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dc.contributor.authorRosolowsky, Erik
dc.contributor.authorGoodman, Alyssa
dc.contributor.authorWilner, David
dc.contributor.authorWilliams, Jonathan
dc.date.accessioned2019-09-24T17:25:08Z
dc.date.issued1999
dc.identifier.citationRosolowsky, Erik W., Alyssa A. Goodman, David J. Wilner, and Jonathan P. Williams. 1999. “The Spectral Correlation Function: A New Tool for Analyzing Spectral Line Maps.” The Astrophysical Journal 524 (2): 887–94. https://doi.org/10.1086/307863.
dc.identifier.issn0004-637X
dc.identifier.issn1538-4357
dc.identifier.urihttp://nrs.harvard.edu/urn-3:HUL.InstRepos:41397405*
dc.description.abstractThe "spectral correlation function" analysis we introduce in this paper is a new tool for analyzing spectral line data cubes. Our initial tests, carried out on a suite of observed and simulated data cubes, indicate that the spectral correlation function (SCF) is likely to be a more discriminating statistic than other statistical methods normally applied. The SCF is a measure of similarity between neighboring spectra in the data cube. When the SCF is used to compare a data cube consisting of spectral line observations of the interstellar medium (ISM) with a data cube derived from MI-ID simulations of molecular clouds, it can find differences that are not found by other analyses. The initial results presented here suggest that the inclusion of self-gravity in numerical simulations is critical for reproducing the correlation behavior of spectra in star-forming molecular clouds.
dc.language.isoen_US
dc.publisherAmerican Astronomical Society
dash.licenseLAA
dc.titleThe spectral correlation function: A new tool for analyzing spectral line maps
dc.typeJournal Article
dc.description.versionAccepted Manuscript
dc.relation.journalThe Astrophysical Journal
dash.depositing.authorGoodman, Alyssa::c0b10f48de57a53ff56cc8d4fee4155a::600
dc.date.available2019-09-24T17:25:08Z
dash.workflow.comments1Science Serial ID 95662
dc.identifier.doi10.1086/307863
dash.source.volume524;2
dash.source.page887


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