Supercomputers Help Uncover 'Noisy' Neutron Star Collisions

By Ken Chiacchia (Pittsburgh Supercomputing Center) and Kimberly Mann Bruch (SDSC)

Newswise — It seems strange to talk about “quiet” versus “noisy” collisions when discussing neutron stars, but many such impacts form a black hole that swallows all but the gravitational evidence. A series of simulations using multiple supercomputers, including Comet at the San Diego Supercomputer Center (SDSC) at UC San Diego, suggests that when the neutron stars’ masses are different enough, the result is far noisier.

The models predicted an electromagnetic ‘bang,’ which isn't present when the merging stars' masses are similar, which may make it easier for astronomers to more easily detect.

David Radice, a Pennsylvania State University astrophysics assistant professor working as member of the Computational Relativity International Collaboration or CoRe, which includes scientists in the U.S., Germany, Italy, and Brazil, wanted to better understand the phenomenon of unequal neutron stars colliding, and to predict signatures of such collisions that astronomers could look for.

Radice gained access to a number of supercomputers for his research, but the ones most useful to conduct these simulations were Comet at SDSC and Bridges at the Pittsburgh Supercomputing Center (PSC). Both systems are funded by the National Science Foundation and allocated to researchers via the agency’s Extreme Science and Engineering Discovery Environment (XSEDE) program. The CoRe group recently reported their results in the Monthly Notices of the Royal Astronomical Society.

“There is a lot of uncertainty surrounding the properties of neutron stars,” said Radice. “A single simulation of one model would not tell us much; we need to perform a large number of fairly computationally intensive simulations. We need a combination of high capacity and high capability that only machines like Bridges and Comet can offer. This work would not have been possible without access to such national supercomputing resources.”

Many neutron-star collisions are quiet, at least in terms of radiation that scientists can detect, according to Radice. A strong surge of gravitational waves emerges from the impact – now being sensed by gravity-wave detectors such as the Laser Interferometer Gravitational-Wave Observatory (LIGO), in Hanford, Washington, and Livingston, Louisiana; and Virgo, in Cascina, near Pisa. But precious little else appears. That's because the incredibly dense collapsed stars combine to form a black hole, which swallows any of the radiation that could have come out of the merger.

But that's not the only way it can play out. After reporting the first detection of a neutron-star merger in 2017, the LIGO team reported a second detection in 2019, which they named GW190425. The first of these mergers was what astronomers expected, with a total mass of about 2.7 times the mass of our Sun and each of the two neutron stars nearly equal in mass. However, GW190425 was heavier, with a combined mass of around 3.5 Solar masses. More importantly, the ratio of the masses of the two participants was more unequal, possibly as high as two to one. 

While that may not seem like such a huge difference, neutron stars can exist only in a narrow range of masses between about 1.2 and three times the mass of our Sun, according to Radice. Lighter stellar remnants don't collapse to form neutron stars, forming white dwarfs instead. Heavier objects collapse directly to form black holes.

When the difference between the merging stars gets as large as in GW190425, scientists suspected that the merger could be messier – and louder in electromagnetic radiation. Astronomers had detected no such signal from GW190425’s location. But coverage of that area of the sky by conventional telescopes that day wasn't good enough to rule it out.

How Supercomputers Helped

To run his simulations, Radice needed ample levels of computing speed, large memory, and flexibility in moving data between memory and computation as found in today’s larger supercomputers. That's partly because scientists know so little about these mergers for certain. Testing their theories required running about 20 simulations, each of which needed 500 compute cores for several weeks.

Radice employed a number of supercomputers for this work, including the XSEDE-allocated Stampede2 at the Texas Advanced Computing Center and Blue Waters at the National Center for Supercomputing Applications, which is an XSEDE Level-2 resource.

Their hope is that the simulated signature they found can be used by astronomers using a combination of gravity-wave and conventional telescopes to detect the paired signals that would herald the breakup of a smaller neutron star merging with a larger one.

This work was supported by EU H2020 ERC Starting Grant (BinGraSp-714626). Numerical relativity simulations were performed on the SuperMUC supercomputer at the Leibniz Supercomputing Centre (LRZ) in Munich, the Marconi supercomputer at CINECA (ISCRA-B project number HP10BMHFQQ). Access to Comet and Bridges was via XSEDE (allocation TG-PHY160025) and on Blue Waters (AWD-1811236). This research used resources of the National Energy Research Scientific Computing Center, a DOE Office of Science User Facility supported by the Office of Science of the U.S. Department of Energy (DE-AC02-05CH11231).

About SDSC

The San Diego Supercomputer Center (SDSC) is a leader and pioneer in high-performance and data-intensive computing, providing cyberinfrastructure resources, services, and expertise to the national research community, academia, and industry. Located on the UC San Diego campus, SDSC supports hundreds of multidisciplinary programs spanning a wide variety of domains, from astrophysics and earth sciences to disease research and drug discovery. In late 2020 SDSC will launch its newest National Science Foundation-funded supercomputer, Expanse. At over twice the performance of Comet, Expanse supports SDSC’s theme of ‘Computing without Boundaries’ with a data-centric architecture, public cloud integration, and state-of-the art GPUs for incorporating experimental facilities and edge computing.