2017
DOI: 10.1007/s10509-017-3178-9
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An atlas of star-forming galaxy equivalent widths

Abstract: We present an atlas of starburst galaxy emission lines spanning 10 orders of magnitude in ionizing flux and 7 orders of magnitude in hydrogen number density. Coupling SEDs from Starburst99 with photoionization calculations from Cloudy, we track 96 emission lines from 977 Å to 205 µm which are common to nebular regions, have been observed in H II regions, and serve as useful diagnostic lines. Each simulation grid displays equivalent widths and contains ~1.5x10 4 photoionization models calculated by supplying a … Show more

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Cited by 4 publications
(4 citation statements)
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“…Nonetheless, insofar as the models are embedded in the experimental methodology, there is a sense in which this could be understood as a kind of experimenter's regress, spelled out in terms of models rather than detectors. There are also clear similarities here to the related "simulationist's regress"(Gelfert 2012;Meskhidze 2017). …”
supporting
confidence: 61%
“…Nonetheless, insofar as the models are embedded in the experimental methodology, there is a sense in which this could be understood as a kind of experimenter's regress, spelled out in terms of models rather than detectors. There are also clear similarities here to the related "simulationist's regress"(Gelfert 2012;Meskhidze 2017). …”
supporting
confidence: 61%
“…This has implications for statistical samples of galaxies that are analyzed with photoionization models that implicitly assume a particular geometrical configuration or mixing methodology in Figure 1. Such assumptions can lead to powerful selection effects (Ferguson et al 1997, Meskhidze & Richardson 2017. These assumptions could limit the applicability of simple relationships that scale physical properties (e.g., f AGN , M BH ) with emission lines ratios for large samples of galaxies.…”
Section: Discussionmentioning
confidence: 99%
“…In reality, H II regions vary drastically in size with a variety of physical conditions. We account for this fact by running suites of models varying φ H and n H to form a parameter space that captures the peak emission for most emission lines in the optical (Meskhidze & Richardson 2017). This approach addresses the restriction mentioned earlier, where clouds with different conditions are responsible for generating the observed emission lines strengths.…”
Section: Distribution Cloud Modelsmentioning
confidence: 99%
“…In particular, the left hand "wing" represents a sequence of star forming galaxies that excite clouds via starlight and the right hand "wing" represents a sequence of active galactic nuclei (AGN) that excite clouds via a combination of thermal and non-thermal sources. Variation in the star forming wing is traditionally interpreted as a change in ionization parameter, U, and metallicity, Z (Kewley et al 2001), or changing distributions in ionizing E-mail: crichardson17@elon.edu (CTR) flux and Z (Richardson et al 2016, Meskhidze & Richardson 2017.…”
Section: Introductionmentioning
confidence: 99%