Beecroft Institute for Particle Astrophysics and Cosmology

Abstract:

We use multiwavelength (0.12-500 μm) photometry from Herschel-ATLAS, WISE, UKIDSS, SDSS and GALEX to study 23 nearby spheroidal galaxies with prominent dust lanes (DLSGs). DLSGs are considered to be remnants of recent minor mergers, making them ideal laboratories for studying both the interstellar medium (ISM) of spheroids and minor-merger-driven star formation in thenearby Universe. The DLSGs exhibit star formation rates (SFRs) between 0.01and 10M⊙ yr-1 with a median of 0.26M⊙ yr-1 (a factor of 3.5 greater thanthe average SG). The median dust mass, dust-to-stellar mass ratio and dust temperature in these galaxies are around 107.6M⊙, ≈0.05 per cent and ≈19.5K, respectively. The dust masses are at least a factor of 50 greater than that expected from stellar mass loss and, like the SFRs, show no correlationwith galaxy luminosity, suggesting that both the ISM and the star formationhave external drivers. Adopting literature gas-to-dust ratios and star formation histories derived from fits to the panchromatic photometry, we estimate that the median current and initial gasto- stellar mass ratios in these systems are ≈4 and ≈7 per cent, respectively. If, as indicated by recent work, minor mergers that drive star formation in spheroids with (NUV - r) > 3.8 (the colour range of our DLSGs) have stellar mass ratios between 1:6 and 1:10, then the satellite gas fractions are likely =50 per cent. © 2013 The Authors Published by Oxford University Press on behalf of the Royal Astronomical Society.

Abstract:

In order to understand the physical mechanisms at work during the formation of massive early-type galaxies, we performed six zoomed hydrodynamical cosmological simulations of haloes in the mass range 4.3×1012 ≤Mvir ≤8.0×1013M at z=0, using the AdaptiveMesh Refinement code RAMSES. These simulations explore the role of active galactic nuclei (AGN), through jets powered by the accretion on to supermassive black holes on the formation of massive elliptical galaxies. In the absence of AGN feedback, large amounts of stars accumulate in the central galaxies to form overly massive, blue, compact and rotation-dominated galaxies. Powerful AGN jets transform the central galaxies into red extended and dispersion-dominated galaxies. This morphological transformation of disc galaxies into elliptical galaxies is driven by the efficient quenching of the in situ star formation due to AGN feedback, which transform these galaxies into systems built up by accretion. For galaxies mainly formed by accretion, the proportion of stars deposited farther away from the centre increases, and galaxies have larger sizes. The accretion is also directly responsible for randomizing the stellar orbits, increasing the amount of dispersion over rotation of stars as a function of time. Finally, we find that our galaxies simulated with AGN feedback better match the observed scaling laws, such as the size-mass, velocity dispersion-mass, Fundamental Plane relations and slope of the total density profiles at z 0, from dynamical and strong lensing constraints.© 2013 The Authors.

Abstract:

The Zooniverse (zooniverse.org) began in 2007 with the launch of Galaxy Zoo, a project in which more than 175,000 people provided shape analyses of more than 1 million galaxy images sourced from the Sloan Digital Sky Survey. These galaxy 'classifications', some 60 million in total, have subsequently been used to produce more than 50 peer-reviewed publications based not only on the original research goals of the project but also because of serendipitous discoveries made by the volunteer community. Based upon the success of Galaxy Zoo the team have gone on to develop more than 25 web-based citizen science projects, all with a strong research focus in a range of subjects from astronomy to zoology where human-based analysis still exceeds that of machine intelligence. Over the past 6 years Zooniverse projects have collected more than 300 million data analyses from over 1 million volunteers providing fantastically rich datasets for not only the individuals working to produce research from their projects but also the machine learning and computer vision research communities. The Zooniverse platform has always been developed to be the 'simplest thing that works', implementing only the most rudimentary algorithms for functionality such as task allocation and user-performance metrics. These simplifications have been necessary to scale the Zooniverse so that the core team of developers and data scientists can remain small and the cost of running the computing infrastructure relatively modest. To date these simplifications have been acceptable for the data volumes and analysis tasks being addressed. This situation however is changing: next generation telescopes such as the Large Synoptic Sky Telescope (LSST) will produce data volumes dwarfing those previously analyzed. If citizen science is to have a part to play in analyzing these next-generation datasets then the Zooniverse will need to evolve into a smarter system capable for example of modeling the abilities of users and the complexities of the data being classified in real time. In this session we will outline the current architecture of the Zooniverse platform and introduce new functionality being developed that should be of interest to the HCOMP community. Our platform is evolving into a system capable of integrating human and machine intelligence in a live environment. Data APIs providing realtime access to 'event streams' from the Zooniverse infrastructure are currently being tested as well as API endpoints for making decisions about for example what piece of data to show next to a volunteer as well as when to retire a piece of data from the live system because a consensus has been reached.

Abstract:

We study ~330 massive (M* > 109.5M⊙), newborn spheroidal galaxies (SGs) around the epoch of peak star formation (1 < z < 3) to explore the high-redshift origin of SGs and gain insight into when and how the old stellar populations that dominate today's Universe formed. The sample is drawn from the Hubble Space Telescope (HST)/WFC3 Early-Release Science programme, which provides deep 10-filter (0.2-1.7 μm) HST imaging over one-third of the GOODS-South field. We find that the star formation episodes that built our SGs likely peaked in the redshift range 2 < z < 5 (with a median of z ~ 3) and have decay time-scales shorter than ~1.5Gyr. Starburst time-scales and ages show no trend with stellar mass in the range 109.5 < M* < 1010.5 M⊙. However, the time-scales show increased scatter towards lower values (<0.3 Gyr) for M* > 1010.5M⊙, and an age trend becomes evident in this mass regime: SGs with M* > 1011.5M⊙ are ~2 Gyr older than their counterparts with M* < 1010.5M⊙. Nevertheless, a smooth downsizing trend with galaxy mass is not observed, and the large scatter in starburst ages indicates that SGs are not a particularly coeval population. Around half of the blue SGs appear not to drive their star formation via major mergers, and those that have experienced a recent major merger show only modest enhancements (~40 per cent) in their specific star formation rates. Our empirical study indicates that processes other than major mergers (e.g. violent disc instability driven by cold streams and/or minor mergers) likely play a dominant role in building SGs, and creating a significant fraction of the old stellar populations that dominate today's Universe. © 2012 The Authors Published by Oxford University Press on behalf of the Royal Astronomical Society.