相关论文: Beam squint and Stokes V with off-axis feeds

Radio-astronomical observations are increasingly contaminated by interference, and suppression techniques become essential. A powerful candidate for interference mitigation is adaptive spatial filtering. We study the effect of spatial…

Radio interferometry allows astronomers to probe small spatial scales that are often inaccessible with single-dish instruments. However, recovering the radio sky from an interferometer is an ill-posed deconvolution problem that astronomers…

Data sizes for next generation radio telescopes, such as the Square Kilometre Array (SKA), are far above that of their predecessors. The CLEAN algorithm was originally developed by H\"ogbom [1974], long before such data sizes were thought…

We present an imaging algorithm for polarimetric interferometric data from radio telescopes. It is based on Bayesian statistics and thereby able to provide uncertainties and to incorporate prior information such as positivity of the total…

Removing the aberrations introduced by the Point Spread Function (PSF) is a fundamental aspect of astronomical image processing. The presence of noise in observed images makes deconvolution a nontrivial task that necessitates the use of…

We present a simple but powerful technique for the analysis of polarized emission from radio galaxies and other objects. It is based on the fact that images of Stokes parameters often contain considerably more information than is available…

The Ultraviolet/Optical Telescope (UVOT) is one of three instruments onboard the Swift observatory. The photometric calibration has been published, and this paper follows up with details on other aspects of the calibration including a…

The SVOM mission under development will carry four instruments, and in particular the coded-mask telescope named ECLAIRs, with a large field of view of about 2 sr, operating in the 4-150 keV energy band. The trigger software on board…

Residual calibration errors are difficult to predict in interferometric radio polarimetry because they depend on the employed observational calibration strategy, encompassing the Stokes vector of the calibrator and parallactic angle…

Multichannel blind deconvolution is the problem of recovering an unknown signal $f$ and multiple unknown channels $x_i$ from their circular convolution $y_i=x_i \circledast f$ ($i=1,2,\dots,N$). We consider the case where the $x_i$'s are…

Microscopy is one of the most essential imaging techniques in life sciences. High-quality images are required in order to solve (potentially life-saving) biomedical research problems. Many microscopy techniques do not achieve sufficient…

Blind deconvolution is the problem of recovering a sharp image and a blur kernel from a noisy blurry image. Recently, there has been a significant effort on understanding the basic mechanisms to solve blind deconvolution. While this effort…

Aberration-corrected scanning transmission electron microscopes (STEM) provide sub-angstrom lateral resolution; however, the large convergence angle greatly reduces the depth of field. For microscopes with a small depth of field,…

Tackling unsupervised source separation jointly with an additional inverse problem such as deconvolution is central for the analysis of multi-wavelength data. This becomes highly challenging when applied to large data sampled on the sphere…

This paper is an attempt to mitigate the beam squint happening due to frequency-dependent phase shifts in the wideband beamforming scenario, specifically in radar applications. The estimation of the direction of arrival is significant for…

The problem of deblurring an image when the blur kernel is unknown remains challenging after decades of work. Recently there has been rapid progress on correcting irregular blur patterns caused by camera shake, but there is still much room…

The CLEAN algorithm, first published by H\"{o}gbom and its later variants such as Multiscale CLEAN (msCLEAN) by Cornwell, has been the most popular tool for deconvolution in radio astronomy. Interferometric imaging used in aperture…

Blind deconvolution is a technique to recover an original signal without knowing a convolving filter. It is naturally formulated as a minimization of a quartic objective function under some assumption. Because its differentiable part does…

In the imaging process of an astronomical telescope, the deconvolution of its beam or Point Spread Function (PSF) is a crucial task. However, deconvolution presents a classical and challenging inverse computation problem. In scenarios where…

Strong gravitational lensing offers a wealth of astrophysical information on the background source it affects, provided the lensed source can be reconstructed as if it was seen in the absence of lensing. In the present work, we illustrate…