Einstein@Home

Einstein@Home is a volunteer distributed computing project that searches for signals from rotating neutron stars in data from the LIGO gravitational-wave detectors, from large radio telescopes, and from the Fermi Gamma-ray Space Telescope. Neutron stars are detected by their pulsed radio and gamma-ray emission as radio and/or gamma-ray pulsars. They also might be observable as continuous gravitational wave sources if they are rapidly rotating and non-axisymmetrically deformed. Einstein@Home examines radio telescope data from the Arecibo Observatory and has in the past analyzed data from Parkes Observatory, searching for radio pulsars. The project also analyses data from the Fermi Gamma-ray Space Telescope to discover gamma-ray pulsars. The project runs on the Berkeley Open Infrastructure for Network Computing (BOINC) software platform and uses free software released under the GNU General Public License, version 2.[1] Einstein@Home is hosted by the University of Wisconsin–Milwaukee and the Max Planck Institute for Gravitational Physics (Albert Einstein Institute, Hannover, Germany). The project is supported by the American Physical Society (APS), the US National Science Foundation (NSF), and the Max Planck Society (MPG). The Einstein@Home project director is Bruce Allen.

Einstein@Home
Developer(s)LIGO Scientific Collaboration (LSC), Max Planck Society (MPG)
Initial releaseFebruary 19, 2005 (2005-02-19)
Development statusActive
Operating systemCross-platform
PlatformBOINC
LicenseGNU General Public License, version 2.[1]
Average performance2.514 PFLOPS[2] (October 2017)
Active users36,647 [3]
Total users440,542 [3]
Active hosts50,310 [3]
Total hosts1,579,553 [3]
Websiteeinsteinathome.org

On August 12, 2010, the first discovery by Einstein@Home of a previously undetected radio pulsar J2007+2722, found in data from the Arecibo Observatory, was published in Science.[4][5] The project had discovered 55 radio pulsars as of November 2016.[6][7]

As of November 2016, Einstein@Home has discovered 18 previously unknown gamma-ray pulsars[8] in data from the Large Area Telescope on board the Fermi Gamma-ray Space Telescope. The Einstein@Home search makes use of novel and more efficient data-analysis methods and discovered pulsars missed in other analyses of the same data.[9]

Introduction

The project was officially launched on 19 February 2005 as part of the American Physical Society's contribution to the World Year of Physics 2005 event.[10] It uses the power of volunteer-driven distributed computing in solving the computationally intensive problem of analyzing a large volume of data. Such an approach was pioneered by the SETI@home project, which is designed to look for signs of extraterrestrial life by analyzing radio wave data. Einstein@Home runs through the same software platform as SETI@home, the Berkeley Open Infrastructure for Network Computing (BOINC).

As of November 2016, more than 440,000 volunteers in 226 countries had participated in the project, making it the fourth-most-popular BOINC application.[11] Users regularly contribute about 1.7 petaFLOPS of computational power,[3] which would rank Einstein@Home among the top 60 on the TOP500 list of supercomputers.[12]

Scientific objectives

The Einstein@Home project has been created to perform all-sky searches for previously unknown continuous gravitational-wave (CW) sources using data from the Laser Interferometer Gravitational-Wave Observatory (LIGO) detector instruments in Washington and Louisiana, USA.[13] The primary class of target CW sources is rapidly rotating neutron stars (including pulsars) which are expected to emit gravitational waves due to a deviation from axisymmetry. Besides validating Einstein's theory of General Relativity, direct detection of gravitational waves would also constitute an important new astronomical tool. As most neutron stars are electromagnetically invisible, gravitational-wave observations might allow completely new populations of neutron stars to be revealed. A CW detection could potentially be extremely helpful in neutron-star astrophysics and would eventually provide unique insights into the nature of matter at high densities.[14]

Since March 2009, part of the Einstein@Home computing power has also been used to analyze data taken by the PALFA Consortium at the Arecibo Observatory in Puerto Rico.[15] This search effort is designed to find radio pulsars in tight binary systems.[16] A similar search has also been performed on two archival data sets from the Parkes Multi-beam Pulsar Survey.[17] The Einstein@Home radio pulsar search employs mathematical methods developed for the search for gravitational waves.[18]

Since July 2011, Einstein@Home is also analyzing data from the Large Area Telescope (LAT), the primary instrument on Fermi Gamma-ray Space Telescope to search for pulsed gamma-ray emission from rotating neutron stars (gamma-ray pulsars).[19] Some neutron stars are only detectable by their pulsed gamma-ray emission, which originates in a different area of the neutron star magnetosphere than the radio emission. Identifying the neutron star's rotation rate is computationally difficult, because for a typical gamma-ray pulsar only thousands of gamma-ray photons will be detected by the LAT over the course of millions of rotations.[20] The Einstein@Home analysis of the LAT data makes use of methods initially developed for the detection of continuous gravitational waves.

