The WiggleZ Dark Energy Survey: constraining the evolution of Newton's constant using the growth rate of structure

We constrain the evolution of Newton's constant using the growth rate of large-scale structure measured by the WiggleZ Dark Energy Survey in the redshift range $0.1 < z < 0.9$. We use this data in two ways. Firstly we constrain the matter density of the Universe, \omms (assuming General Relativity), and use this to construct a diagnostic to detect the presence of an evolving Newton's constant. Secondly we directly measure the evolution of Newton's constant, \Geff, that appears in Modified Gravity theories, without assuming General Relativity to be true. The novelty of these approaches are that, contrary to other methods, they do not require knowledge of the expansion history of the Universe, $H(z)$, making them model independent tests. Our constraints for the second derivative of Newton's constant at the present day, assuming it is slowly evolving as suggested by Big Bang Nucleosynthesis constraints, using the WiggleZ data is \ddotGeff(t_0)=-1.19\pm 0.95\cdot 10^{-20}h^2 \textrm{yr}^{-2}, where $h$ is defined via $H_0=100 h km s^{-1}Mpc^{-1}$, while using both the WiggleZ and the Sloan Digital Sky Survey Luminous Red Galaxy (SDSS LRG) data is \ddotGeff(t_0)=-3.6\pm 6.8\cdot 10^{-21}h^2 \rm{yr}^{-2}, both being consistent with General Relativity. Finally, our constraint for the rms mass fluctuation $\sigma_8$ using the WiggleZ data is $\sigma_8=0.75 \pm 0.08$, while using both the WiggleZ and the SDSS LRG data $\sigma_8=0.77 \pm 0.07$, both in good agreement with the latest measurements from the Cosmic Microwave Background radiation.Comment: 15 pages, 5 figures, 4 tables, changes match the published versio

Driving policy change for decentralised wastewater management (DWWM)

Centralised approaches often run counter to people-centered management of wastewater. Large areas are not served by formal facilities and existing systems are often overloaded and poorly maintained, with major effects especially for poor people. A possibly more people-centered alternative may be to adopt a decentralised approach that locates planning and aspects implementation at community level and enhances local ownership of wastewater management. (DWWM). Although DWWM should not be considered to be a panacea, this paper presents a number of decentralised options and considers their implications. To implement decentralised options requires more than local initiative – a supportive crosscutting policy environment is crucial to move initiatives beyond a pilot scale. The paper considers the requirements of an effective enabling policy and what it means in practice It argues for holistic, inclusive and replicable policies that link to the wider context of poverty reduction within a cross-cutting framework of good governance in decentralised political administration

Optimizing baryon acoustic oscillation surveys – I. Testing the concordance ΛCDM cosmology

We optimize the design of future spectroscopic redshift surveys for constraining the dark energy via precision measurements of the baryon acoustic oscillations (BAO), with particular emphasis on the design of the Wide-Field Multi-Object Spectrograph (WFMOS). We develop a model that predicts the number density of possible target galaxies as a function of exposure time and redshift. We use this number counts model together with fitting formulae for the accuracy of the BAO measurements to determine the effectiveness of different surveys and instrument designs. We search through the available survey parameter space to find the optimal survey with respect to the dark energy equation-of-state parameters according to the Dark Energy Task Force Figure-of-Merit, including predictions of future measurements from the Planck satellite. We optimize the survey to test the LambdaCDM model, assuming that galaxies are pre-selected using photometric redshifts to have a constant number density with redshift, and using a non-linear cut-off for the matter power spectrum that evolves with redshift. We find that line-emission galaxies are strongly preferred as targets over continuum emission galaxies. The optimal survey covers a redshift range 0.8 < z < 1.4, over the widest possible area (6000 sq. degs from 1500 hours observing time). The most efficient number of fibres for the spectrograph is 2,000, and the survey performance continues to improve with the addition of extra fibres until a plateau is reached at 10,000 fibres. The optimal point in the survey parameter space is not highly peaked and is not significantly affected by including constraints from upcoming supernovae surveys and other BAO experiments.Comment: 15 pages, 9 figure

The conservation and evolutionary modularity of metabolism

A novel evolutionary analysis of metabolic networks across 26 taxa reveals a highly-conserved but flexible core of metabolic enzymes

