Model-independent searches of new physics in DARWIN with deep learning

Aalbers, J. orcid.org/0000-0003-0030-0030, Abe, K. orcid.org/0009-0000-9620-788X, Adrover, M. et al. (228 more authors) (2026) Model-independent searches of new physics in DARWIN with deep learning. The European Physical Journal C, 86 (3). 312. ISSN: 1434-6044

Abstract

Metadata

Item Type: Article
Authors/Creators:
Copyright, Publisher and Additional Information:

© The Author(s) 2026. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

Keywords: XLZD Collaboration
Dates:
  • Submitted: 21 October 2024
  • Accepted: 3 December 2025
  • Published (online): 26 March 2026
  • Published: January 2026
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Science (Sheffield) > School of Mathematical and Physical Sciences
Funding Information:
Funder
Grant number
Swiss National Science Foundation
175863
Swiss National Science Foundation
162501
Date Deposited: 09 Apr 2026 13:44
Last Modified: 09 Apr 2026 13:44
Status: Published
Publisher: Springer Science and Business Media LLC
Refereed: Yes
Identification Number: 10.1140/epjc/s10052-025-15161-2
Related URLs:
Open Archives Initiative ID (OAI ID):

Export

Statistics