Gravitational-wave data analysis and results

Einstein@Home has carried out many analysis runs using data from the LIGO instruments. Since its first search run in 2005, the quality of the LIGO data has consistently improved from enhanced detector instrument performance. Einstein@Home search algorithms have kept pace with the LIGO's evolution in technology, achieving an increasing search sensitivity.

Einstein@Home's first analysis[21] used data from the "third science run" (S3) of LIGO. Processing of the S3 data set was conducted between 22 February 2005 and 2 August 2005. This analysis employed 60 segments from the LIGO Hanford 4-km detector, totaling ten hours of data each. Each 10-hour segment was analyzed for CW signals by the volunteers' computers using a matched-filtering technique. When all matched-filtering results were returned, the results from different segments were then combined in a "post-processing step" on Einstein@Home servers via a coincidence scheme to further enhance search sensitivity. Results were published on the Einstein@Home webpages.[22]

Work on the S4 data set (LIGO's fourth science run) was started via interlacing with the S3 calculations and finished in July 2006. This analysis used 10 segments of 30 hours each from the LIGO Hanford 4-km detector and 7 segments of 30 hours each from the LIGO Livingston 4-km detector. Besides the S4 data being more sensitive, a more sensitive coincidence combination scheme was also applied in the post-processing. The results of this search have led to the first scientific publication of Einstein@Home in Physical Review D.[23]

Einstein@home gained considerable attention in the international distributed computing community when an optimized application for the S4 data set analysis was developed and released in March 2006 by project volunteer Akos Fekete, a Hungarian programmer.[24] Fekete improved the official S4 application and introduced SSE, 3DNow! and SSE3 optimizations into the code improving performance by up to 800%.[25] Fekete was recognized for his efforts and was afterward officially involved with the Einstein@home team in the development of the new S5 application.[26] As of late July 2006, this new official application had become widely distributed among Einstein@home users. The app created a large surge in the project's total performance and productivity, as measured by floating point speed (or FLOPS), which over time has increased by approximately 50% compared to non-optimized S4 applications.[27]

The first Einstein@Home analysis of the early LIGO S5 data set, where the instruments initially reached their design sensitivity, began on 15 June 2006. This search used 22 segments of 30 hours each from the LIGO Hanford 4-km detector and six segments of 30 hours from the LIGO Livingston 4-km detector. This analysis run (code name "S5R1"), employing the search methodology as Einstein@Home, was very similar to the previous S4 analysis. However, the search results were more sensitive due to the use of more data of better quality compared to S4. Over large parts of the search parameter space, these results, which also appeared in Physical Review D, are the most exhaustive published to date.[28]

The second Einstein@Home search of LIGO S5 data (code name "S5R3") constituted a further major improvement regarding search sensitivity.[29] As opposed to previous searches, the ensuing results were already combined on the volunteers' computers via a Hough transform technique. This method matched-filtered results from 84 data segments of 25 hours each, parameters from which came from both 4-km LIGO Hanford and Livingston instruments. The results of this search are currently undergoing further examination.

