Related papers: Evaluation of cosmic ray rejection algorithms on s…
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-…
When solving scientific and applied problems, such as latitude monitoring, it is important to correctly exclude primary cosmic ray variations from observation data. Therefore, the purpose of this study was to develop and implement a method…
The Earth is subjected to a uniform flux of very-high-energy (VHE, E > 100 GeV) cosmic rays unless they are obscured by an object, such as the Moon, in which case a deficit or shadow is created. Since cosmic rays are charged this deficit is…
The results of recognition of cosmic ray (CR) signatures on a single image were analyzed for several codes written by several authors. For most visual images made during low solar activity at exposure time t>4 s, the number of clusters of…
The sensitivity of astronomical X-ray detectors is limited by the instrumental background. The background is especially important when observing low surface brightness sources that are critical for many of the science cases targeted by…
Depth estimation using a single-photon LiDAR is often solved by a matched filter. It is, however, error-prone in the presence of background noise. A commonly used technique to reject background noise is the rank-ordered mean (ROM) filter…
This work reinterprets so-called 'noise' in cosmic ray imaging, indicating that the data of reconstructed Points of Closest Approach (PoCA points) outside the volume of interest defined by traditional tomography methods contain valuable…
A Kalman Filter alignment algorithm has been applied to cosmic-ray data. We discuss the alignment algorithm and an experiment-independent implementation including outlier rejection and treatment of weakly determined parameters. Using this…
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.…
The interpretation of data from indirect detection experiments searching for dark matter annihilations requires computationally expensive simulations of cosmic-ray propagation. In this work we present a new method based on Recurrent Neural…
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…
Digital radio detection of cosmic-ray air showers has emerged as an alternative technique in high-energy astroparticle physics. Estimation of the detection efficiency of cosmic-ray radio arrays is one of the few remaining challenges…
Over the past decade, radio detection of cosmic rays has matured from small-scale prototype experiments to installations spanning several km$^2$ with more than a hundred antennas. The physics of the radio signal is well understood and…
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…
A cosmic ray observatory with full-sky coverage can exploit standard anisotropy analysis methods that do not work if part of the celestial sphere is never seen. In particular, the distribution of arrival directions can be fully…
Object recognition systems are usually trained and evaluated on high resolution images. However, in real world applications, it is common that the images have low resolutions or have small sizes. In this study, we first track the…
[Abridged] Detecting cosmic ray hits (cosmics) in fiber-fed IFS data of single exposures is a challenging task, because of the complex signal recorded by IFS instruments. Existing detection algorithms are commonly found to be unreliable in…
Bringing artificial intelligence (AI) alongside next-generation X-ray imaging detectors, including CCDs and DEPFET sensors, enhances their sensitivity to achieve many of the flagship science cases targeted by future X-ray observatories,…
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…
This paper implements likelihood-based jump detection for detectors read out up-the-ramp, using the entire set of reads to compute likelihoods. The approach compares the $\chi^2$ value of a fit with and without a jump for every possible…