Related papers: Cosmic-Ray Rejection by Laplacian Edge Detection
We present a convolution-based algorithm for finding cosmic rays in single well-sampled astronomical images. The spatial filter used is the point spread function (approximated by a Gaussian) minus a scaled delta function, and cosmic rays…
We present a method for detecting cosmic rays in single images. The algorithm is based on simple analysis of the histogram of the image data and does not use any modeling of the picture of the object. It does not require a good signal to…
To maximise data output from single-shot astronomical images, the rejection of cosmic rays is important. We present the results of a benchmark trial comparing various cosmic ray rejection algorithms. The procedures assess relative…
Single-exposure spectra in large spectral surveys are valuable for time domain studies such as stellar variability, but there is no available method to eliminate cosmic rays for single-exposure, multi-fiber spectral images. In this paper,…
Astronomical images often show sharp features that are caused by cosmic ray (CR) hits, hot pixels, or non-Gaussian noise. L.A.Cosmic (van Dokkum 2001) is a widely used edge detection algorithm that identifies and replaces such features.…
We present an algorithm to optimally process uniformly sampled array image data obtained with a nondestructive readout. The algorithm discards full wells, removes cosmic ray (particle) hits and other glitches, and makes a nearly optimum…
Traditional cosmic ray filtering algorithms used in X-ray imaging detectors aboard space telescopes perform event reconstruction based on the properties of activated pixels above a certain energy threshold, within 3x3 or 5x5 pixel sliding…
Cosmic ray (CR) identification and replacement are critical components of imaging and spectroscopic reduction pipelines involving solid-state detectors. We present deepCR, a deep learning based framework for CR identification and subsequent…
As a space telescope, the China Space Station Survey Telescope (CSST) will face significant challenges from cosmic ray (CR) contamination. These CRs will severely degrade image quality and further influence scientific analysis. Due to the…
Cosmic rays are a known problem in astronomy, causing both loss of data and data inaccuracy. The problem becomes even more extreme when considering data from a high-radiation environment, such as in orbit around Earth or outside the Earth's…
(Abridged) Gaia aims to make a 3-dimensional map of 1,000 million stars in our Milky Way to unravel its kinematical, dynamical, and chemical structure and evolution. Gaia's on-board detection software discriminates stars from spurious…
Cosmic ray astronomy attempts to identify and study the sources of ultrahigh energy cosmic rays. It is unique in its reliance on charged particles as the information carriers. While no discrete source of ultrahigh energy cosmic rays has…
We present a new approach for the identification of ultra-high energy cosmic rays from sources using dynamic graph convolutional neural networks. These networks are designed to handle sparsely arranged objects and to exploit their short-…
We present a novel method to search for structures of coherently aligned patterns in ultra-high energy cosmic-ray arrival directions simultaneously across the entire sky. This method can be used to obtain information on the Galactic…
We present a method to correct for deflections of ultra-high energy cosmic rays in the galactic magnetic field. We perform these corrections by simulating the expected arrival directions of protons using a parameterization of the field…
Sub-GeV dark matter candidates are of increasing interest, because long-favored candidates such as GeV-scale WIMPs have not been detected. For low-mass dark matter, model-independent constraints are weak or nonexistent. We show that for…
The understanding of the nature of ultra-high-energy cosmic rays is one of the most intriguing open questions for current and future observatories. These particles are expected to be accelerated in extragalactic sources. Because of their…
The cosmic crystallography method of Lehoucq et al. [1] produces sharp peaks in the distribution of distances between the images of cosmic sources. But the method cannot be applied to universes with compact spatial sections of negative…
Rejecting cosmic rays (CRs) is essential for the scientific interpretation of CCD-captured data, but detecting CRs in single-exposure images has remained challenging. Conventional CR detectors require experimental parameter tuning for…
Cosmic crystallography is based on the principle that peaks in the pair separation histogram (PSH) of objects in a catalogue should be induced by the high number of topologically lensed pairs that are separated by Clifford translations, in…