4 research outputs found
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Faraday Rotation Measure Gradients from a Helical Magnetic Field in 3C273
Using high frequency (12-22 GHz) VLBA observations we confirm the existence of a Faraday rotation measure gradient of {approx}500 rad m{sup -2} mas{sup -1} transverse to the jet axis in the quasar 3C273. The gradient is seen in two epochs spaced roughly six months apart. This stable transverse rotation measure gradient is expected if a helical magnetic field wraps around the jet. The overall order to the magnetic field in the inner projected 40 parsecs is consistent with a helical field. However, we find an unexpected increase in fractional polarization along the edges of the source, contrary to expectations. This high fractional polarization rules out internal Faraday rotation, but is not readily explained by a helical field. After correcting for the rotation measure, the intrinsic magnetic field direction in the jet of 3C273 changes from parallel to nearly perpendicular to the projected jet motion at two locations. If a helical magnetic field causes the observed rotation measure gradient then the synchrotron emitting electrons must be separate from the helical field region. The presence or absence of transverse rotation measure gradients in other sources is also discussed
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SDSS spectroscopic survey of stars
In addition to optical photometry of unprecedented quality, the Sloan Digital Sky Survey (SDSS) is also producing a massive spectroscopic database. They discuss determination of stellar parameters, such as effective temperature, gravity and metallicity from SDSS spectra, describe correlations between kinematics and metallicity, and study their variation as a function of the position in the Galaxy. They show that stellar parameter estimates by Beers et al. show a good correlation with the position of a star in the g-r vs. u-g color-color diagram, thereby demonstrating their robustness as well as a potential for photometric parameter estimation methods. Using Beers et al. parameters, they find that the metallicity distribution of the Milky Way stars at a few kpc from the galactic plane is bimodal with a local minimum at [Z/Z{sub {circle_dot}}] {approx} -1.3. The median metallicity for the low-metallicity [Z/Z{sub {circle_dot}}] < =1.3 subsample is nearly independent of Galactic cylindrical coordinates R and z, while it decreases with z for the high-metallicity [Z/Z{sub {circle_dot}}] > -1.3 sample. they also find that the low-metallicity sample has {approx} 2.5 times larger velocity dispersion and that it does not rotate (at the {approx} 10 km/s level), while the rotational velocity of the high-metallicity sample decreases smoothly with the height above the galactic plane
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Large Synoptic Survey Telescope: From Science Drivers to Reference Design
In the history of astronomy, major advances in our understanding of the Universe have come from dramatic improvements in our ability to accurately measure astronomical quantities. Aided by rapid progress in information technology, current sky surveys are changing the way we view and study the Universe. Next-generation surveys will maintain this revolutionary progress. We focus here on the most ambitious survey currently planned in the visible band, the Large Synoptic Survey Telescope (LSST). LSST will have unique survey capability in the faint time domain. The LSST design is driven by four main science themes: constraining dark energy and dark matter, taking an inventory of the Solar System, exploring the transient optical sky, and mapping the Milky Way. It will be a large, wide-field ground-based system designed to obtain multiple images covering the sky that is visible from Cerro Pachon in Northern Chile. The current baseline design, with an 8.4 m (6.5 m effective) primary mirror, a 9.6 deg{sup 2} field of view, and a 3,200 Megapixel camera, will allow about 10,000 square degrees of sky to be covered using pairs of 15-second exposures in two photometric bands every three nights on average. The system is designed to yield high image quality, as well as superb astrometric and photometric accuracy. The survey area will include 30,000 deg{sup 2} with {delta} < +34.5{sup o}, and will be imaged multiple times in six bands, ugrizy, covering the wavelength range 320-1050 nm. About 90% of the observing time will be devoted to a deep-wide-fast survey mode which will observe a 20,000 deg{sup 2} region about 1000 times in the six bands during the anticipated 10 years of operation. These data will result in databases including 10 billion galaxies and a similar number of stars, and will serve the majority of science programs. The remaining 10% of the observing time will be allocated to special programs such as Very Deep and Very Fast time domain surveys. We describe how the LSST science drivers led to these choices of system parameters
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Parametrization and Classification of 20 Billion LSST Objects: Lessons from SDSS
The Large Synoptic Survey Telescope (LSST) will be a large, wide-field ground-based system designed to obtain, starting in 2015, multiple images of the sky that is visible from Cerro Pachon in Northern Chile. About 90% of the observing time will be devoted to a deep-wide-fast survey mode which will observe a 20,000 deg{sup 2} region about 1000 times during the anticipated 10 years of operations (distributed over six bands, ugrizy). Each 30-second long visit will deliver 5{sigma} depth for point sources of r {approx} 24.5 on average. The co-added map will be about 3 magnitudes deeper, and will include 10 billion galaxies and a similar number of stars. We discuss various measurements that will be automatically performed for these 20 billion sources, and how they can be used for classification and determination of source physical and other properties. We provide a few classification examples based on SDSS data, such as color classification of stars, color-spatial proximity search for wide-angle binary stars, orbital-color classification of asteroid families, and the recognition of main Galaxy components based on the distribution of stars in the position-metallicity-kinematics space. Guided by these examples, we anticipate that two grand classification challenges for LSST will be (1) rapid and robust classification of sources detected in difference images, and (2) simultaneous treatment of diverse astrometric and photometric time series measurements for an unprecedentedly large number of objects