4,329 research outputs found

    Rational asset pricing bubbles

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    This paper provides a fairly systematic study of general economic conditions under which rational asset pricing bubbles may arise in an intertemporal competitive equilibrium framework. Our main results are concerned with non-existence of asset pricing bubbles in those economies. These results imply that the conditions under which bubbles are possible inc1uding sorne well-known examples of monetary equilibria-are relatively fragile

    The Abundance of Low-luminosity Lyman alpha Emitters at High Redshift

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    We derive the luminosity function of high-redshift Lyman alpha emitting sources from a deep, blind, spectroscopic survey that utilized strong-lensing magnification by intermediate-redshift clusters of galaxies. We observed carefully selected regions near 9 clusters, consistent with magnification factors generally greater than 10 for the redshift range 4.5<z<6.7. Eleven emission-line candidates were located in the range 2.2<z<5.6 whose identification we justify as Lyman alpha, in most cases via further spectroscopic observations. The selection function we constructed for our survey takes into account our varying intrinsic Lyman alpha line sensitivity as a function of wavelength and sky position. By virtue of the strong magnification factor, we provide constraints on the Lyman alpha luminosity function to unprecedented limits of 10^40 erg/s, corresponding to a star-formation rate of 0.01 Msun/yr. Our cumulative z=5 Lyman alpha luminosity function is consistent with a power law form, n(>L) proportional to L^-1 over 10^41 to 10^42.5 erg/s. When combined with the results of other surveys, limited at higher luminosities, our results suggest evidence for the suppression of star formation in low-mass halos, as predicted in popular models of galaxy formation.Comment: 22 pages, 14 figures, submitted to Ap

    Correlation-Strength Driven Anderson Metal-Insulator Transition

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    The possibility of driving an Anderson metal-insulator transition in the presence of scale-free disorder by changing the correlation exponent is numerically investigated. We calculate the localization length for quasi-one-dimensional systems at fixed energy and fixed disorder strength using a standard transfer matrix method. From a finite-size scaling analysis we extract the critical correlation exponent and the critical exponent characterizing the phase transition.Comment: 3 pages; 2 figure

    Novel Bayesian Networks for Genomic Prediction of Developmental Traits in Biomass Sorghum.

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    The ability to connect genetic information between traits over time allow Bayesian networks to offer a powerful probabilistic framework to construct genomic prediction models. In this study, we phenotyped a diversity panel of 869 biomass sorghum (Sorghum bicolor (L.) Moench) lines, which had been genotyped with 100,435 SNP markers, for plant height (PH) with biweekly measurements from 30 to 120 days after planting (DAP) and for end-of-season dry biomass yield (DBY) in four environments. We evaluated five genomic prediction models: Bayesian network (BN), Pleiotropic Bayesian network (PBN), Dynamic Bayesian network (DBN), multi-trait GBLUP (MTr-GBLUP), and multi-time GBLUP (MTi-GBLUP) models. In fivefold cross-validation, prediction accuracies ranged from 0.46 (PBN) to 0.49 (MTr-GBLUP) for DBY and from 0.47 (DBN, DAP120) to 0.75 (MTi-GBLUP, DAP60) for PH. Forward-chaining cross-validation further improved prediction accuracies of the DBN, MTi-GBLUP and MTr-GBLUP models for PH (training slice: 30-45 DAP) by 36.4-52.4% relative to the BN and PBN models. Coincidence indices (target: biomass, secondary: PH) and a coincidence index based on lines (PH time series) showed that the ranking of lines by PH changed minimally after 45 DAP. These results suggest a two-level indirect selection method for PH at harvest (first-level target trait) and DBY (second-level target trait) could be conducted earlier in the season based on ranking of lines by PH at 45 DAP (secondary trait). With the advance of high-throughput phenotyping technologies, our proposed two-level indirect selection framework could be valuable for enhancing genetic gain per unit of time when selecting on developmental traits

    Metal-Poor Globular Clusters and the Formation of Their Host Galaxies

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    We have determined the total numbers and specific frequencies of blue, metal-poor globular clusters (GCs) in eight spiral and early-type galaxies. These data, along with five measurements from the literature, show a trend of increasing blue GC specific frequency with increasing mass of the host galaxy. The increase is not accounted for in a simple galaxy formation model in which ellipticals and their GC systems are formed by the merger of typical spiral galaxies. The data appear broadly consistent with hierarchical formation scenarios in which metal-poor GCs are formed over a finite period in the early Universe during the initial stages of galaxy assembly. In this picture, the observed trend is related to biasing, in the sense that the more massive galaxies of today began assembling earlier and therefore formed relatively more GCs during this early epoch of metal-poor GC formation. We discuss how comparisons of the observed specific frequency of metal-poor GCs with model calculations can constrain the formation redshift of these objects.Comment: 5 pages, 1 figure. Accepted for publication in ApJ Letter

    Predictable phenotypic, but not karyotypic, evolution of populations with contrasting initial history

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    This study was financed by Portuguese National Funds through FCT - ‘Fundação para a Ciência e Tecnologia’ within the projects PTDC/BIA-BEC/098213/2008, PTDC/BIA-BIC/2165/2012 and cE3c Unit FCT funding UID/BIA/00329/2013. I.F. had a PhD grant (SFRH/BD/60734/2009), P.S. has a Post Doc grant (SFRH/BPD/86186/2012) and S.G.S. has a Post Doc grant (SFRH/BPD/108413/2015) from FCT. M.S. is funded by grant CGL2013-42432-P from the Ministerio de Economía y Competitividad (Spain) and grant 2014 SGR 1346 from Generalitat de Catalunya. The datasets generated during and/or analysed during the current study are available in the figshare repository, at https://doi.org/10.6084/m9.figshare.4797550.The relative impact of selection, chance and history will determine the predictability of evolution. There is a lack of empirical research on this subject, particularly in sexual organisms. Here we use experimental evolution to test the predictability of evolution. We analyse the real-time evolution of Drosophila subobscura populations derived from contrasting European latitudes placed in a novel laboratory environment. Each natural population was sampled twice within a three-year interval. We study evolutionary responses at both phenotypic (life-history, morphological and physiological traits) and karyotypic levels for around 30 generations of laboratory culture. Our results show (1) repeatable historical effects between years in the initial state, at both phenotypic and karyotypic levels; (2) predictable phenotypic evolution with general convergence except for body size; and (3) unpredictable karyotypic evolution. We conclude that the predictability of evolution is contingent on the trait and level of organization, highlighting the importance of studying multiple biological levels with respect to evolutionary patterns.Publisher PDFPeer reviewe
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