Person:

Goodman, Alyssa

We present a study of dense structures in the L1495 filament in the Taurus Molecular Cloud and examine its star-forming properties. In particular we construct a dust extinction map of the filament using deep near-infrared observations, exposing its small-scale structure in unprecedented detail. The filament shows highly fragmented substructures and a high mass-per-length value of (M_{line} = 17 M \odot \ pc^{-1}), reflecting star-forming potential in all parts of it. However, a part of the filament, namely B211, is remarkably devoid of young stellar objects. We argue that in this region the initial filament collapse and fragmentation is still taking place and star formation is yet to occur. In the star-forming part of the filament, we identify 39 cores with masses from (0.4 to 10 M \odot) and preferred separations in agreement with the local Jeans length. Most of these cores exceed the Bonnor-Ebert critical mass, and are therefore likely to collapse and form stars. The Dense Core Mass Function follows a power law with exponent (\lceil = 1.2 \pm 0.2), a form commonly observed in star-forming regions.

We investigate the shape of the extinction law in two (1^{\circ}) square fields of the Perseus molecular cloud complex. We combine deep red-optical (r, i and z band) observations obtained using Megacam on the MMT with UKIRT (United Kingdom Infrared Telescope) Infrared Deep Sky Survey near-infrared (J, H and K band) data to measure the colours of background stars. We develop a new hierarchical Bayesian statistical model, including measurement error, intrinsic colour variation, spectral type and dust reddening, to simultaneously infer parameters for individual stars and characteristics of the population. We implement an efficient Markov chain Monte Carlo algorithm utilizing generalized Gibbs sampling to compute coherent probabilistic inferences. We find a strong correlation between the extinction ((A_V)) and the slope of the extinction law (parametrized by (R_V)). Because the majority of the extinction towards our stars comes from the Perseus molecular cloud, we interpret this correlation as evidence of grain growth at moderate optical depths. The extinction law changes from the ‘diffuse’ value of (R_V \sim 3) to the 'dense cloud' value of (R_V \sim 5) as the column density rises from (A_V = 2) to 10 mag. This relationship is similar for the two regions in our study, despite their different physical conditions, suggesting that dust grain growth is a fairly universal process.

We investigate how uncertainties in flux measurements affect the results from modified blackbody spectral energy distribution (SED) fits. We show that an inverse correlation between the dust temperature T and spectral index β 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 > \sim 200 \mu m)), or for warm sources ((T >\sim 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 interstellar medium, we find that the observed inverse correlation may be primarily due to noise.

In this paper, we present a dust emission map of the starless core TMC-1C taken at (2100 \mu m). Along with maps at 160, 450, 850, and 1200 μm, we study the dust emissivity spectral index from the (sub)millimeter spectral energy distribution, and find that it is close to the typically assumed value of (\beta = 2). We also map the dust temperature and column density in TMC-1C, and find that at the position of the dust peak ((A_{V} \sim 50)) the line-of-sight-averaged temperature is (\sim 7) K. Employing simple Monte Carlo modeling, we show that the data are consistent with a constant value for the emissivity spectral index over the whole map of TMC-1C.

We use the COMPLETE Survey's observations of the Perseus star-forming region to assess and intercompare the three methods used for measuring column density in molecular clouds: near-infrared (NIR) extinction mapping; thermal emission mapping in the far-IR; and mapping the intensity of CO isotopologues. Overall, the structures shown by all three tracers are morphologically similar, but important differences exist among the tracers. We find that the dust-based measures (NIR extinction and thermal emission) give similar, log-normal, distributions for the full ((\sim20 \ pc \ scale)) Perseus region, once careful calibration corrections are made. We also compare dust- and gas-based column density distributions for physically meaningful subregions of Perseus, and we find significant variations in the distributions for those ((smaller, \sim few \ pc \ scale)) regions. Even though we have used (^{12}CO) data to estimate excitation temperatures, and we have corrected for opacity, the (^{13}CO) 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 from the column density distribution comparisons. In that shell's interior and in the parts where it overlaps the molecular cloud, there appears to be a dearth of (^{13}CO), which is likely due either to (^{13}CO) not yet having had time to form in this young structure and/or destruction of (^{13}CO) in the molecular cloud by the HD 278942's wind and/or radiation. We conclude that the use of either dust or gas measures of column density without extreme attention to calibration (e.g., of thermal emission zero-levels) and artifacts (e.g., the shell) is more perilous than even experts might normally admit. And, the use of (^{13}CO) data 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 (rather than temperature or kinematics), then dust extinction seems the best probe, up to a limiting extinction caused by a dearth of sufficient background sources. Linear fits among all three tracers' estimates of column density are given, allowing us to quantify the inherent uncertainties

We investigate the effect of line-of-sight temperature variations and noise on two commonly used methods to determine dust properties from dust-continuum observations of dense cores. One method employs a direct fit to a modified blackbody spectral energy distribution (SED); the other involves a comparison of flux ratios to an analytical prediction. Fitting fluxes near the SED peak produces inaccurate temperature and dust spectral index estimates due to the line-of-sight temperature (and density) variations. Longer wavelength fluxes in the Rayleigh-Jeans part of the spectrum ((>{\sim} 600 \mu m) for typical cores) may more accurately recover the spectral index, but both methods are very sensitive to noise. The temperature estimate approaches the density-weighted temperature, or "column temperature," of the source as short wavelength fluxes are excluded. An inverse temperature-spectral index correlation naturally results from SED fitting, due to the inaccurate isothermal assumption, as well as noise uncertainties. We show that above some "threshold" temperature, the temperatures estimated through the flux ratio method can be highly inaccurate. In general, observations with widely separated wavelengths, and including shorter wavelengths, result in higher threshold temperatures; such observations thus allow for more accurate temperature estimates of sources with temperatures less than the threshold temperature. When only three fluxes are available, a constrained fit, where the spectral index is fixed, produces less scatter in the temperature estimate when compared to the estimate from the flux ratio method.