Institution
University of Portsmouth
Education•Portsmouth, Portsmouth, United Kingdom•
About: University of Portsmouth is a education organization based out in Portsmouth, Portsmouth, United Kingdom. It is known for research contribution in the topics: Population & Galaxy. The organization has 5452 authors who have published 14256 publications receiving 424346 citations. The organization is also known as: Portsmouth and Gosport School of Science and Art & Portsmouth and Gosport School of Science and the Arts.
Topics: Population, Galaxy, Redshift, Context (language use), Computer science
Papers published on a yearly basis
Papers
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TL;DR: The data suggests that exposure of salmon smolts to atrazine in fresh water may compromise their physiological capabilities to survive in saline conditions.
140 citations
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12 Apr 1999TL;DR: This paper describes and discusses the syntax, functionality and performance of mpiJava, an object-oriented Java interface to MPI, and discusses some performance measurements made of communications bandwidth and latency to compare mpi Java on these systems.
Abstract: A basic prerequisite for parallel programming is a good communication API The recent interest in using Java for scientific and engineering application has led to several international efforts to produce a message passing interface to support parallel computation In this paper we describe and then discuss the syntax, functionality and performance of one such interface, mpiJava, an object-oriented Java interface to MPI We first discuss the design of the mpiJava API and the issues associated with its development We then more on to briefly outline the steps necessary to ‘port’ mpiJava onto a range of operating systems, including Windows NT, Linux and Solaris In the second part of the paper we present and then discuss some performance measurements made of communications bandwidth and latency to compare mpiJava on these systems Finally, we summarise our experiences and then briefly mention work that we plan to undertake
140 citations
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TL;DR: In this paper, a review of European Member States’ national legislation revealed considerable variation in ownership and access to coastal waters/fisheries, and in the legal distinction between sport fishing and other recreational uses of marine fisheries and their commercial (catching for sale and profit) counterparts.
139 citations
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Leibniz Institute for Astrophysics Potsdam1, Max Planck Society2, New Mexico State University3, Lawrence Berkeley National Laboratory4, Spanish National Research Council5, University of Portsmouth6, Vanderbilt University7, New York University8, University of Utah9, Yale University10, University of Arizona11, Pennsylvania State University12, Case Western Reserve University13, University of Florida14
TL;DR: In this paper, the authors used the MultiDark cosmological simulation, one of the largest N-body runs presently available, together with a simple halo abundance matching technique, to estimate galaxy correlation functions, power spectra, abundance of subhaloes and galaxy biases.
Abstract: We present results on the clustering of 282 068 galaxies in the Baryon Oscillation Spectroscopic Survey (BOSS) sample of massive galaxies with redshifts 0.4 < z < 0.7 which is part of the Sloan Digital Sky Survey III project. Our results cover a large range of scales from ∼500 to ∼90 h−1 Mpc. We compare these estimates with the expectations of the flat Λ cold dark matter (ΛCDM) standard cosmological model with parameters compatible with Wilkinson Microwave Anisotropy Probe 7 data. We use the MultiDark cosmological simulation, one of the largest N-body runs presently available, together with a simple halo abundance matching technique, to estimate galaxy correlation functions, power spectra, abundance of subhaloes and galaxy biases. We find that the ΛCDM model gives a reasonable description to the observed correlation functions at z ≈ 0.5, which is remarkably good agreement considering that the model, once matched to the observed abundance of BOSS galaxies, does not have any free parameters. However, we find a ≳10 per cent deviation in the correlation functions for scales ≲ 1 and ∼10–40 h−1 Mpc. A more realistic abundance matching model and better statistics from upcoming observations are needed to clarify the situation. We also estimate that about 12 per cent of the ‘galaxies’ in the abundance-matched sample are satellites inhabiting central haloes with mass M ≳ 1014 h−1 M⊙. Using the MultiDark simulation, we also study the real-space halo bias b of the matched catalogue finding that b = 2.00 ± 0.07 at large scales, consistent with the one obtained using the measured BOSS-projected correlation function. Furthermore, the linear large-scale bias, defined using the extrapolated linear matter power spectrum, depends on the number density n of the abundance-matched sample as b = −0.048 − (0.594 ± 0.02)log10(n/ h3 Mpc−3). Extrapolating these results to baryon acoustic oscillation scales, we measure a scale-dependent damping of the acoustic signal produced by non-linear evolution that leads to ∼2–4 per cent dips at ≳ 3σ level for wavenumbers k ≳ 0.1 h Mpc−1 in the linear large-scale bias.
