High-precision star-formation efficiency measurements in nearby clouds

On average molecular clouds convert only a small fraction epsilon(ff) of their mass into stars per free-fall time, but different star-formation theories make contrasting claims for how this low mean efficiency is achieved. To test these theories, we need precise measurements of both the mean value and the scatter of epsilon(ff), but high-precision measurements have been difficult because they require determining cloud-volume densities, from which we can calculate free-fall times. Until recently, most density estimates treated clouds as uniform spheres, while their real structures are often filamentary and highly non-uniform, yielding systematic errors in epsilon(ff) estimates and smearing real cloud-to-cloud variations. We recently developed a theoretical model to reduce this error by using column-density distributions in clouds to produce more accurate volume-density estimates. In this work, we apply this model to recent observations of 12 nearby molecular clouds. Compared to earlier analyses, our method reduces the typical dispersion of epsilon(ff) within individual clouds from 0.16 to 0.12 dex, and decreases the median value of epsilon(ff) over all clouds from approximate to 0.02 to approximate to 0.01. However, we find no significant change in the approximate to 0.2 dex cloud-to-cloud dispersion of epsilon(ff), suggesting the measured dispersions reflect real structural differences between clouds.