scholarly journals Dark Energy Survey year 3 results: point spread function modelling

2020 ◽  
Vol 501 (1) ◽  
pp. 1282-1299
Author(s):  
M Jarvis ◽  
G M Bernstein ◽  
A Amon ◽  
C Davis ◽  
P F Léget ◽  
...  
Keyword(s):  
Dark Energy ◽  
Point Spread Function ◽  
Systematic Errors ◽  
Field Of View ◽  
Dark Energy Survey ◽  
Point Spread ◽  
Spread Function ◽  
Function Modelling ◽  
Astronomical Images ◽  
Energy Survey

ABSTRACT We introduce a new software package for modelling the point spread function (PSF) of astronomical images, called piff (PSFs In the Full FOV), which we apply to the first three years (known as Y3) of the Dark Energy Survey (DES) data. We describe the relevant details about the algorithms used by piff to model the PSF, including how the PSF model varies across the field of view (FOV). Diagnostic results show that the systematic errors from the PSF modelling are very small over the range of scales that are important for the DES Y3 weak lensing analysis. In particular, the systematic errors from the PSF modelling are significantly smaller than the corresponding results from the DES year one (Y1) analysis. We also briefly describe some planned improvements to piff that we expect to further reduce the modelling errors in future analyses.

Improving position accuracy for telescopes with small aperture and wide field of view utilizing point spread function modelling

2020 ◽  
Vol 497 (3) ◽  
pp. 4000-4008
Author(s):  
Rongyu Sun ◽  
Shengxian Yu ◽  
Peng Jia ◽  
Changyin Zhao
Keyword(s):  
Point Spread Function ◽  
Large Scale ◽  
Field Of View ◽  
Wide Field ◽  
Position Measurement ◽  
Small Aperture ◽  
Position Accuracy ◽  
Point Spread ◽  
Wide Field Of View ◽  
Spread Function

ABSTRACT Telescopes with a small aperture and a wide field of view are widely used and play a significant role in large-scale state-of-the-art sky survey applications, such as transient detection and near-Earth object observations. However, owing to the specific defects caused by optical aberrations, the image quality and efficiency of source detection are affected. To achieve high-accuracy position measurements, an innovative technique is proposed. First, a large number of raw images are analysed using principal component analysis. Then, the effective point spread function is reconstructed, which reflects the state of the telescope and reveals the characteristics of the imaging process. Finally, based on the point spread function model, the centroids of star images are estimated iteratively. To test the efficiency and reliability of our algorithm, a large number of simulated images are produced, and a telescope with small aperture and wide field of view is utilized to acquire the raw images. The position measurement of sources is performed using our novel method and two other common methods on these data. Based on a comparison of the results, the improvement is investigated, and it is demonstrated that our proposed technique outperforms the others on position accuracy. We explore the limitations and potential gains that may be achieved by applying this technique to custom systems designed specifically for wide-field astronomical applications.

Brain PET imaging optimization with time of flight and point spread function modelling

2015 ◽  
Vol 31 (8) ◽  
pp. 948-955 ◽  
Author(s):  
Elena Prieto ◽  
Josep M. Martí-Climent ◽  
Verónica Morán ◽  
Lidia Sancho ◽  
Benigno Barbés ◽  
...  
Keyword(s):  
Pet Imaging ◽  
Point Spread Function ◽  
Time Of Flight ◽  
Brain Pet ◽  
Point Spread ◽  
Spread Function ◽  
Function Modelling

scholarly journals On point spread function modelling: towards optimal interpolation

2011 ◽  
Vol 419 (3) ◽  
pp. 2356-2368 ◽  
Author(s):  
Joel Bergé ◽  
Sedona Price ◽  
Adam Amara ◽  
Jason Rhodes
Keyword(s):  
Point Spread Function ◽  
Optimal Interpolation ◽  
Point Spread ◽  
Spread Function ◽  
Function Modelling

scholarly journals Variability and transient search in the SUDARE–VOICE field: a new method to extract the light curves

2020 ◽  
Vol 493 (3) ◽  
pp. 3825-3837
Author(s):  
Dezi Liu ◽  
Wenqiang Deng ◽  
Zuhui Fan ◽  
Liping Fu ◽  
Giovanni Covone ◽  
...  
Keyword(s):  
Uncertainty Analysis ◽  
Point Spread Function ◽  
Forthcoming Paper ◽  
Light Curves ◽  
New Method ◽  
Imaging Data ◽  
Point Spread ◽  
Spread Function ◽  
Function Modelling ◽  
The Difference

ABSTRACT The VLT Survey Telescope (VST) Optical Imaging of the CDFS and ES1 Fields Survey, in synergy with the SUDARE survey, is a deep optical ugri imaging of the CDFS and ES1 fields using the VST. The observations for the CDFS field comprise about 4.38 deg2 down to r ∼ 26 mag. The total on-sky time spans over 4 yr in this field, distributed over four adjacent sub-fields. In this paper, we use the multiepoch r-band imaging data to measure the variability of the detected objects and search for transients. We perform careful astrometric and photometric calibrations and point spread function modelling. A new method, referring to as differential running-average photometry, is proposed to measure the light curves of the detected objects. With the method, the difference of PSFs between different epochs can be reduced, and the background fluctuations are also suppressed. Detailed uncertainty analysis and detrending corrections on the light curves are performed. We visually inspect the light curves to select variable objects, and present some objects with interesting light curves. Further investigation of these objects in combination with multiband data will be presented in our forthcoming paper.

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