scholarly journals Fast algorithms to approximate the position-dependent point spread function responses in radio interferometric wide-field imaging

2020 ◽  
Vol 499 (1) ◽  
pp. 292-303
Author(s):  
M Atemkeng ◽  
O Smirnov ◽  
C Tasse ◽  
G Foster ◽  
S Makhathini
Keyword(s):  
Point Spread Function ◽  
Simulated Data ◽  
High Sensitivity ◽  
Image Plane ◽  
Three Dimensions ◽  
Wide Field ◽  
Point Spread ◽  
Spread Function ◽  
Field Imaging ◽  
Wide Field Imaging

ABSTRACT The desire for wide field of view, large fractional bandwidth, high sensitivity, high spectral and temporal resolution has driven radio interferometry to the point of big data revolution where the data are represented in at least three dimensions with an axis for spectral windows, baselines, sources, etc., where each axis has its own set of subdimensions. The cost associated with storing and handling these data is very large, and therefore several techniques to compress interferometric data and/or speed up processing have been investigated. Unfortunately, averaging-based methods for visibility data compression are detrimental to the data fidelity, since the point spread function (PSF) is position-dependent, that is, distorted and attenuated as a function of distance from the phase centre. The position dependence of the PSF becomes more severe, requiring more PSF computations for wide-field imaging. Deconvolution algorithms must take the distortion into account in the major and minor cycles to properly subtract the PSF and recover the fidelity of the image. This approach is expensive in computation since at each deconvolution iteration a distorted PSF must be computed. We present two algorithms that approximate these position-dependent PSFs with fewer computations. The first algorithm approximates the position-dependent PSFs in the uv-plane and the second algorithm approximates the position-dependent PSFs in the image plane. The proposed algorithms are validated using simulated data from the MeerKAT telescope.

scholarly journals The Point Spread Function Variations inside Wide-field Astonomical Images

10.14311/1696 ◽  
2013 ◽  
Vol 53 (1) ◽  
Author(s):  
Elena Anisimova ◽  
Jan Bednář ◽  
Petr Páta
Keyword(s):  
Point Spread Function ◽  
Imaging System ◽  
Wide Field ◽  
Optical Aberrations ◽  
Atmospheric Scattering ◽  
Function Fitting ◽  
Astronomical Imaging ◽  
Point Spread ◽  
Spread Function ◽  
Field Imaging

The Point Spread Function (PSF) of the astronomical imaging system is usually approximated by a Gaussian or Moffat function. For simplification, the astronomical imaging system is considered to be time and space invariant. This means that invariable PSF within an exposed image is assumed. If real wide-field imaging systems are considered, this presumption is not fulfilled. In real systems, stronger optical aberrations are expected (especially coma) at greater distances from the center of the captured image. This impacts the efficiency of stellar astrometry and photometry algorithms, so it is necessary to know the PSF variation. In this paper, we perform the first step toward assigning PSF changes: we study the dependence of the Moffat function fitting parameters (FWHM and the atmospheric scattering coefficient ) on the position of a stellar object.

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.

Point spread function degradation model of a polarization imaging system for wide-field subwavelength nanoparticles

2020 ◽  
Vol 59 (23) ◽  
pp. 7114 ◽  
Author(s):  
Wu Qiong ◽  
Kun Gan ◽  
Zizheng Hua ◽  
Zhenzhou Zhang ◽  
Hanwen Zhao ◽  
...  
Keyword(s):  
Point Spread Function ◽  
Imaging System ◽  
Wide Field ◽  
Degradation Model ◽  
Polarization Imaging ◽  
Point Spread ◽  
Spread Function

scholarly journals Physics-based model of the adaptive-optics-corrected point spread function

2019 ◽  
Vol 628 ◽  
pp. A99 ◽  
Author(s):  
R. J. L. Fétick ◽  
T. Fusco ◽  
B. Neichel ◽  
L. M. Mugnier ◽  
O. Beltramo-Martin ◽  
...  
Keyword(s):  
Adaptive Optics ◽  
Point Spread Function ◽  
Simulated Data ◽  
Optical Systems ◽  
Field Mode ◽  
The Core ◽  
Point Spread ◽  
Power Spectral ◽  
Spread Function ◽  
Large Telescopes

Context. Adaptive optics (AO) systems greatly increase the resolution of large telescopes, but produce complex point spread function (PSF) shapes, varying in time and across the field of view. The PSF must be accurately known since it provides crucial information about optical systems for design, characterization, diagnostics, and image post-processing. Aims. We develop here a model of the AO long-exposure PSF, adapted to various seeing conditions and any AO system. This model is made to match accurately both the core of the PSF and its turbulent halo. Methods. The PSF model we develop is based on a parsimonious parameterization of the phase power spectral density, with only five parameters to describe circularly symmetric PSFs and seven parameters for asymmetrical ones. Moreover, one of the parameters is the Fried parameter r0 of the turbulence’s strength. This physical parameter is an asset in the PSF model since it can be correlated with external measurements of the r0, such as phase slopes from the AO real time computer (RTC) or site seeing monitoring. Results. We fit our model against end-to-end simulated PSFs using the OOMAO tool, and against on-sky PSFs from the SPHERE/ZIMPOL imager and the MUSE integral field spectrometer working in AO narrow-field mode. Our model matches the shape of the AO PSF both in the core and the halo, with a relative error smaller than 1% for simulated and experimental data. We also show that we retrieve the r0 parameter with sub-centimeter precision on simulated data. For ZIMPOL data, we show a correlation of 97% between our r0 estimation and the RTC estimation. Finally, MUSE allows us to test the spectral dependency of the fitted r0 parameter. It follows the theoretical λ6/5 evolution with a standard deviation of 0.3 cm. Evolution of other PSF parameters, such as residual phase variance or aliasing, is also discussed.

scholarly journals Scanning FCS, a novel method for three-dimensional particle tracking

2003 ◽  
Vol 31 (5) ◽  
pp. 997-1000 ◽  
Author(s):  
V. Levi ◽  
Q. Ruan ◽  
K. Kis-Petikova ◽  
E. Gratton
Keyword(s):  
Laser Beam ◽  
Fluorescence Intensity ◽  
Point Spread Function ◽  
Three Dimensional ◽  
Three Dimensions ◽  
Circular Path ◽  
Fluorescent Particle ◽  
Point Spread ◽  
Spread Function ◽  
Novel Method

We describe a novel method to track fluorescent particles in three dimensions with nanometre precision and millisecond time resolution. In this method, we use our two-photon excitation microscope. The galvomotor-driven x–y scanning mirrors allow the laser beam to move repetitively in a circular path with a radius of half the width of the point spread function of the laser. When the fluorescent particle is located within the scanning radius of the laser, the precise position of the particle in the x–x plane can be determined by its fluorescence intensity distribution along the circular scanning path. A z-nanopositioner on the objective was used to change the laser focus at two planes (half width of the point spread function apart). The difference of the fluorescence intensity in the two planes is used to calculate the z-position of the fluorescent particle. The laser beam is allowed to scan multiple circular orbits before it is moved to the other plane, thus improving the signal to noise ratio. With a fast feedback mechanism, the position of the laser beam is directed to the centre of the fluorescent particle, thus allowing us to track a particle in three dimensions. In this contribution we describe some calibration experiments performed to test the three-dimensional tracking capability of our system over a large range.

scholarly journals Point spread function modelling for wide-field small-aperture telescopes with a denoising autoencoder

2020 ◽  
Vol 493 (1) ◽  
pp. 651-660 ◽  
Author(s):  
Peng Jia ◽  
Xiyu Li ◽  
Zhengyang Li ◽  
Weinan Wang ◽  
Dongmei Cai
Keyword(s):  
Point Spread Function ◽  
Wide Field ◽  
Calibration Data ◽  
Post Processing ◽  
Denoising Autoencoder ◽  
Small Aperture ◽  
Point Spread ◽  
Spread Function ◽  
Function Modelling ◽  
Star Images

ABSTRACT The point spread function reflects the state of an optical telescope and it is important for the design of data post-processing methods. For wide-field small-aperture telescopes, the point spread function is hard to model because it is affected by many different effects and has strong temporal and spatial variations. In this paper, we propose the use of a denoising autoencoder, a type of deep neural network, to model the point spread function of wide-field small-aperture telescopes. The denoising autoencoder is a point spread function modelling method, based on pure data, which uses calibration data from real observations or numerical simulated results as point spread function templates. According to real observation conditions, different levels of random noise or aberrations are added to point spread function templates, making them realizations of the point spread function (i.e. simulated star images). Then we train the denoising autoencoder with realizations and templates of the point spread function. After training, the denoising autoencoder learns the manifold space of the point spread function and it can map any star images obtained by wide-field small-aperture telescopes directly to its point spread function. This could be used to design data post-processing or optical system alignment methods.

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