The thick disk rotation-metallicity correlation as a fossil of an "inverse chemical gradient" in the early Galaxy

The thick disk rotation--metallicity correlation, \partial V_\phi/\partial[Fe/H] =40\div 50 km s^{-1}dex^{-1} represents an important signature of the formation processes of the galactic disk. We use nondissipative numerical simulations to follow the evolution of a Milky Way (MW)-like disk to verify if secular dynamical processes can account for this correlation in the old thick disk stellar population. We followed the evolution of an ancient disk population represented by 10 million particles whose chemical abundances were assigned by assuming a cosmologically plausible radial metallicity gradient with lower metallicity in the inner regions, as expected for the 10-Gyr-old MW. Essentially, inner disk stars move towards the outer regions and populate layers located at higher |z|. A rotation--metallicity correlation appears, which well resembles the behaviour observed in our Galaxy at a galactocentric distance between 8 kpc and 10 kpc. In particular,we measure a correlation of \partial V_\phi/\partial[Fe/H]\simeq 60 km s^{-1}dex^{-1} for particles at 1.5 kpc < |z| < 2.0 kpc that persists up to 6 Gyr. Our pure N-body models can account for the V_\phi vs. [Fe/H] correlation observed in the thick disk of our Galaxy, suggesting that processes internal to the disk such as heating and radial migration play a role in the formation of this old stellar component. In this scenario, the positive rotation-metallicity correlation of the old thick disk population would represent the relic signature of an ancient "inverse" chemical (radial) gradient in the inner Galaxy, which resulted from accretion of primordial gas.Comment: Accepted for publication on Astronomy and Astrophysic

High-resolution computed tomography reconstructions of invertebrate burrow systems

The architecture of biogenic structures can be highly influential in determining species contributions to major soil and sediment processes, but detailed 3-D characterisations are rare and descriptors of form and complexity are lacking. Here we provide replicate high-resolution micro-focus computed tomography (μ-CT) data for the complete burrow systems of three co-occurring, but functionally contrasting, sediment-dwelling inter-tidal invertebrates assembled alone, and in combination, in representative model aquaria. These data (≤2,000 raw image slices aquarium−1, isotropic voxel resolution, 81 μm) provide reference models that can be used for the development of novel structural analysis routines that will be of value within the fields of ecology, pedology, geomorphology, palaeobiology, ichnology and mechanical engineering. We also envisage opportunity for those investigating transport networks, vascular systems, plant rooting systems, neuron connectivity patterns, or those developing image analysis or statistics related to pattern or shape recognition. The dataset will allow investigators to develop or test novel methodology and ideas without the need to generate a complete three-dimensional computation of exemplar architecture

An evolutionary stage model of outsourcing and competence destruction : a Triad comparison of the consumer electronics industry

Outsourcing has gained much prominence in managerial practice and academic discussions in the last two decades or so. Yet, we still do not understand the full implications of outsourcing strategy for corporate performance. Traditionally outsourcing across borders is explained as a cost-cutting exercise, but more recently the core competency argument states that outsourcing also leads to an increased focus, thereby improving effectiveness. However, no general explanation has so far been provided for how outsourcing could lead to deterioration in a firm‟s competence base. We longitudinally analyze three cases of major consumer electronics manufacturers, Emerson Radio from the U.S., Japan‟s Sony and Philips from the Netherlands to understand the dynamic process related to their sourcing strategies. We develop an evolutionary stage model that relates outsourcing to competence development inside the firm and shows that a vicious cycle may emerge. Thus it is appropriate to look not only at how outsourcing is influenced by an organization‟s current set of competences, but also how it alters that set over time. The four stages of the model are offshore sourcing, phasing out, increasing dependence on foreign suppliers, and finally industry exit or outsourcing reduction. The evolutionary stage model helps managers understand for which activities and under which conditions outsourcing across borders is not a viable option. Results suggest that each of these firms had faced a loss of manufacturing competitiveness in its home country, to which it responded by offshoring and then outsourcing production. When a loss of competences occurred, some outsourcing decisions were reversed

Risk, Unexpected Uncertainty, and Estimation Uncertainty: Bayesian Learning in Unstable Settings

