From U Manchester: “Shear brilliance: computing tackles the mystery of the dark universe”

U Manchester bloc

University of Manchester

24 November 2016
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Scientists from The University of Manchester working on a revolutionary telescope project have harnessed the power of distributed computing from the UK’s GridPP collaboration to tackle one of the Universe’s biggest mysteries – the nature of dark matter and dark energy.

Researchers at The University of Manchester have used resources provided by GridPP – who represent the UK’s contribution to the computing grid used to find the Higgs boson at CERN – to run image processing and machine learning algorithms on thousands of images of galaxies from the international Dark Energy Survey.

Dark Energy Icon

The Manchester team are part of the collaborative project to build the Large Synoptic Survey Telescope (LSST), a new kind of telescope currently under construction in Chile and designed to conduct a 10-year survey of the dynamic Universe. LSST will be able to map the entire visible sky.

LSST/Camera, built at SLAC
LSST/Camera, built at SLAC

LSST Interior
LSST telescope, currently under construction at Cerro Pachón Chile
LSST telescope, currently under construction at Cerro Pachón Chile

In preparation to the LSST starting its revolutionary scanning, a pilot research project has helped researchers detect and map out the cosmic shear seen across the night sky, one of the tell-tale signs of the dark matter and dark energy thought to make up some 95 per cent of what we see in the Universe. This in turn will help prepare for the analysis of the expected 200 petabytes of data the LSST will collect when it starts operating in 2023.

The pilot research team based at The Manchester of University was led by Dr Joe Zuntz, a cosmologist originally at Manchester’s Jodrell Bank Observatory and now a researcher at the Royal Observatory in Edinburgh.

“Our overall aim is to tackle the mystery of the dark universe – and this pilot project has been hugely significant. When the LSST is fully operating researchers will face a galactic data deluge – and our work will prepare us for the analytical challenge ahead.”
Sarah Bridle, Professor of Astrophysics

Dr George Beckett, the LSST-UK Science Centre Project Manager based at The University of Edinburgh, added: “The pilot has been a great success. Having completed the work, Joe and his colleagues are able to carry out shear analysis on vast image sets much faster than was previously the case. Thanks are due to the members of the GridPP community for their assistance and support throughout.”

The LSST will produce images of galaxies in a wide variety of frequency bands of the visible electromagnetic spectrum, with each image giving different information about the galaxy’s nature and history. In times gone by, the measurements needed to determine properties like cosmic shear might have been done by hand, or at least with human-supervised computer processing.

With the billions of galaxies expected to be observed by LSST, such approaches are unfeasible. Specialised image processing and machine learning software (Zuntz 2013) has therefore been developed for use with galaxy images from telescopes like LSST and its predecessors. This can be used to produce cosmic shear maps like those shown in the figure below. The challenge then becomes one of processing and managing the data for hundreds of thousands of galaxies and extracting scientific results required by LSST researchers and the wider astrophysics community.

As each galaxy is essentially independent of other galaxies in the catalogue, the image processing workflow itself is highly parallelisable. This makes it an ideal problem to tackle with the kind of High-Throughput Computing (HTP) resources and infrastructure offered by GridPP. In many ways, the data from CERN’s Large Hadron Collider particle collision events is like that produced by a digital camera (indeed, pixel-based detectors are used near the interaction points) – and GridPP regularly processes billions of such events as part of the Worldwide LHC Computing Grid (WLCG).

A pilot exercise, led by Dr Joe Zuntz while at The University of Manchester and supported by one of the longest serving and most experienced GridPP experts, Senior System Administrator Alessandra Forti, saw the porting of the image analysis workflow to GridPP’s distributed computing infrastructure. Data from the Dark Energy Survey (DES) was used for the pilot.

After transferring this data from the US to GridPP Storage Elements, and enabling the LSST Virtual Organisation on a number of GridPP Tier-2 sites, the IM3SHAPE analysis software package (Zuntz, 2013) was tested on local, grid-friendly client machines to ensure smooth running on the grid. Analysis jobs were then submitted and managed using the Ganga software suite, which is able to coordinate the thousands of individual analyses associated with each batch of galaxies. Initial runs were submitted using Ganga to local grid sites, but the pilot progressed to submission to multiple sites via the GridPP DIRAC (Distributed Infrastructure with Remote Agent Control) service. The flexibility of Ganga allows both types of submission, which made the transition from local to distributed running significantly easier.

By the end of pilot, Dr Zuntz was able to run the image processing workflow on multiple GridPP sites, regularly submitting thousands of analysis jobs on DES images.

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The University of Manchester (UoM) is a public research university in the city of Manchester, England, formed in 2004 by the merger of the University of Manchester Institute of Science and Technology (renamed in 1966, est. 1956 as Manchester College of Science and Technology) which had its ultimate origins in the Mechanics’ Institute established in the city in 1824 and the Victoria University of Manchester founded by charter in 1904 after the dissolution of the federal Victoria University (which also had members in Leeds and Liverpool), but originating in Owens College, founded in Manchester in 1851. The University of Manchester is regarded as a red brick university, and was a product of the civic university movement of the late 19th century. It formed a constituent part of the federal Victoria University between 1880, when it received its royal charter, and 1903–1904, when it was dissolved.

The University of Manchester is ranked 33rd in the world by QS World University Rankings 2015-16. In the 2015 Academic Ranking of World Universities, Manchester is ranked 41st in the world and 5th in the UK. In an employability ranking published by Emerging in 2015, where CEOs and chairmen were asked to select the top universities which they recruited from, Manchester placed 24th in the world and 5th nationally. The Global Employability University Ranking conducted by THE places Manchester at 27th world-wide and 10th in Europe, ahead of academic powerhouses such as Cornell, UPenn and LSE. It is ranked joint 56th in the world and 18th in Europe in the 2015-16 Times Higher Education World University Rankings. In the 2014 Research Excellence Framework, Manchester came fifth in terms of research power and seventeenth for grade point average quality when including specialist institutions. More students try to gain entry to the University of Manchester than to any other university in the country, with more than 55,000 applications for undergraduate courses in 2014 resulting in 6.5 applicants for every place available. According to the 2015 High Fliers Report, Manchester is the most targeted university by the largest number of leading graduate employers in the UK.

The university owns and operates major cultural assets such as the Manchester Museum, Whitworth Art Gallery, John Rylands Library and Jodrell Bank Observatory which includes the Grade I listed Lovell Telescope.