On May 7, 2010, a new Einstein@Home search (code name "S5GC1"), which uses a significantly improved search method, launched. This program analyzed 205 data segments of 25 hours each, using data from both 4-km LIGO Hanford and Livingston instruments. It employed a technique which exploited global parameter-space correlations to efficiently combine the matched-filtering results from the different segments.[14][30]

In March 2016, Einstein@home began a search of the advanced-generation LIGO O1 data. The search focuses on signals with frequencies between 20 Hz and 100 Hz. The search includes two components, one for standard ever-lasting continuous gravitational waves and another for continuous signals lasting only some days.[31]

Radio data analysis and results

On March 24, 2009, it was announced that the Einstein@Home project was beginning to analyze data received by the PALFA Consortium at the Arecibo Observatory in Puerto Rico.[15]

On November 26, 2009, a CUDA-optimized application for the Arecibo Binary Pulsar Search was first detailed on official Einstein@home webpages. This application uses both a regular CPU and an NVIDIA GPU to perform analyses faster (in some cases up to 50% faster).[32]

In its analysis of radio data from the Arecibo Observatory, Einstein@Home has re-detected 134 different known radio pulsars that include 8 millisecond pulsars.[33]

On August 12, 2010, the Einstein@Home project announced the discovery of a new disrupted binary pulsar, PSR J2007+2722;[5] it may be the fastest-spinning such pulsar discovered to date.[4] The computers of Einstein@Home volunteers Chris and Helen Colvin and Daniel Gebhardt observed PSR 2007+2722 with the highest statistical significance.

On March 1, 2011, the Einstein@Home project announced their second discovery: a binary pulsar system PSR J1952+2630.[34] The computers of Einstein@Home volunteers from Russia and the UK observed PSR J1952+2630 with the highest statistical significance.

By May 15, 2012, Einstein@Home volunteers had discovered three new radio pulsars (J1901+0510, J1858+0319, and J1857+0259) in Arecibo PALFA data,[35] and a new application for ATI/AMD graphic cards had been released. Using OpenCL, the new application was ten times faster than running on a typical CPU. The application is currently available for Windows and Linux computers with Radeon HD 5000 or better graphics cards.[36]

As of February 2015, the Einstein@Home project had discovered a total of 51 pulsars: 24 using Parkes Multibeam Survey data and 27 using Arecibo radio data (including two from the Arecibo Binary Radio Pulsar Search and 25 using data from the PALFA Mock spectrometer data from Arecibo Observatory).[33][37][38]

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gollark: Hard to avoid, but bad.

