SIMBAD references

2009AJ....137...83C - Astron. J., 137, 83-93 (2009/January-0)

Precision astrometry with adaptive optics.

CAMERON P.B., BRITTON M.C. and KULKARNI S.R.

Abstract (from CDS):

We investigate the limits of ground-based astrometry with adaptive optics using the core of the Galactic globular cluster M5. Adaptive optics systems provide near diffraction-limit imaging with the world's largest telescopes. The substantial improvement in both resolution and signal-to-noise ratio enables high-precision astrometry from the ground. We describe the dominant systematic errors that typically limit ground-based differential astrometry, and enumerate observational considerations for mitigating their effects. After implementing these measures, we find that the dominant limitation on astrometric performance in this experiment is caused by tilt anisoplanatism. We then present an optimal estimation technique for measuring the position of one star relative to a grid of reference stars in the face of this correlated random noise source. Our methodology has the advantage of reducing the astrometric errors to and faster than the square root of the number of reference stars, effectively eliminating noise caused by atmospheric tilt to the point that astrometric performance is limited by centering accuracy. Using 50 reference stars, we demonstrate a single-epoch astrometric precision of ~1 mas in 1 s, decreasing to ≲100 µas in 2 minutes of integration time at the Hale 200 inch telescope. We also show that our astrometry is accurate to ≲100 µas for observations separated by 2 months. Finally, we discuss the limits and potential of differential astrometry with current and next-generation large-aperture telescopes. At this level of accuracy, numerous astrometric applications become accessible, including planet detection, astrometric microlensing signatures, and kinematics of distant Galactic stellar populations.

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Journal keyword(s): astrometry - globular clusters: individual: M5 - instrumentation: adaptive optics - methods: statistical

Simbad objects: 2

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