Measuring Galactic Extinction: A Test

We test the recently published all-sky reddening map of Schlegel, Finkbeiner & Davis (1998 [SFD]) using the extinction study of a region in the Taurus dark cloud complex by Arce & Goodman (1999 [AG]). In their study, AG use four different techniques to measure the amount and structure of the extinction toward Taurus, and all four techniques agree very well. Thus we believe that the AG results are a truthful representation of the extinction in the region and can be used to test the reliability of the SFD reddening map. The results of our test show that the SFD all-sky reddening map, which is based on data from COBE/DIRBE and IRAS/ISSA, overestimates the reddening by a factor of 1.3 to 1.5 in regions of smooth extinction with A_V > 0.5 mag. In some regions of steep extinction gradients the SFD map underestimates the reddening value, probably due to its low spatial resolution. We expect that the astronomical community will be using the SFD reddening map extensively. We offer this Letter as a cautionary note about using the SFD map in regions of high extinction (A_V > 0.5 mag), as it might not be giving accurate reddening values there.Comment: 14 pages (which include 2 pages of figures

The Effect of Noise on the Dust Temperature - Spectral Index Correlation

We investigate how uncertainties in flux measurements affect the results from modified blackbody SED fits. We show that an inverse correlation between the dust temperature T and spectral index (beta) naturally arises from least squares fits due to the uncertainties, even for sources with a single T and beta. Fitting SEDs to noisy fluxes solely in the Rayleigh-Jeans regime produces unreliable T and beta estimates. Thus, for long wavelength observations (lambda >~ 200 micron), or for warm sources (T >~ 60 K), it becomes difficult to distinguish sources with different temperatures. We assess the role of noise in recent observational results that indicate an inverse and continuously varying T - beta relation. Though an inverse and continuous T - beta correlation may be a physical property of dust in the ISM, we find that the observed inverse correlation may be primarily due to noise.Comment: 14 pages, including 5 Figures; Accepted for publication in Ap

The "True" Column Density Distribution in Star-Forming Molecular Clouds

We use the COMPLETE Survey's observations of the Perseus star-forming region to assess and intercompare three methods for measuring column density in molecular clouds: extinction mapping (NIR); thermal emission mapping (FIR); and mapping the intensity of CO isotopologues. The structures shown by all three tracers are morphologically similar, but important differences exist. Dust-based measures give similar, log-normal, distributions for the full Perseus region, once careful calibration corrections are made. We also compare dust- and gas-based column density distributions for physically-meaningful sub-regions of Perseus, and we find significant variations in the distributions for those regions. Even though we have used 12CO data to estimate excitation temperatures, and we have corrected for opacity, the 13CO maps seem unable to give column distributions that consistently resemble those from dust measures. We have edited out the effects of the shell around the B-star HD 278942. In that shell's interior and in the parts where it overlaps the molecular cloud, there appears to be a dearth of 13CO, likely due either to 13CO not yet having had time to form in this young structure, and/or destruction of 13CO in the molecular cloud. We conclude that the use of either dust or gas measures of column density without extreme attention to calibration and artifacts is more perilous than even experts might normally admit. And, the use of 13CO to trace total column density in detail, even after proper calibration, is unavoidably limited in utility due to threshold, depletion, and opacity effects. If one's main aim is to map column density, then dust extinction seems the best probe. Linear fits amongst column density tracers are given, quantifying the inherent uncertainties in using one tracer (when compared with others). [abridged]Comment: Accepted in ApJ. 13 pages, 6 color figures. It includes small changes to improve clarity. For a version with high-resolution figures see http://www.cfa.harvard.edu/COMPLETE/papers/Goodman_ColumnDensity.pd

The Spectral Correlation Function -- A New Tool for Analyzing Spectral-Line Maps

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 ISM with a data cube derived from MHD 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.Comment: 29 pages, including 4 figures (tar file submitted as source) See also: http://cfa-www.harvard.edu/~agoodman/scf/velocity_methods.htm

The ADS All-Sky Survey

The ADS All-Sky Survey (ADSASS) is an ongoing effort aimed at turning the NASA Astrophysics Data System (ADS), widely known for its unrivaled value as a literature resource for astronomers, into a data resource. The ADS is not a data repository per se, but it implicitly contains valuable holdings of astronomical data, in the form of images, tables and object references contained within articles. The objective of the ADSASS effort is to extract these data and make them discoverable and available through existing data viewers. The resulting ADSASS data layer promises to greatly enhance workflows and enable new research by tying astronomical literature and data assets into one resource.Astronom