Work

Towards efficient machine-learning-based reduction of the cosmic-ray induced background in X-ray imaging detectors: increasing context awareness

Year: 2024

Type: conference-paper

Source: Space Telescopes and Instrumentation: Ultraviolet to Gamma Ray

DOI: 10.1117/12.3020598

Authors: Artem Poliszczuk, Dan R. Wilkins, Steven W. Allen, Eric D. Miller, Tanmoy Chattopadhyay, Benjamin Schneider, Julien E. Darve, Marshall W. Bautz, Abraham D. Falcone, Rick F. Foster, Catherine E. Grant, Sven C. Herrmann, Ralph P. Kraft, Glenn Morris, Paul E. J. Nulsen, Peter Orel, Gerrit Schellenberger, Haley R. Stueber

Institutions: Kavli Institute for Particle Astrophysics and Cosmology, Stanford University, SLAC National Accelerator Laboratory, Massachusetts Institute of Technology, Pennsylvania State University, Smithsonian Institution, Center for Astrophysics Harvard & Smithsonian

Language: English

Topic: Particle Detector Development and Performance

Subfield: Nuclear and High Energy Physics

Field: Physics and Astronomy

Domain: Physical Sciences

Open Access status: closed

OpenAlex ID: W4401778790

FWCI:

Cites: 56

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Related to: 10