, which can extend up to 1–2 kpc above the galactic midplane. The heating of the DIG remains poorly understood, however, as simple photoionization models do not reproduce the observed line ratio correlations well or the DIG temperature. We present turbulent mixing layer (TML) models in which warm photoionized condensations are immersed in a hot supersonic wind. Turbulent dissipation and mixing generate an intermediate region where the gas is accelerated, heated, and mixed. The emission spectrum of such layers is compared with observations of Rand of the DIG in the edge-on spiral NGC 891. We generate two sequence of models that fit the line ratio correlations between [S ii]/Hα, [O i]/Hα, [N ii]/[S ii], and [O iii]/Hβ reasonably well. In one sequence of models, the hot wind velocity increases, while in the other, the ionization parameter and layer opacity increase. Despite the success of the mixing layer models, the overall efficiency in reprocessing the stellar UV is much too low, much less than 1%, which compels us to reject the TML model in its present form.","PeriodicalId":93403,"journal":{"name":"ACM CHIL 2021 : proceedings of the 2021 ACM Conference on Health, Inference, and Learning : April 8-9, 2021, Virtual Event. ACM Conference on Health, Inference, and Learning (2021 : Online)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2021-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACM CHIL 2021 : proceedings of the 2021 ACM Conference on Health, Inference, and Learning : April 8-9, 2021, Virtual Event. ACM Conference on Health, Inference, and Learning (2021 : Online)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1515/9783110723922-072","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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Abstract

It is generally believed that O stars, confined near the galactic midplane, are somehow able to photoionize a significant fraction of what is termed the “diffuse ionized gas” (DIG) of spiral galaxies, which can extend up to 1–2 kpc above the galactic midplane. The heating of the DIG remains poorly understood, however, as simple photoionization models do not reproduce the observed line ratio correlations well or the DIG temperature. We present turbulent mixing layer (TML) models in which warm photoionized condensations are immersed in a hot supersonic wind. Turbulent dissipation and mixing generate an intermediate region where the gas is accelerated, heated, and mixed. The emission spectrum of such layers is compared with observations of Rand of the DIG in the edge-on spiral NGC 891. We generate two sequence of models that fit the line ratio correlations between [S ii]/Hα, [O i]/Hα, [N ii]/[S ii], and [O iii]/Hβ reasonably well. In one sequence of models, the hot wind velocity increases, while in the other, the ionization parameter and layer opacity increase. Despite the success of the mixing layer models, the overall efficiency in reprocessing the stellar UV is much too low, much less than 1%, which compels us to reject the TML model in its present form.
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C
人们普遍认为,被限制在银河系中部附近的O型恒星,在某种程度上能够光电离相当一部分被称为螺旋星系的“漫射电离气体”(DIG)的物质,它可以延伸到银河系中部以上1 - 2kpc。然而,由于简单的光电离模型不能很好地再现观测到的线比相关性或DIG温度,因此对DIG的加热仍然知之甚少。我们提出了湍流混合层(TML)模型,在该模型中,热光离冷凝物浸没在高温超音速风中。湍流耗散和混合产生一个中间区域,在这里气体被加速、加热和混合。这些层的发射光谱与DIG的Rand在边缘螺旋NGC 891中的观测结果进行了比较。我们生成了两个序列的模型,它们很好地拟合了[S ii]/Hα、[O i]/Hα、[N ii]/[S ii]和[O iii]/Hβ之间的线比相关性。在一个模式序列中,热风速度增加,而在另一个模式序列中,电离参数和层不透明度增加。尽管混合层模型取得了成功,但再处理恒星紫外线的总体效率太低,远低于1%,这迫使我们拒绝目前形式的TML模型。
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