A Study of the Point-spread Function in SDSS Images
We use SDSS imaging data in the ugriz passbands to study the shape of the point-spread function (PSF) profile and the variation of its width with wavelength and time. We find that the PSF profile is well described by theoretical predictions based on von Kármán’s turbulence theory. The observed PSF r...
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Veröffentlicht in: | The Astronomical journal 2018-11, Vol.156 (5), p.222, Article 222 |
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Zusammenfassung: | We use SDSS imaging data in the
ugriz
passbands to study the
shape of the point-spread function (PSF) profile and the variation of its width
with wavelength and time. We find that the PSF profile is well described by
theoretical predictions based on von Kármán’s turbulence
theory. The observed PSF radial profile can be parameterized by only two
parameters, the profile’s full width at half maximum (FWHM) and a
normalization of the contribution of an empirically determined
“instrumental” PSF. The profile shape is very similar to the
“double Gaussian plus power-law wing” decomposition used by the SDSS
image-processing pipeline, but here it is successfully modeled with two free
model parameters, rather than six as in the SDSS pipeline. The FWHM variation
with wavelength follows the
λ
α
power law, where
α
≈ −0.3 and is correlated with
the FWHM itself. The observed behavior is much better described by von
Kármán’s turbulence theory, with the outer-scale parameter
in the range of 5–100 m, than by Kolmogorov’s turbulence theory. We
also measure the temporal and angular structure functions for FWHM and compare
them to simulations and results from the literature. The angular structure
function saturates at scales beyond 05−10. The power spectrum of
the temporal behavior is found to be broadly consistent with a damped
random-walk model with a characteristic timescale in the range of
∼5–30 minutes, though the data show a shallower high-frequency
behavior. The latter is well fit by a single power law with an index in the
range of −1.5 to −1.0. A hybrid model is likely needed to fully
capture both the low-frequency and high-frequency behavior of the temporal
variations of atmospheric seeing. |
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ISSN: | 0004-6256 1538-3881 1538-3881 |
DOI: | 10.3847/1538-3881/aae316 |