2026-02-25 10:51 |
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2026-02-25 10:49 |
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2026-02-25 10:46 |
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2026-02-25 10:41 |
[PUBDB-2026-00849]
Journal Article
Aad, G. ; Aakvaag, E. ; Abbott, B. K. ; et al
Transforming jet flavour tagging at ATLAS
[CERN-EP-2025-103; arXiv:2505.19689]
Jet flavour tagging enables the identification of jets originating from heavy-flavour quarks in proton–proton collisions at the Large Hadron Collider, playing a critical role in its physics programmes. This paper presents GN2, a transformer-based flavour tagging algorithm deployed by the ATLAS Collaboration that represents a different methodology compared to previous approaches. [...]
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2026-02-25 10:38 |
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2026-02-24 14:15 |
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2026-02-23 15:42 |
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2026-02-23 09:32 |
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2026-02-21 17:17 |
[PUBDB-2026-00809]
Poster
Klemps, A. ; Ilia, D. ; banjaree, p. k. ; et al
Machine Learning driven beam emittance optimization at EuXFEL
20255th ICFA Beam Dynamics Mini-Workshop on Machine Learning for Particle Accelerators, CERNCERN, Switzerland, 8 Apr 2025 - 11 Apr 20252025-04-082025-04-11
Planned upgrades of the European X-Ray Free Electron Laser (EuXFEL) target higher photon energy and a high duty-cycle operation up to CW-operation using a superconducting RF gun with lower gradient. An operation in this regime though critically depends on improvements of the beam slice emittance of the electron gun. [...]
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2026-02-20 15:03 |
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