Beecroft Institute for Particle Astrophysics and Cosmology

Abstract:

At the peak of cosmic star formation (1 ≲ z ≲ 2), the majority of star-forming galaxies hosted compact, star-forming clumps, which were responsible for a large fraction of cosmic star formation. By comparison, ≲5% of local star-forming galaxies host comparable clumps. In this work, we investigate the link between the environmental conditions surrounding local (z < 0.04) galaxies and the prevalence of clumps in these galaxies. To obtain our clump sample, we use a Faster R-CNN object detection network trained on the catalog of clump labels provided by the Galaxy Zoo: Clump Scout project, then apply this network to detect clumps in approximately 240,000 Sloan Digital Sky Survey galaxies (originally selected for Galaxy Zoo 2). The resulting sample of 41,445 u-band bright clumps in 34,246 galaxies is the largest sample of clumps yet assembled. We then select a volume-limited sample of 9964 galaxies and estimate the density of their local environment using the distance to their projected fifth nearest neighbor. We find a robust correlation between environment and the clumpy fraction (f clumpy) for star-forming galaxies (specific star formation rate, sSFR > 10−2 Gyr−1) but find little to no relationship when controlling for galaxies’ sSFR or color. Further, f clumpy increases significantly with sSFR in local galaxies, particularly above sSFR > 10−1 Gyr−1. We posit that a galaxy’s gas fraction primarily controls the formation and lifetime of its clumps, and that environmental interactions play a smaller role.

Abstract:

<jats:p>The study of third-order statistics in large-scale structure analyses has been hampered by the increased complexity of bispectrum estimators (compared to power spectra), the large dimensionality of the data vector, and the difficulty in estimating its covariance matrix. In this paper we present the filtered-squared bispectrum (FSB), an estimator of the projected bispectrum effectively consisting of the cross-correlation between the square of a field filtered on a range of scales and the original field. Within this formalism, we are able to recycle much of the infrastructure built around power spectrum measurement to construct an estimator that is both fast and robust against mode-coupling effects caused by incomplete sky observations. Furthermore, we demonstrate that the existing techniques for the estimation of analytical power spectrum covariances can be used within this formalism to calculate the bispectrum covariance at very high accuracy, naturally accounting for the most relevant Gaussian and non-Gaussian contributions in a model-independent manner.</jats:p>

Abstract: