Point-spread function modeling for the James Webb Space Telescope

2006 ◽  
Author(s):  
Colin Cox ◽  
Philip Hodge
Keyword(s):  
Point Spread Function ◽  
Space Telescope ◽  
Point Spread ◽  
James Webb Space Telescope ◽  
Spread Function

scholarly journals Imaging of Magellanic Cloud Planetary Nebulae by the Hubble Space Telescope

1993 ◽  
Vol 155 ◽  
pp. 212-212
Author(s):  
M. A. Dopita ◽  
S. J. Meatheringham ◽  
P. R. Wood ◽  
H. C. Ford ◽  
R. C. Bohlin ◽  
...  
Keyword(s):  
Point Spread Function ◽  
Hubble Space Telescope ◽  
Planetary Nebulae ◽  
Magellanic Cloud ◽  
Space Telescope ◽  
Point Spread ◽  
Spread Function ◽  
Made In

We have obtained Hubble Space Telescope (HST) Planetary Camera (PC) images of a number of Magellanic Cloud planetary nebulae. The objects, except for SMP 83 were observed as part of the Cycle I GO program. The observations were made in the [O III] λ5007Å line. The object SMP 83, was observed as part of the GTO program, and in this case observations were also made in the Hα line using the F650N filter. In order to characterise the point spread function, a star was placed at the same point on the chip as the PN. This allowed us to determine the diameters of barely resolved PN in an accurate manner, by convolving the PSF with a function until it matched the appearance of the PN image. The results are given in Table 1.

scholarly journals The nature of point source fringes in mid-infrared spectra acquired with the James Webb Space Telescope

2020 ◽  
Vol 641 ◽  
pp. A150 ◽  
Author(s):  
Ioannis Argyriou ◽  
Martyn Wells ◽  
Alistair Glasse ◽  
David Lee ◽  
Pierre Royer ◽  
...  
Keyword(s):  
Point Source ◽  
Point Spread Function ◽  
Point Sources ◽  
Systematic Variation ◽  
Multiple Point ◽  
Mid Infrared ◽  
Space Telescope ◽  
Point Spread ◽  
Spread Function ◽  
Extended Sources

Context. As is common for infrared spectrometers, the constructive and destructive interference in different layers of the James Webb Space Telescope (JWST) Mid-Infrared Instrument (MIRI) detector arrays modulate the detected signal as a function of wavelength. The resulting “fringing” in the Medium-Resolution Spectrometer (MRS) spectra varies in amplitude between 10% and 30% of the spectral baseline. A common method for correcting for fringes relies on dividing the data by a fringe flat. In the case of MIRI MRS, the fringe flat is derived from measurements of an extended, spatially homogeneous source acquired during the thermal-vacuum ground verification of the instrument. While this approach reduces fringe amplitudes of extended sources below the percent level, at the detector level, point source fringe residuals vary in a systematic way across the point spread function. The effect could hamper the scientific interpretation of MRS observations of unresolved sources, semi-extended sources, and point sources in crowded fields. Aims. We find MIRI MRS point source fringes to be reproducible under similar observing conditions. We want to investigate whether a generic and accurate correction can be determined. Therefore, we want to identify the variables, if they exist, that would allow for a parametrization of the signal variations induced by point source fringe modulations. Methods. We determine the point source fringe properties by analyzing MRS detector plane images acquired on the ground. We extracted the fringe profile of multiple point source observations and studied the amplitude and phase of the fringes as a function of field position and pixel sampling of the point spread function of the optical chain. Results. A systematic variation in the amplitude and phase of the point source fringes is found over the wavelength range covered by the test sources (4.9 − 5.8 μm). The variation depends on the fraction of the point spread function seen by the detector pixel. We identify the non-uniform pixel illumination as the root cause of the reported systematic variation. This new finding allows us to reconcile the point source and extended source fringe patterns observed in test data during ground verification. We report an improvement after correction of 50% on the 1σ standard deviation of the spectral continuum. A 50% improvement is also reported in line sensitivity for a benchmark test with a spectral continuum of 100 mJy. The improvement in the shape of weak lines is illustrated using a T Tauri model spectrum. Consequently, we verify that fringes of extended sources and potentially semi-extended sources and crowded fields can be simulated by combining multiple point source fringe transmissions. Furthermore, we discuss the applicability of this novel fringe-correction method to the MRS data (and the data of other instruments).

scholarly journals Mitigating the effects of undersampling in weak lensing shear estimation with metacalibration

2021 ◽  
Vol 502 (3) ◽  
pp. 4048-4063
Author(s):  
Arun Kannawadi ◽  
Erik Rosenberg ◽  
Henk Hoekstra
Keyword(s):  
Point Spread Function ◽  
Gravitational Lensing ◽  
State Of The Art ◽  
Weak Lensing ◽  
Weight Functions ◽  
High Signal ◽  
Signal To Noise ◽  
Space Telescope ◽  
Point Spread ◽  
Spread Function

ABSTRACT metacalibration is a state-of-the-art technique for measuring weak gravitational lensing shear from well-sampled galaxy images. We investigate the accuracy of shear measured with metacalibration from fitting elliptical Gaussians to undersampled galaxy images. In this case, metacalibration introduces aliasing effects leading to an ensemble multiplicative shear bias about 0.01 for Euclid  and even larger for the Roman Space Telescope, well exceeding the missions’ requirements. We find that this aliasing bias can be mitigated by computing shapes from weighted moments with wider Gaussians as weight functions, thereby trading bias for a slight increase in variance of the measurements. We show that this approach is robust to the point-spread function in consideration and meets the stringent requirements of Euclid for galaxies with moderate to high signal-to-noise ratios. We therefore advocate metacalibration as a viable shear measurement option for weak lensing from upcoming space missions.

Point spread function based feature optimization and fusion for underwater objet recognition

2013 ◽  
Vol 26 (11) ◽  
pp. 944-952 ◽  
Author(s):  
Huibin Wang ◽  
Rong Zhang ◽  
Zhe Chen ◽  
Lizhong Xu ◽  
Jie Shen
Keyword(s):  
Point Spread Function ◽  
Point Spread ◽  
Spread Function ◽  
Feature Optimization
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