The spectral correlation function: A new tool for analyzing spectral line maps

Abstract

The "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.