|Developer(s)||LIGO Scientific Collaboration (LSC)|
|Initial release||February 19, 2005|
|Average performance||470 TFLOPS, 1.005 PFLOPS|
Einstein@Home is a volunteer distributed computing project that searches through data from the LIGO detectors for evidence of continuous gravitational-wave sources, which are expected from objects such as rapidly spinning non-axisymmetric neutron stars, and radio telescope data from the Arecibo Observatory, searching for radio pulsars. Running on the Berkeley Open Infrastructure for Network Computing (BOINC) software platform, Einstein@Home is hosted by the University of Wisconsin–Milwaukee and the Max Planck Institute for Gravitational Physics (Albert Einstein Institute, Hannover, Germany) and is directed by Bruce Allen. 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. The project has discovered 46 pulsars as of August 2012.
The project was officially launched on 19 February 2005 as part of American Physical Society's contribution to the World Year of Physics 2005. 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 August 2012, over 300,000 volunteers in 221 countries have participated in the project, making it the third-most-popular BOINC project. Users contribute about 1.005 petaFLOPS of computational power, which would rank Einstein@Home among the top 20 on the TOP500 list of supercomputers.
The Einstein@Home project has been created to perform all-sky searches for previously unknown continuous gravitational-wave (CW) sources using data from the LIGO detector instruments. The primary class of target CW sources are rapidly rotating neutron stars (including pulsars) which emit gravitational waves due to a deviation from axissymmetry. Besides validating Einstein's theory of General Relativity, direct detection of gravitational waves will also constitute an important new astronomical tool. As most neutron stars are electromagnetically invisible, gravitational-wave observations might allow to reveal completely new populations of neutron stars. Therefore, a CW detection could potentially be extremely helpful for neutron-star astrophysics and will eventually provide unique insights into the nature of matter at high densities.
Since March 2009, part of the Einstein@Home computing power is used to also analyze data taken by the PALFA Consortium at the Arecibo Observatory in Puerto Rico. This search effort is designed to find radio pulsars in tight binary systems.
Gravitational-wave data analysis and results
Einstein@Home has carried out a number of analysis runs using data from the LIGO instruments. Since its first search run in 2005, the quality of the LIGO data has constantly improved from enhanced detector instrument performance, as well as the Einstein@Home search algorithms which have been improved from run to run, achieving an increasing search sensitivity.
Einstein@Home's first analysis 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 the Einstein@Home servers via a coincidence scheme to further enhance the search sensitivity. The results were published on the Einstein@Home webpages.
Work on the S4 data set (LIGO's fourth science run) was started interlaced with the S3 calculations, and had finished in July 2006. This analysis used 10 segments of 30 hours from the LIGO Hanford 4-km detector and 7 segments of 30 hours from the LIGO Livingston 4-km detector. Besides the S4 data being more sensitive, also a more sensitive coincidence combination scheme was applied in the post-processing. The results of this search have led to the first scientific publication of Einstein@Home in Physical Review D.
Einstein@home has gained considerable attention of the world's 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. Fekete improved the official S4 application and introduced SSE, 3DNow! and SSE3 optimizations into the code improving performance by up to 800%. Fekete was recognized for his efforts and was afterward officially involved with the Einstein@home team in the development of the new S5 application. As of late July 2006 this new official application became widely distributed among the Einstein@home users, creating a large surge in the project's total performance and productivity, best measured by floating point speed (or FLOPS), which has increased by approximately 50% compared to non-optimized S4 application.
The first Einstein@Home analysis of early LIGO S5 data set, where the instruments reached their design sensitivity for the first time, began on 15 June 2006. This search used 22 segments of 30 hours from the LIGO Hanford 4-km detector and 6 segments of 30 hours from the LIGO Livingston 4-km detector. This analysis run (code name "S5R1") employed the search methodology on Einstein@Home was very similar to the previous S4 analysis. However, the search results were still more sensitive due to using more data which also had improved quality compared to S4. Over large parts of the searched parameter space these results (which also appeared in Physical Review D) are the most sensitive ones published to date.
The second Einstein@Home search of LIGO S5 data (code name "S5R3") has constituted once more a major improvement in terms of search sensitivity. In contrast to the previous searches, here the matched-filtering results from 84 data segments of 25 hours each, from both 4-km LIGO Hanford and Livingston instruments, were already combined on the volunteers' computers via a Hough transform technique. The results of this search are currently undergoing further examination.
On May 7, 2010, a new Einstein@Home search (code name "S5GC1") has been launched which uses a significantly improved search method. This search analyses 205 data segments of 25 hours each, from both 4-km LIGO Hanford and Livingston instruments, using a technique which exploits global parameter-space correlations to efficiently combine the matched-filtering results from the different segments.
Radio data analysis and results
On November 26, 2009, CUDA-optimized application for Arecibo Binary Pulsar Search was announced, on official Einstein@home webpages. This application uses both a regular CPU plus NVIDIA GPU to perform the analysis faster (in some cases up to 50% faster).
In its analysis of radio data from the Arecibo Observatory, Einstein@Home has re-detected 134 different known radio pulsars that include 8 milli-second pulsars.
On August 12, 2010, the Einstein@Home project announced their discovery of a new disrupted binary pulsar, PSR J2007+2722; it may be the fastest-spinning such pulsar discovered to date. 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: binary pulsar PSR J1952+2630. The computers of Einstein@Home volunteers from Russia and UK observed PSR J1952+2630 with the highest statistical significance.
On May 15, 2012, Einstein@Home volunteers have discovered three new radio pulsars (J1901+0510, J1858+0319, and J1857+0259) in Arecibo PALFA data and the new application for ATI/AMD graphic cards has been released. Using OpenCL, it is 10 times faster than running on CPU. The application is currently available for Windows and Linux computers with Radeon HD 5000 or better graphics cards
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- Server status
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- Einstein@Home Website
- Einstein@home project information in Chinese
- Einstein@home user statistics
- Berkeley Open Infrastructure for Network Computing (BOINC)
- Video of the Einstein@home screensaver.