An ALMA survey of the SCUBA-2 Cosmology Legacy Survey UKIDSS/UDS field: halo masses for submillimetre galaxies

We present an analysis of the spatial clustering of a large sample of high-resolution, interferometically identified, submillimetre galaxies (SMGs). We measure the projected cross-correlation function of ∼350 SMGs in the UKIDSS Ultra Deep-Survey Field across a redshift range of z = 1.5–3 utilizing a method that incorporates the uncertainties in the redshift measurements for both the SMGs and cross-correlated galaxies through sampling their full probability distribution functions. By measuring the absolute linear bias of the SMGs, we derive halo masses of log10(Mhalo[h−1M⊙]) ∼ 12.8 with no evidence of evolution in the halo masses with redshift, contrary to some previous work. From considering models of halo mass growth rates, we predict that the SMGs will reside in haloes of mass log10(Mhalo[h−1M⊙]) ∼ 13.2 at z = 0, consistent with the expectation that the majority of z = 1.5–3 SMGs will evolve into present-day spheroidal galaxies. Finally, comparing to models of stellar-to-halo mass ratios, we show that SMGs may correspond to systems that are maximally efficient at converting their gas reservoirs into stars. We compare them to a simple model for gas cooling in haloes that suggests that the unique properties of the SMG population, including their high levels of star formation and their redshift distribution, are a result of the SMGs being the most massive galaxies that are still able to accrete cool gas from their surrounding intragalactic medium

Can big data solve a big problem? Reporting the obesity data landscape in line with the Foresight obesity system map.

BACKGROUND: Obesity research at a population level is multifaceted and complex. This has been characterised in the UK by the Foresight obesity systems map, identifying over 100 variables, across seven domain areas which are thought to influence energy balance, and subsequent obesity. Availability of data to consider the whole obesity system is traditionally lacking. However, in an era of big data, new possibilities are emerging. Understanding what data are available can be the first challenge, followed by an inconsistency in data reporting to enable adequate use in the obesity context. In this study we map data sources against the Foresight obesity system map domains and nodes and develop a framework to report big data for obesity research. Opportunities and challenges associated with this new data approach to whole systems obesity research are discussed. METHODS: Expert opinion from the ESRC Strategic Network for Obesity was harnessed in order to develop a data source reporting framework for obesity research. The framework was then tested on a range of data sources. In order to assess availability of data sources relevant to obesity research, a data mapping exercise against the Foresight obesity systems map domains and nodes was carried out. RESULTS: A reporting framework was developed to recommend the reporting of key information in line with these headings: Background; Elements; Exemplars; Content; Ownership; Aggregation; Sharing; Temporality (BEE-COAST). The new BEE-COAST framework was successfully applied to eight exemplar data sources from the UK. 80% coverage of the Foresight obesity systems map is possible using a wide range of big data sources. The remaining 20% were primarily biological measurements often captured by more traditional laboratory based research. CONCLUSIONS: Big data offer great potential across many domains of obesity research and need to be leveraged in conjunction with traditional data for societal benefit and health promotion

Identification of Stochastically Perturbed Autonomous Systems from Temporal Sequences of Probability Density Functions

The paper introduces a method for reconstructing one-dimensional iterated maps that are driven by an external control input and subjected to an additive stochastic perturbation, from sequences of probability density functions that are generated by the stochastic dynamical systems and observed experimentally

An ALMA survey of the SCUBA-2 CLS UDS field: Physical properties of 707 Sub-millimetre Galaxies

We analyse the physical properties of a large, homogeneously selected sample of ALMA-located sub-millimetre galaxies (SMGs). This survey, AS2UDS, identified 707 SMGs across the ∼ 1 deg2 field, including ∼ 17 per cent which are undetected at K ≳ 25.7 mag. We interpret their UV-to-radio data using MAGPHYS and determine a median redshift of z = 2.61±0.08 (1-σ range of z = 1.8–3.4) with just ∼ 6 per cent at z > 4. Our survey provides a sample of massive dusty galaxies at z ≳ 1, with median dust and stellar masses of Md = (6.8±0.3) × 108 M⊙ (thus, gas masses of ∼ 1011 M⊙) and M* = (1.26±0.05) × 1011 M⊙. We find no evolution in dust temperature at a constant far-infrared luminosity across z ∼ 1.5–4. The gas mass function of our sample increases to z ∼ 2–3 and then declines at z > 3. The space density and masses of SMGs suggest that almost all galaxies with M* ≳ 3 × 1011 M⊙ have passed through an SMG-like phase. The redshift distribution is well fit by a model combining evolution of the gas fraction in halos with the growth of halo mass past a critical threshold of Mh ∼ 6 × 1012 M⊙, thus SMGs may represent the highly efficient collapse of gas-rich massive halos. We show that SMGs are broadly consistent with simple homologous systems in the far-infrared, consistent with a centrally illuminated starburst. Our study provides strong support for an evolutionary link between the active, gas-rich SMG population at z > 1 and the formation of massive, bulge-dominated galaxies across the history of the Universe