Universal fitting formulae for baryon oscillation surveys

The next generation of galaxy surveys will attempt to measure the baryon oscillations in the clustering power spectrum with high accuracy. These oscillations encode a preferred scale which may be used as a standard ruler to constrain cosmological parameters and dark energy models. In this paper we present simple analytical fitting formulae for the accuracy with which the preferred scale may be determined in the tangential and radial directions by future spectroscopic and photometric galaxy redshift surveys. We express these accuracies as a function of survey parameters such as the central redshift, volume, galaxy number density and (where applicable) photometric redshift error. These fitting formulae should greatly increase the efficiency of optimizing future surveys, which requires analysis of a potentially vast number of survey configurations and cosmological models. The formulae are calibrated using a grid of Monte Carlo simulations, which are analysed by dividing out the overall shape of the power spectrum before fitting a simple decaying sinusoid to the oscillations. The fitting formulae reproduce the simulation results with a fractional scatter of 7 per cent (10 per cent) in the tangential (radial) directions over a wide range of input parameters. We also indicate how sparse-sampling strategies may enhance the effective survey area if the sampling scale is much smaller than the projected baryon oscillation scal

Optimizing baryon acoustic oscillation surveys - I. Testing the concordance ΛCDM cosmology

We optimize the design of future spectroscopic redshift surveys for constraining the dark energy via precision measurements of the baryon acoustic oscillations (BAOs), with particular emphasis on the design of the Wide-Field Multi-Object Spectrograph. We develop a model that predicts the number density of possible target galaxies as a function of exposure time and redshift. We use this number counts model together with fitting formulae for the accuracy of the BAO measurements to determine the effectiveness of different surveys and instrument designs. We search through the available survey parameter space to find the optimal survey with respect to the dark energy equation-of-state parameters according to the Dark Energy Task Force Figure-of-Merit, including predictions of future measurements from the Planck satellite. We optimize the survey to test the Lambda cold dark matter model, assuming that galaxies are pre-selected using photometric redshifts to have a constant number density with redshift, and using a non-linear cut-off for the matter power spectrum that evolves with redshift. We find that line-emission galaxies are strongly preferred as targets over continuum emission galaxies. The optimal survey covers a redshift range 0.8 < z < 1.4, over the widest possible area (6000 deg2 from 1500 h observing time). The most efficient number of fibres for the spectrograph is 2000, and the survey performance continues to improve with the addition of extra fibres until a plateau is reached at 10 000 fibres. The optimal point in the survey parameter space is not highly peaked and is not significantly affected by including constraints from upcoming supernovae surveys and other BAO experiment

Developing data-driven innovation in creative industries

This White Paper reports on the findings of the Data-Driven Innovation (DDI) Programme Sector Development consultation (2018-20), which investigated the data capability and further potential for innovation across the creative industries in the Edinburgh and South East City Region of Scotland. It presents an overview of the findings with early models of delivery through The University of Edinburgh to stimulate greater awareness and support for data innovation ambition, as well as key themes to focus on for future development. Consultation was conducted with the creative industries community in the Edinburgh and South East City Region, including Scottish creative industries trade bodies and networks, leading creative companies and individual creative practitioners, and with staff in The University of Edinburgh. We are grateful to the industry for their feedback, and to colleagues within the Data-Driven Innovation Programme, Edinburgh Futures Institute, Creative Informatics Cluster and their partners Edinburgh Napier University, Codebase and Creative Edinburgh for their input, advice and support. The consultation that informs this White Paper was initiated and supported by the Data-Driven Innovation Programme of The University of Edinburgh within the Edinburgh and South East Region City Deal

Comparison of T-cell Receptor Diversity of people with Myalgic Encephalomyelitis versus controls

Objective: Myalgic Encephalomyelitis (ME; sometimes referred to as Chronic Fatigue Syndrome) is a chronic disease without laboratory test, detailed aetiological understanding or effective therapy. Its symptoms are diverse, but it is distinguished from other fatiguing illnesses by the experience of post-exertional malaise, the worsening of symptoms even after minor physical or mental exertion. Its frequent onset after infection suggests autoimmune involvement or that it arises from abnormal T-cell activation. Results: To test this hypothesis, we sequenced the genomic loci of and T-cell receptors (TCR) from 40 human blood samples from each of four groups: severely affected people with ME; mildly or moderately affected people with ME; people diagnosed with Multiple Sclerosis, as disease controls; and, healthy controls. Seeking to automatically classify these individuals’ samples by their TCR repertoires, we applied P-SVM, a machine learning method. However, despite working well on a simulated data set, this approach did not allow statistically significant partitioning of samples into the four subgroups. Our findings do not support the hypothesis that blood samples from people with ME frequently contain altered T-cell receptor diversity