Einstein@Home discovers first millisecond pulsar visible only in gamma rays

Distributed volunteer computing project finds two rapidly rotating neutron stars in data from Fermi gamma-ray space telescope

February 28, 2018

The distributed computing project Einstein@Home aggregates the computing power donated by tens of thousands of volunteers from across the globe. In a survey of the gamma-ray sky, this computer network has now discovered two previously unknown rapidly rotating neutron stars in data from the Fermi gamma-ray space telescope. While all other such millisecond pulsars have also been observed with radio telescopes, one of the two discoveries is the first millisecond pulsar detectable solely through its pulsed gamma-ray emission. The findings raise hopes of detecting other new millisecond pulsars, e.g., from a predicted large population of such objects towards the center of our Galaxy. Scientists from the Max Planck Institute for Gravitational Physics in Hannover and the Max Planck Institute for Radio Astronomy in Bonn closely collaborated to enable the discoveries.

Additional information: Who made the discoveries?

The discoveries were enabled by tens of thousands of Einstein@Home volunteers who have donated their CPU time to the project. Without them this survey could not have been performed and these discoveries could not have been made. The team is especially grateful to those volunteers whose computers discovered the 2 pulsars reported in the Science Advances publication (where the volunteer’s name is unknown or private, we give the Einstein@Home username in quotation marks):

  • PSR J1035−6720: “WSyS”; Kurt Kovacs, of Seattle Washington, USA; and the ATLAS Cluster, AEI, Hannover, Germany.
  • PSR J1744−7619: Darrell Hoberer, of Gainesville, TX, USA; the ATLAS Cluster, AEI, Hannover, Germany; Igor Yakushin of Chicago, IL, USA and the LIGO Laboratory, USA; and Keith Pickstone of Oldham, UK.

Additional information: Einstein@Home quick facts

Einstein@Home is a distributed volunteer computing and connects computers and smartphones from the general public from all over the world. The project volunteers donate spare computing time on their devices. Until now more than 460,000 volunteers have participated, making Einstein@Home one of the largest projects of this kind. The current aggregate computing power contributed by about 53,000 computers from 33,000 active volunteers is about 6.8 petaFLOPS. This would secure Einstein@Home a position among the top 15 on the TOP500 list of supercomputers.

Since 2005, Einstein@Home has analyzed data from the gravitational wave detectors within the LIGO Scientific and the Virgo Collaborations for gravitational waves from unknown, rapidly rotating neutron stars. As of March 2009, Einstein@Home has also been involved in the search for signals from radio pulsars in observational data from the Arecibo Observatory in Puerto Rico and the Parkes Observatory in Australia. Since the first discovery of a radio pulsar by Einstein@Home in August 2010, the global computer network has discovered 55 new radio pulsars. A search for gamma-ray pulsars in data of the Fermi satellite was added in August 2011. It has discovered 23 new gamma-ray pulsars as of today.

Scientific supporters are the Max Planck Institute for Gravitational Physics (Albert Einstein Institute, Hanover) and the Center for Gravitation and Cosmology at the University of Wisconsin-Milwaukee with financial support from the National Science Foundation and the Max Planck Society.

Additional information: Einstein@Home gamma-ray pulsar survey

Enlisting the help of tens of thousands of volunteers from all around world donating idle compute cycles on their tens of thousands of computers at home, the team was able to conduct a large-scale survey with the distributed computing project Einstein@Home. In total this search required about 10,000 years of CPU core time. It would have taken more than one thousand years on a single household computer. On Einstein@Home it finished within one year – even though it only used a fraction of the project’s resources.

The scientists selected their targets from 1000 unidentified sources in the Fermi-LAT Third Source Catalog by their gamma-ray energy distribution as the most “pulsar-like” objects. For each of the 152 selected sources, they used novel, highly efficient methods to analyze the detected gamma-ray photons for hidden periodicities.

Additional information: “Blindly” detecting gamma-ray pulsars

Finding the periodic pulsations from gamma-ray pulsars is very difficult – even more so from the very fast millisecond pulsars. On average only 10 photons per day are detected from a typical pulsar by the LAT onboard the Fermi spacecraft. To detect periodicities, years of data must be analyzed, during which the pulsar might rotate tens of billions of times. For each photon one must determine exactly when during a single milliseconds rotation period it was emitted. This requires searching over long data sets with very fine resolution in order not to miss any signals. The computing power required for these “blind searches” – when little to no information about the pulsar is known beforehand – is enormous.

The new methods used in the Einstein@Home survey improve the search sensitivity without increasing the associated computational costs. They consist of an initial search stage more sensitive than in any other Einstein@Home gamma-ray search before. The initial search produces a number of interesting candidates which are then followed up on with an even more sensitive second stage, which zooms in and narrows down the uncertainty in the pulsars physical properties. The final step of the search is not performed on Einstein@Home, but on the Atlas computer cluster at the Max Planck Institute for Gravitational Physics in Hannover.

Previous similar blind searches have detected 37 gamma-ray pulsars in Fermi-LAT data. All blind search discoveries in the past 5 years have been made by Einstein@Home which has found a total of 23 gamma-ray pulsars in blind searches, more than a third of all such objects discovered through blind searches.

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