Related papers: Reducing the background in X-ray imaging detectors…
Collisions at high-energy particle colliders are a traditionally fruitful source of exotic particle discoveries. Finding these rare particles requires solving difficult signal-versus-background classification problems, hence machine…
Recent analysis of 23 years of Hubble Space Telescope ACS/SBC data has shown that background levels can vary considerably between observations, with most filters showing over an order of magnitude variation. For the shorter-wavelength…
Dark matter cannot be observed directly, but its weak gravitational lensing slightly distorts the apparent shapes of background galaxies, making weak lensing one of the most promising probes of cosmology. Several observational studies have…
The KATRIN experiment aims to measure the effective electron antineutrino mass $m_{\overline{\nu}_e}$ with a sensitivity of 0.2 eV/c$^2$ using a gaseous tritium source combined with the MAC-E filter technique. A low background rate is…
Applications of machine learning tools to problems of physical interest are often criticized for producing sensitivity at the expense of transparency. To address this concern, we explore a data planing procedure for identifying combinations…
Imaging atmospheric Cherenkov telescopes record an enormous number of cosmic-ray background events. Suppressing these background events while retaining $\gamma$-rays is key to achieving good sensitivity to faint $\gamma$-ray sources. The…
Deep X-ray surveys have shown that the cosmic X-ray background (XRB) is largely due to the accretion onto supermassive black holes, integrated over cosmic time. The ROSAT, Chandra and XMM-Newton satellites have resolved more than 80% of the…
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…
Physics goals of a Muon Collider (MC) can only be reached with appropriate design of the ring, interaction region (IR), high-field superconducting magnets, machine -detector interface (MDI) and detector. Results of the most recent realistic…
As a space X-ray imaging mission dedicated to time-domain astrophysics, the Einstein Probe (EP) carries two kinds of scientific payloads, the wide-field X-ray telescope (WXT) and the follow-up X-ray telescope (FXT). FXT utilizes Wolter-I…
The large-scale (~ 20') diffuse x-ray background surrounding a sample of quasars observed during ROSAT PSPC pointed observations is studied using a new source-detection algorithm, the scaling-index method. This algorithm, which can identify…
Background showers triggered by hadrons represent over 99.9% of all particles arriving at ground-based gamma-ray observatories. An important stage in the data analysis of these observatories, therefore, is the removal of hadron-triggered…
The low-frequency radio sky is dominated by the diffuse synchrotron emission of our Galaxy and extragalactic radio sources related to Active Galactic Nuclei and star-forming galaxies. This foreground emission is much brighter than the…
The anticipated high sensitivity and the science goals of the next generation X-ray space missions, like the International X-ray Observatory or Simbol-X, rely on a low instrumental background, which in turn requires optimized shielding…
This paper discusses various observations on beam-induced and cosmic-ray backgrounds in the ATLAS detector during the LHC 2012 proton-proton run. Building on published results based on 2011 data, the correlations between background and…
Extensive measurements of the X-ray background (XRB) yield a reasonably reliable characterisation of its basic properties. Having resolved most of the cosmic XRB into discrete sources, the levels and spectral shapes of its main components…
The problem of detecting new signals in the presence of an unknown background is ubiquitous in scientific discoveries and is especially prominent in the physical sciences. Most solutions proposed thus far to address the problem focus on…
Common approaches to explainable AI (XAI) for deep learning focus on analyzing the importance of input features on the classification task in a given model: saliency methods like SHAP and GradCAM are used to measure the impact of spatial…
Anomaly detection relies on designing a score to determine whether a particular event is uncharacteristic of a given background distribution. One way to define a score is to use autoencoders, which rely on the ability to reconstruct certain…
We investigate the impact of shot noise on the stochastic gravitational wave background generated by binary neutron star mergers, and confirm that the overall background can be significantly influenced by relatively few neighboring, loud…