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Einstein@Home aggregates the computer power of hundreds of thousands of volunteers from 192 countries to mine large data sets. It has now found a 40.8 Hz isolated pulsar in radio survey data from the Arecibo Observatory taken in February 2007. Additional timing observations indicate that this pulsar is likely a disrupted recycled pulsar. PSR J2007+2722s pulse profile is remarkably wide with emission over almost the entire spin period; the pulsar likely has closely aligned magnetic and spin axes. The massive computing power provided by volunteers should enable many more such discoveries.
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We report the discovery of the 20.7 ms binary pulsar J1952+2630, made using the distributed computing project Einstein@Home in Pulsar ALFA survey observations with the Arecibo telescope. Follow-up observations with the Arecibo telescope confirm the binary nature of the system. We obtain a circular orbital solution with an orbital period of 9.4 hr, a projected orbital radius of 2.8 lt-s, and a mass function of f = 0.15 solar masses by analysis of spin period measurements. No evidence of orbital eccentricity is apparent; we set a 2-sigma upper limit e < 1.7e-3. The orbital parameters suggest a massive white dwarf companion with a minimum mass of 0.95 solar masses, assuming a pulsar mass of 1.4 solar masses. Most likely, this pulsar belongs to the rare class of intermediate mass binary pulsars. Future timing observations will aim to determine the parameters of this system further, measure relativistic effects, and elucidate the nature of the companion star.
We have conducted a new search for radio pulsars in compact binary systems in the Parkes multi-beam pulsar survey (PMPS) data, employing novel methods to remove the Doppler modulation from binary motion. This has yielded unparalleled sensitivity to pulsars in compact binaries. The required computation time of approximately 17000 CPU core years was provided by the distributed volunteer computing project Einstein@Home, which has a sustained computing power of about 1 PFlop/s. We discovered 24 new pulsars in our search, of which 18 were isolated pulsars, and six were members of binary systems. Despite the wide filterbank channels and relatively slow sampling time of the PMPS data, we found pulsars with very large ratios of dispersion measure (DM) to spin period. Among those is PSR J1748-3009, the millisecond pulsar with the highest known DM (approximately 420 pc/cc). We also discovered PSR J1840-0643, which is in a binary system with an orbital period of 937 days, the fourth largest known. The new pulsar J1750-2536 likely belongs to the rare class of intermediate-mass binary pulsars. Three of the isolated pulsars show long-term nulling or intermittency in their emission, further increasing this growing family. Our discoveries demonstrate the value of distributed volunteer computing for data-driven astronomy and the importance of applying new analysis methods to extensively searched data.
Volunteer computing is the use of consumer digital devices for high-throughput scientific computing. It can provide large computing capacity at low cost, but presents challenges due to device heterogeneity, unreliability, and churn. BOINC, a widely-used open-source middleware system for volunteer computing, addresses these challenges. We describe its features, architecture, and implementation.
The large penetration and continued growth in ownership of personal electronic devices represents a freely available and largely untapped source of computing power. To leverage those, we present Pando, a new volunteer computing tool based on a declarative concurrent programming model and implemented using JavaScript, WebRTC, and WebSockets. This tool enables a dynamically varying number of failure-prone personal devices contributed by volunteers to parallelize the application of a function on a stream of values, by using the devices browsers. We show that Pando can provide throughput improvements compared to a single personal device, on a variety of compute-bound applications including animation rendering and image processing. We also show the flexibility of our approach by deploying Pando on personal devices connected over a local network, on Grid5000, a French-wide computing grid in a virtual private network, and seven PlanetLab nodes distributed in a wide area network over Europe.
We have developed a method for estimating the properties of the progenitor dwarf galaxy from the tidal stream of stars that were ripped from it as it fell into the Milky Way. In particular, we show that the mass and radial profile of a progenitor dwarf galaxy evolved along the orbit of the Orphan Stream, including the stellar and dark matter components, can be reconstructed from the distribution of stars in the tidal stream it produced. We use MilkyWay@home, a PetaFLOPS-scale distributed supercomputer, to optimize our dwarf galaxy parameters until we arrive at best-fit parameters. The algorithm fits the dark matter mass, dark matter radius, stellar mass, radial profile of stars, and orbital time. The parameters are recovered even though the dark matter component extends well past the half light radius of the dwarf galaxy progenitor, proving that we are able to extract information about the dark matter halos of dwarf galaxies from the tidal debris. Our simulations assumed that the Milky Way potential, dwarf galaxy orbit, and the form of the density model for the dwarf galaxy were known exactly; more work is required to evaluate the sources of systematic error in fitting real data. This method can be used to estimate the dark matter content in dwarf galaxies without the assumption of virial equilibrium that is required to estimate the mass using line-of-sight velocities. This demonstration is a first step towards building an infrastructure that will fit the Milky Way potential using multiple tidal streams.
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