2011
DOI: 10.1111/j.1365-2966.2011.18938.x
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Quantified H i morphology - I. Multi-wavelength analysis of the THINGS galaxies

Abstract: Galaxy evolution is driven to a large extent by interactions and mergers with other galaxies and the gas in galaxies is extremely sensitive to the interactions. One method to measure such interactions uses the quantified morphology of galaxy images. Well‐established parameters are Concentration, Asymmetry, Smoothness, Gini and M20 of a galaxy image. Thus far, the application of this technique has mostly been restricted to rest‐frame ultraviolet and optical images. However, with the new radio observatories bein… Show more

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Cited by 38 publications
(95 citation statements)
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References 68 publications
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“…Future observations of the molecular gas in these galaxies could provide some insight. A more detailed morphological analysis of the HI akin to that in Holwerda et al (2011) could also provide some clues, but the distances to these galaxies coupled with the short integration times of the observations described here make that type of work less robust.…”
Section: Discussionmentioning
confidence: 99%
“…Future observations of the molecular gas in these galaxies could provide some insight. A more detailed morphological analysis of the HI akin to that in Holwerda et al (2011) could also provide some clues, but the distances to these galaxies coupled with the short integration times of the observations described here make that type of work less robust.…”
Section: Discussionmentioning
confidence: 99%
“…We chose to ignore the positive background contribution to asymmetry as the Spitzer data have a very high signal-to-noise ratio and the added asymmetry from sky noise is negligible (see also Holwerda et al 2011d). Fully symmetric galaxies (e.g., ellipticals) would have very low values of asymmetry.…”
Section: Morphological Parametersmentioning
confidence: 99%
“…Uncertainties are based on randomly changing the central position (with the exception of Gini) and a random reshuffle of the pixel values to simulate shot noise. We note that these uncertainties should be viewed as formal errors and do not include the effects of, for example, disk inclination, which has a pronounced effect (see also Bendo et al 2007;Holwerda et al 2011d). We explore the possibility of an ordered morphological list based on these parameters and their ability to select out-ofthe-ordinary or merging morphology in the NIR.…”
Section: Morphology Catalogsmentioning
confidence: 99%
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“…We then recalculate the parameters for several (x c , y c ) values. After a number of iterations (10) (Holwerda et al 2011c), we compute the rms of the spread in parameter values as an approximate value of the uncertainty in the parameters.…”
Section: Uncertainty Estimationmentioning
confidence: 99%