HPC supports first black hole image


The Event Horizon Telescope (EHT) — a planet-scale array of eight ground-based radio telescopes forged through international collaboration — was designed to capture images of a black hole. In coordinated press conferences across the globe, EHT researchers revealed that they succeeded, unveiling the first direct visual evidence of the supermassive black hole in the centre of Messier 87 and its shadow. The shadow of a black hole seen here is the closest we can come to an image of the black hole itself, a completely dark object from which light cannot escape. The black hole’s boundary — the event horizon from which the EHT takes its name — is around 2.5 times smaller than the shadow it casts and measures just under 40 billion km across. While this may sound large, this ring is only about 40 microarcseconds across — equivalent to measuring the length of a credit card on the surface of the Moon. Although the telescopes making up the EHT are not physically connected, they are able to synchronize their recorded data with atomic clocks — hydrogen masers — which precisely time their observations. These observations were collected at a wavelength of 1.3 mm during a 2017 global campaign. Each telescope of the EHT produced enormous amounts of data – roughly 350 terabytes per day – which was stored on high-performance helium-filled hard drives. These data were flown to highly specialised supercomputers — known as correlators — at the Max Planck Institute for Radio Astronomy and MIT Haystack Observatory to be combined. They were then painstakingly converted into an image using novel computational tools developed by the collaboration.

On 10 April 2019 the first-ever image of a black hole was unveiled. This once-in-a-lifetime achievement would not have happened without the support of a global team of dedicated scientists, and of European supercomputers.

During a live-streamed press conference in Brussels, spectators were treated to a short video zooming in on galaxy M87 to end with a view of the supermassive black hole that exists at its centre and is 6.5 billion times more massive than the Sun. BlackHoleCam Scientists (https://blackholecam.org/) as part of the Event Horizon Telescope (EHT) Consortium (https://eventhorizontelescope.org) contributed to obtain the long-sought image, which actually shows the “shadow” of the black hole surrounded by a bright ring. The black hole itself remains hidden, as light bends in the intense gravity and cannot escape to show us what reality looks like beyond the event horizon (point of no return).

Prof. Dr. Luciano Rezzolla, Chair of Theoretical Astrophysics at the Goethe University, Frankfurt, Germany, and one of the principal investigators (PI) of BlackHoleCam (https://astro.uni-frankfurt.de/rezzolla/) is part of the global network of more than 200 scientists that needed one year and eight telescopes to achieve their feat.

In addition to the telescopes, the team used supercomputing resources to explore theoretically the various aspects of this discovery and understand the properties of the black hole. The German Tier-0 systems SuperMUC, hosted by LRZ in Garching, HazelHen, hosted by HLRS in Stuttgart, and the LOEWE cluster in CSC in Frankfurt, were directly employed in these calculations. SuperMUC and HazelHen are part of the PRACE Research Infrastructure that supports excellent science and engineering in Europe.

Two aspects of our work that would have been impossible without supercomputers: the direct simulations that first produce the plasma dynamics near a black hole and subsequently the appearance of the “shadow” from a black hole, and the data reduction needed to turn the huge amount of interferometric data from the radiotelescopes into an image.

When using world-class HPC systems, the need for efficient algorithms and skilled scientific programmers increases significantly. Katie Bouman, who is an assistant professor at the California Institute of Technology’s computing and mathematical sciences department, was one of the talented scientists on the EHT team. The image showing her excitement at the first viewing of the image has gone viral, and has given a young and female face to universe science.

“In international projects with diverse teams of highly skilled and motivated people, the best scientific results are achieved. This project, which combines the most advanced technology with the finest theoretical supercomputer simulations, is a good example of that,” Rezzolla added.

PRACE is proud to have Luciano Rezzolla as a Member of its Access Committee, the body that gives advice to the Board of Directors concerning the allocation of resources of the RI.

The image opens new windows onto the study of black holes, their event horizons, and gravity, and PRACE will continue to support excellent research in this field via its Call for Proposals for Project Access. To date PRACE has supported 17 such projects, providing them with more than 780 million core hours combined. The topic is also featured in the Scientific Case for Computing in Europe 2018 – 2026 (https://prace-ri.eu/about/scientific-case/), which the PRACE Scientific Steering Committee, the body that provides advice and guidance on all matters of a scientific and technical nature which may influence the scientific work carried out by the use of the resources provided by PRACE.

About BlackHoleCam

BlackHoleCam is a EU-funded project to finally image, measure and understand astrophysical black holes. Our research will test fundamental predictions of Einstein’s theory of General Relativity (GR). The BlackHoleCam team members are active partners of the global Event Horizon Telescope Consortium. BHCam is a project funded through a “Synergy Grant” awarded by the European Research Council (ERC) to a team of European astrophysicists, in partnership with the Event Horizon Telescope project and other international partners.

This article was first published on www.prace-ri.eu on Tuesday 16 April 2019.


The mission of PRACE (Partnership for Advanced Computing in Europe) is to enable high-impact scientific discovery and engineering research and development across all disciplines to enhance European competitiveness for the benefit of society. 

PRACE seeks to realise this mission by offering world class computing and data management resources and services through a peer review process. 

PRACE aisbl is funded by the PRACE Members The Implementation Phase of PRACE receives funding from the EU’s Horizon 2020 Research and Innovation Programme (2014-2020).

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