Rapid Star Formation in the Presence of Active Galactic Nuclei

Recent observations reveal galaxies in the early Universe (2<z<6.4) with large reservoirs of molecular gas and extreme star formation rates. For a very large range of sources, a tight relationship exists between star formation rate and the luminosity of the HCN J=1-0 spectral line, but sources at redshifts of z~2 and beyond do not follow this trend. The deficit in HCN is conventionally explained by an excess of infrared (IR) radiation due to active galactic nuclei (AGN). We show in this letter not only that the presence of AGN cannot account for the excess of IR over molecular luminosity, but also that the observed abundance of HCN is in fact consistent with a population of stars forming from near-primordial gas.Comment: 4 pages, 1 figure. Accepted by the Astrophysical Journal Letter

Morphology in the Era of Large Surveys

The study of galaxies has changed dramatically over the past few decades with the advent of large-scale astronomical surveys. These large collaborative efforts have made available high-quality imaging and spectroscopy of hundreds of thousands of systems, providing a body of observations which has significantly enhanced our understanding not only of cosmology and large-scale structure in the universe but also of the astrophysics of galaxy formation and evolution. Throughout these changes, one thing that has remained constant is the role of galaxy morphology as a clue to understanding galaxies. But obtaining morphologies for large numbers of galaxies is challenging; this topic, "Morphology in the era of large surveys", was the subject of a recent discussion meeting at the Royal Astronomical Society, and this "Astronomy and Geophysics" article is a report on that meeting.Comment: Meeting Report article published in the October 2013 issue of the Royal Astronomical Society journal Astronomy and Geophysics. 4 page pdf with colour image

Galaxy Zoo: Morphological Classification and Citizen Science

We provide a brief overview of the Galaxy Zoo and Zooniverse projects, including a short discussion of the history of, and motivation for, these projects as well as reviewing the science these innovative internet-based citizen science projects have produced so far. We briefly describe the method of applying en-masse human pattern recognition capabilities to complex data in data-intensive research. We also provide a discussion of the lessons learned from developing and running these community--based projects including thoughts on future applications of this methodology. This review is intended to give the reader a quick and simple introduction to the Zooniverse.Comment: 11 pages, 1 figure; to be published in Advances in Machine Learning and Data Mining for Astronom

Citizen Science: Contributions to Astronomy Research

The contributions of everyday individuals to significant research has grown dramatically beyond the early days of classical birdwatching and endeavors of amateurs of the 19th century. Now people who are casually interested in science can participate directly in research covering diverse scientific fields. Regarding astronomy, volunteers, either as individuals or as networks of people, are involved in a variety of types of studies. Citizen Science is intuitive, engaging, yet necessarily robust in its adoption of sci-entific principles and methods. Herein, we discuss Citizen Science, focusing on fully participatory projects such as Zooniverse (by several of the au-thors CL, AS, LF, SB), with mention of other programs. In particular, we make the case that citizen science (CS) can be an important aspect of the scientific data analysis pipelines provided to scientists by observatories.Comment: 12 pages, 2 figure