Recently, evidence has emerged that humans approach learning using Bayesian updating rather than (model-free) reinforcement algorithms in a six-arm restless bandit problem. Here, we investigate what this implies for human appreciation of uncertainty. In our task, a Bayesian learner distinguishes three equally salient levels of uncertainty. First, the Bayesian perceives irreducible uncertainty or risk: even knowing the payoff probabilities of a given arm, the outcome remains uncertain. Second, there is (parameter) estimation uncertainty or ambiguity: payoff probabilities are unknown and need to be estimated. Third, the outcome probabilities of the arms change: the sudden jumps are referred to as unexpected uncertainty. We document how the three levels of uncertainty evolved during the course of our experiment and how it affected the learning rate. We then zoom in on estimation uncertainty, which has been suggested to be a driving force in exploration, in spite of evidence of widespread aversion to ambiguity. Our data corroborate the latter. We discuss neural evidence that foreshadowed the ability of humans to distinguish between the three levels of uncertainty. Finally, we investigate the boundaries of human capacity to implement Bayesian learning. We repeat the experiment with different instructions, reflecting varying levels of structural uncertainty. Under this fourth notion of uncertainty, choices were no better explained by Bayesian updating than by (model-free) reinforcement learning. Exit questionnaires revealed that participants remained unaware of the presence of unexpected uncertainty and failed to acquire the right model with which to implement Bayesian updating

The Milky Way Tomography With SDSS. III. Stellar Kinematics

We study Milky Way kinematics using a sample of 18.8 million main-sequence stars with r 20 degrees). We find that in the region defined by 1 kpc < Z < 5 kpc and 3 kpc < R < 13 kpc, the rotational velocity for disk stars smoothly decreases, and all three components of the velocity dispersion increase, with distance from the Galactic plane. In contrast, the velocity ellipsoid for halo stars is aligned with a spherical coordinate system and appears to be spatially invariant within the probed volume. The velocity distribution of nearby (Z < 1 kpc) K/M stars is complex, and cannot be described by a standard Schwarzschild ellipsoid. For stars in a distance-limited subsample of stars (< 100 pc), we detect a multi-modal velocity distribution consistent with that seen by HIPPARCOS. This strong non-Gaussianity significantly affects the measurements of the velocity-ellipsoid tilt and vertex deviation when using the Schwarzschild approximation. We develop and test a simple descriptive model for the overall kinematic behavior that captures these features over most of the probed volume, and can be used to search for substructure in kinematic and metallicity space. We use this model to predict further improvements in kinematic mapping of the Galaxy expected from Gaia and the Large Synoptic Survey Telescope.NSF AST-615991, AST-0707901, AST-0551161, AST-02-38683, AST-06-07634, AST-0807444, PHY05-51164NASA NAG5-13057, NAG5-13147, NNXO-8AH83GPhysics Frontier Center/Joint Institute for Nuclear Astrophysics (JINA) PHY 08-22648U.S. National Science FoundationMarie Curie Research Training Network ELSA (European Leadership in Space Astrometry) MRTN-CT-2006-033481Fermi Research Alliance, LLC, United States Department of Energy DE-AC02-07CH11359Alfred P. Sloan FoundationParticipating InstitutionsJapanese MonbukagakushoMax Planck SocietyHigher Education Funding Council for EnglandMcDonald Observator

The Milky Way Tomography with SDSS: III. Stellar Kinematics

We study Milky Way kinematics using a sample of 18.8 million main-sequence stars with r<20 and proper-motion measurements derived from SDSS and POSS astrometry, including ~170,000 stars with radial-velocity measurements from the SDSS spectroscopic survey. Distances to stars are determined using a photometric parallax relation, covering a distance range from ~100 pc to 10 kpc over a quarter of the sky at high Galactic latitudes (|b|>20 degrees). We find that in the region defined by 1 kpc <Z< 5 kpc and 3 kpc <R< 13 kpc, the rotational velocity for disk stars smoothly decreases, and all three components of the velocity dispersion increase, with distance from the Galactic plane. In contrast, the velocity ellipsoid for halo stars is aligned with a spherical coordinate system and appears to be spatially invariant within the probed volume. The velocity distribution of nearby ($Z<1$ kpc) K/M stars is complex, and cannot be described by a standard Schwarzschild ellipsoid. For stars in a distance-limited subsample of stars (<100 pc), we detect a multimodal velocity distribution consistent with that seen by HIPPARCOS. This strong non-Gaussianity significantly affects the measurements of the velocity ellipsoid tilt and vertex deviation when using the Schwarzschild approximation. We develop and test a simple descriptive model for the overall kinematic behavior that captures these features over most of the probed volume, and can be used to search for substructure in kinematic and metallicity space. We use this model to predict further improvements in kinematic mapping of the Galaxy expected from Gaia and LSST.Comment: 90 pages, 26 figures, submitted to Ap

The Discovery Potential of a Super B Factory

The Proceedings of the 2003 SLAC Workshops on flavor physics with a high luminosity asymmetric e+e- collider. The sensitivity of flavor physics to physics beyond the Standard Model is addressed in detail, in the context of the improvement of experimental measurements and theoretical calculations.Comment: 476 pages. Printed copies may be obtained by request to [email protected] . arXiv admin note: v2 appears to be identical to v