50,532 research outputs found

    The Contribution of Late-type/Irregulars to the Faint Galaxy Counts from HST Medium Deep Survey Images

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    We present a complete morphologically classified sample of 144 faint field galaxies from the HST Medium Deep Survey with 20.0 < I <22.0 mag. We compare the global properties of the ellipticals, early and late-type spirals, and find a non-negligible fraction (13/144) of compact blue [(V-I) < 1.0 mag] systems with r1/4r^{1/4}-profiles. We give the differential galaxy number counts for ellipticals and early-type spirals independently, and find that the data are consistent with no-evolution predictions based on conventional flat Schechter luminosity functions (LF's) and a standard cosmology. Conversely, late-type/Irregulars show a steeply rising differential number count with slope (δlogNδm)=0.64±0.1(\frac{\delta log N}{\delta m}) = 0.64\pm 0.1. No-evolution models based on the Loveday et al. (1992) and Marzke et al. (1994b) {\it local} luminosity functions under-predict the late-type/Irregular counts by 1.0 and 0.5 dex, respectively, at I = 21.75 mag. Examination of the Irregulars alone shows that ∼50\sim 50% appear inert and the remainder have multiple cores. If the inert galaxies represent a non-evolving late-type population, then a Loveday-like LF (α≃−1.0\alpha\simeq -1.0) is ruled out for these types, and a LF with a steep faint-end (α≃−1.5\alpha\simeq -1.5) is suggested. If multiple core structure indicates recent star-formation, then the observed excess of faint blue field galaxies is likely due to {\it evolutionary} processes acting on a {\it steep} field LF for late-type/Irregulars. The evolutionary mechanism is unclear, but 60% of the multiple-core Irregulars show close companions. To reconcile a Marzke-like LF with the faint redshift surveys, this evolution must be preferentially occurring in the brightest late-type galaxies with z > 0.5 at I = 21.75 mag.Comment: 29 pages, 1 catalog and 10 figures. The figures and catalog can be found at http://www.phys.unsw.edu.au/~spd/bib.htm

    A stellar census of the nearby, young 32 Orionis group

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    The 32 Orionis group was discovered almost a decade ago and despite the fact that it represents the first northern, young (age ~ 25 Myr) stellar aggregate within 100 pc of the Sun (d≃93d \simeq 93 pc), a comprehensive survey for members and detailed characterisation of the group has yet to be performed. We present the first large-scale spectroscopic survey for new (predominantly M-type) members of the group after combining kinematic and photometric data to select candidates with Galactic space motion and positions in colour-magnitude space consistent with membership. We identify 30 new members, increasing the number of known 32 Ori group members by a factor of three and bringing the total number of identified members to 46, spanning spectral types B5 to L1. We also identify the lithium depletion boundary (LDB) of the group, i.e. the luminosity at which lithium remains unburnt in a coeval population. We estimate the age of the 32 Ori group independently using both isochronal fitting and LDB analyses and find it is essentially coeval with the {\beta} Pictoris moving group, with an age of 24±424\pm4 Myr. Finally, we have also searched for circumstellar disc hosts utilising the AllWISE catalogue. Although we find no evidence for warm, dusty discs, we identify several stars with excess emission in the WISE W4-band at 22 {\mu}m. Based on the limited number of W4 detections we estimate a debris disc fraction of 32−8+1232^{+12}_{-8} per cent for the 32 Ori group.Comment: Accepted for publication in MNRAS; 24 pages, 17 figures and 10 table

    The effects of halo alignment and shape on the clustering of galaxies

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    We investigate the effects of halo shape and its alignment with larger scale structure on the galaxy correlation function. We base our analysis on the galaxy formation models of Guo et al., run on the Millennium Simulations. We quantify the importance of these effects by randomizing the angular positions of satellite galaxies within haloes, either coherently or individually, while keeping the distance to their respective central galaxies fixed. We find that the effect of disrupting the alignment with larger scale structure is a ~2 per cent decrease in the galaxy correlation function around r=1.8 Mpc/h. We find that sphericalizing the ellipsoidal distributions of galaxies within haloes decreases the correlation function by up to 20 per cent for r<1 Mpc/h and increases it slightly at somewhat larger radii. Similar results apply to power spectra and redshift-space correlation functions. Models based on the Halo Occupation Distribution, which place galaxies spherically within haloes according to a mean radial profile, will therefore significantly underestimate the clustering on sub-Mpc scales. In addition, we find that halo assembly bias, in particular the dependence of clustering on halo shape, propagates to the clustering of galaxies. We predict that this aspect of assembly bias should be observable through the use of extensive group catalogues.Comment: 8 pages, 6 figures. Accepted for publication in MNRAS. Minor changes relative to v1. Note: this is an revised and considerably extended resubmission of http://arxiv.org/abs/1110.4888; please refer to the current version rather than the old on

    Fairness in nurse rostering

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    Inference for double Pareto lognormal queues with applications

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    In this article we describe a method for carrying out Bayesian inference for the double Pareto lognormal (dPlN) distribution which has recently been proposed as a model for heavy-tailed phenomena. We apply our approach to inference for the dPlN/M/1 and M/dPlN/1 queueing systems. These systems cannot be analyzed using standard techniques due to the fact that the dPlN distribution does not posses a Laplace transform in closed form. This difficulty is overcome using some recent approximations for the Laplace transform for the Pareto/M/1 system. Our procedure is illustrated with applications in internet traffic analysis and risk theory.Heavy tails, Bayesian inference, Queueing theory
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