The Fueling and Evolution of AGN: Internal and External Triggers

In this chapter, I review the fueling and evolution of active galactic nuclei (AGN) under the influence of internal and external triggers, namely intrinsic properties of host galaxies (morphological or Hubble type, color, presence of bars and other non-axisymmetric features, etc) and external factors such as environment and interactions. The most daunting challenge in fueling AGN is arguably the angular momentum problem as even matter located at a radius of a few hundred pc must lose more than 99.99 % of its specific angular momentum before it is fit for consumption by a BH. I review mass accretion rates, angular momentum requirements, the effectiveness of different fueling mechanisms, and the growth and mass density of black BHs at different epochs. I discuss connections between the nuclear and larger-scale properties of AGN, both locally and at intermediate redshifts, outlining some recent results from the GEMS and GOODS HST surveys.Comment: Invited Review Chapter to appear in LNP Volume on "AGN Physics on All Scales", Chapter 6, in press. 40 pages, 12 figures. Typo in Eq 5 correcte

Metal enrichment processes

There are many processes that can transport gas from the galaxies to their environment and enrich the environment in this way with metals. These metal enrichment processes have a large influence on the evolution of both the galaxies and their environment. Various processes can contribute to the gas transfer: ram-pressure stripping, galactic winds, AGN outflows, galaxy-galaxy interactions and others. We review their observational evidence, corresponding simulations, their efficiencies, and their time scales as far as they are known to date. It seems that all processes can contribute to the enrichment. There is not a single process that always dominates the enrichment, because the efficiencies of the processes vary strongly with galaxy and environmental properties.Comment: 18 pages, 8 figures, accepted for publication in Space Science Reviews, special issue "Clusters of galaxies: beyond the thermal view", Editor J.S. Kaastra, Chapter 17; work done by an international team at the International Space Science Institute (ISSI), Bern, organised by J.S. Kaastra, A.M. Bykov, S. Schindler & J.A.M. Bleeke

Measurement of event-shape observables in Z→ℓ+ℓ− events in pp collisions at √ s=7 TeV with the ATLAS detector at the LHC

Event-shape observables measured using charged particles in inclusive $Z$-boson events are presented, using the electron and muon decay modes of the $Z$ bosons. The measurements are based on an integrated luminosity of $1.1 {\rm fb}^{-1}$ of proton--proton collisions recorded by the ATLAS detector at the LHC at a centre-of-mass energy $\sqrt{s}=7$ TeV. Charged-particle distributions, excluding the lepton--antilepton pair from the $Z$-boson decay, are measured in different ranges of transverse momentum of the $Z$ boson. Distributions include multiplicity, scalar sum of transverse momenta, beam thrust, transverse thrust, spherocity, and $\mathcal{F}$-parameter, which are in particular sensitive to properties of the underlying event at small values of the $Z$-boson transverse momentum. The Sherpa event generator shows larger deviations from the measured observables than Pythia8 and Herwig7. Typically, all three Monte Carlo generators provide predictions that are in better agreement with the data at high $Z$-boson transverse momenta than at low $Z$-boson transverse momenta and for the observables that are less sensitive to the number of charged particles in the event.Comment: 36 pages plus author list + cover page (54 pages total), 14 figures, 4 tables, submitted to EPJC, All figures including auxiliary figures are available at http://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PAPERS/STDM-2014-0

External Learning Opportunities and the Diffusion of Process Innovations to Small Firms: The Case of Programmable Automation

In this chapter, we are concerned with explaining which types of firms have failed to adopt well-known improvements in process technology. This problem has, of course, been the underlying concern of all studies of diffusion “to rationalize why, if a new technology is superior, it is not taken up by all potential adopters” (Stoneman, 1983). Drawing on various theoretical perspectives, we identify a number of different barriers to adoption. With data collected from a 1987 nationally representative sample of US establishments in 21 metal-working and machinery manufacturing industries, we then construct a multivariate logistic regression model to empirically test for the effects of these factors on the likelihood of adoption of a particular process innovation, namely programmable automation (PA) machine tools