139 citations
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École Polytechnique Fédérale de Lausanne1, University of California, Los Angeles2, Technische Universität München3, Academia Sinica Institute of Astronomy and Astrophysics4, Max Planck Society5, Stanford University6, University of California, Davis7, University of Tokyo8, Niels Bohr Institute9, University of Cambridge10, Fermilab11, University of Portsmouth12, Kapteyn Astronomical Institute13, Valparaiso University14, Leiden University15, European Southern Observatory16, INAF17
TL;DR: In this article, the authors investigate three potential sources: stellar kinematics, 2- line-of-sight effects, and 3- the deflector mass model and find no evidence of bias or errors larger than the current statistical uncertainties reported by TDCOSMO.
Abstract: Time-delay cosmography of lensed quasars has achieved 2.4% precision on the measurement of the Hubble constant, H0. As part of an ongoing effort to uncover and control systematic uncertainties, we investigate three potential sources: 1- stellar kinematics, 2- line-of-sight effects, and 3- the deflector mass model. To meet this goal in a quantitative way, we reproduced the H0LiCOW/SHARP/STRIDES (hereafter TDCOSMO) procedures on a set of real and simulated data, and we find the following. First, stellar kinematics cannot be a dominant source of error or bias since we find that a systematic change of 10% of measured velocity dispersion leads to only a 0.7% shift on H0 from the seven lenses analyzed by TDCOSMO. Second, we find no bias to arise from incorrect estimation of the line-of-sight effects. Third, we show that elliptical composite (stars + dark matter halo), power-law, and cored power-law mass profiles have the flexibility to yield a broad range in H0 values. However, the TDCOSMO procedures that model the data with both composite and power-law mass profiles are informative. If the models agree, as we observe in real systems owing to the "bulge-halo" conspiracy, H0 is recovered precisely and accurately by both models. If the two models disagree, as in the case of some pathological models illustrated here, the TDCOSMO procedure either discriminates between them through the goodness of fit, or it accounts for the discrepancy in the final error bars provided by the analysis. This conclusion is consistent with a reanalysis of six of the TDCOSMO (real) lenses: the composite model yields H0 = 74.0-1.8+1.7 km s-1 Mpc-1, while the power-law model yields 74.2-1.6+1.6 km s-1 Mpc-1. In conclusion, we find no evidence of bias or errors larger than the current statistical uncertainties reported by TDCOSMO.
139 citations
Authors
Showing all 5624 results
Name | H-index | Papers | Citations |
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Robert C. Nichol | 187 | 851 | 162994 |
Gavin Davies | 159 | 2036 | 149835 |
Daniel Thomas | 134 | 846 | 84224 |
Will J. Percival | 129 | 473 | 87752 |
Claudia Maraston | 103 | 362 | 59178 |
I. W. Harry | 98 | 312 | 65338 |
Timothy Clark | 95 | 1137 | 53665 |
Kevin Schawinski | 95 | 376 | 30207 |
Ashley J. Ross | 90 | 248 | 46395 |
Josep Call | 90 | 451 | 34196 |
David A. Wake | 89 | 214 | 46124 |
L. K. Nuttall | 89 | 253 | 54834 |
Stephen Neidle | 89 | 457 | 32417 |
Andrew Lundgren | 88 | 249 | 57347 |
Rita Tojeiro | 87 | 229 | 43140 |