See also

References
  1. Einstein@Home application source code and license
  2. de Zutter W. "Einstein@home: Detailed stats". boincstats.com. Retrieved 2017-10-02.
  3. "Einstein@home: Credit overview". Retrieved 2016-11-14.
  4. Knispel B, Allen B, Cordes JM, et al. (September 2010). "Pulsar discovery by global volunteer computing". Science. 329 (5997): 1305. arXiv:1008.2172. Bibcode:2010Sci...329.1305K. doi:10.1126/science.1195253. PMID 20705813.
  5. "Home computers discover rare star". BBC News. August 13, 2010. Retrieved 2010-08-13.
  6. "Discoveries in Arecibo data". Einstein@Home. Retrieved 2016-11-14.
  7. "Discoveries in Parkes Observatory data". Einstein@Home. Retrieved 2016-11-14.
  8. "Discoveries in Fermi LAT data". Einstein@Home. Retrieved 2016-11-10.
  9. Clark, Colin J.; et al. (2016). "The Einstein@Home Gamma-ray Pulsar Survey I: Search Methods, Sensitivity and Discovery of New Young Gamma-ray Pulsars". The Astrophysical Journal. 834 (2): 106. arXiv:1611.01015. Bibcode:2017ApJ...834..106C. doi:10.3847/1538-4357/834/2/106.
  10. Boyle, Alan. "Software sifts through gravity's mysteries". NBC News. Retrieved 2006-06-03.
  11. BOINCstats project statistics, retrieved 2016-11-14
  12. "Top500 List - November 2016". Retrieved 2016-11-14.
  13. "Einstein@Home All Sky Search". American Physical Society. Archived from the original on 2006-05-04. Retrieved 2006-06-03.
  14. Holger J. Pletsch. "Deepest All-Sky Surveys for Continuous Gravitational Waves". 2Physics.com. Retrieved 2010-07-25.
  15. "New Einstein@Home Effort launched: Thousands of homecomputers to search Arecibo data for new radio pulsars". MPI for Gravitational Physics. MPI for Gravitational Physics. March 24, 2009. Retrieved 2016-11-16.
  16. "The Einstein@Home Arecibo Radio Pulsar search". Retrieved November 16, 2016.
  17. "Einstein@Home forum post about searches in Parkes Observatory data". Retrieved November 16, 2016.
  18. Allen, Bruce; et al. (2013). "The Einstein@Home search for radio pulsars and PSR J2007+2722 discovery". The Astrophysical Journal. 773 (2): 91. arXiv:1303.0028. Bibcode:2013ApJ...773...91A. doi:10.1088/0004-637X/773/2/91.
  19. "Launching Fermi-LAT gamma ray pulsar search". Retrieved November 16, 2016.
  20. Pletsch, Holger J.; et al. (2011). "Discovery of Nine Gamma-Ray Pulsars in Fermi-LAT Data Using a New Blind Search Method". The Astrophysical Journal. 744 (2): 105. arXiv:1111.0523. Bibcode:2012ApJ...744..105P. doi:10.1088/0004-637X/744/2/105.
  21. "First report on the S3 analysis". Retrieved September 11, 2005.
  22. "Final report on the S3 analysis". Retrieved March 28, 2007.
  23. Abbott, B.; Abbott, R.; Adhikari, R.; Ajith, P.; Allen, B.; Allen, G.; Amin, R.; Anderson, D. P.; Anderson, S. B.; Anderson, W. G.; Arain, M. A.; Araya, M.; Armandula, H.; Armor, P.; Aso, Y.; Aston, S.; Aufmuth, P.; Aulbert, C.; Babak, S.; Ballmer, S.; Bantilan, H.; Barish, B. C.; Barker, C.; Barker, D.; Barr, B.; Barriga, P.; Barton, M. A.; Bastarrika, M.; Bayer, K.; et al. (2009). "Einstein@Home search for periodic gravitational waves in LIGO S4 data". Physical Review D. 79 (2): 022001. arXiv:0804.1747. Bibcode:2009PhRvD..79b2001A. doi:10.1103/PhysRevD.79.022001.
  24. "Profile: Akos Fekete". Retrieved 2016-11-16.
  25. New Optimised Executables Links, retrieved 2016-11-16
  26. "Programmer speeds search for gravitational waves". New Scientist. 2006-05-17. Retrieved 2009-07-01.
  27. "Einstein@home Server Status". Archived from the original on 2006-08-20. Retrieved 2006-08-22.
  28. Abbott, B. P.; Abbott, R.; Adhikari, R.; Ajith, P.; Allen, B.; Allen, G.; Amin, R. S.; Anderson, S. B.; Anderson, W. G.; Arain, M. A.; Araya, M.; Armandula, H.; Armor, P.; Aso, Y.; Aston, S.; Aufmuth, P.; Aulbert, C.; Babak, S.; Baker, P.; Ballmer, S.; Barker, C.; Barker, D.; Barr, B.; Barriga, P.; Barsotti, L.; Barton, M. A.; Bartos, I.; Bassiri, R.; Bastarrika, M.; et al. (2009). "Einstein@Home search for periodic gravitational waves in early S5 LIGO data". Physical Review D. 80 (4): 042003. arXiv:0905.1705. Bibcode:2009PhRvD..80d2003A. doi:10.1103/PhysRevD.80.042003.
  29. Reinhard Prix. "S5R3 search strategy".
  30. Holger J. Pletsch; Bruce Allen (2009). "Exploiting Large-Scale Correlations to Detect Continuous Gravitational Waves". Physical Review Letters. 103 (18): 181102. arXiv:0906.0023. Bibcode:2009PhRvL.103r1102P. doi:10.1103/PhysRevLett.103.181102. PMID 19905796.
  31. "First search on the advanced-generation LIGO detector data". einsteinathome.org. Retrieved 2016-11-16.
  32. "ABP1 CUDA applications". Retrieved 2016-11-16.
  33. "Einstein@Home Arecibo Binary Radio Pulsar Search (Re-)Detections". Retrieved 2011-08-12.
  34. "Einstein@Home Discovers New Binary Radio Pulsar". Einstein@Home project homepage. March 1, 2011.
  35. "Einstein@Home volunteers discover three new radio pulsars in Arecibo data - Einstein@Home". uwm.edu.
  36. https://einsteinathome.org/content/einsteinhome-gpu-application-atiamd-graphics-cards#117166
  37. "Einstein@Home - List of pulsars discovered from PMPS data".
  38. "Einstein@Home new discoveries and detections of known pulsars in the BRP4 search". Retrieved 2015-03-02.

Scientific Publications
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