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High Energy Physics - Phenomenology

arXiv:2509.22247 (hep-ph)
[Submitted on 26 Sep 2025 (v1), last revised 4 Mar 2026 (this version, v3)]

Title:Fair Universe Higgs Uncertainty Challenge

Authors:Ragansu Chakkappai (1 and 2), Wahid Bhimji (3), Paolo Calafiura (3), Po-Wen Chang (3), Yuan-Tang Chou (4), Sascha Diefenbacher (3), Jordan Dudley (5 and 3), Steven Farrell (3), Aishik Ghosh (6 and 3), Isabelle Guyon (2), Chris Harris (3), Shih-Chieh Hsu (4), Elham E. Khoda (7 and 4 and 3), Benjamin Nachman (3), Peter Nugent (3), David Rousseau (1 and 2), Benjamin Thorne (3), Ihsan Ullah (2), Yulei Zhang (4) ((1) Université Paris-Saclay, CNRS/IN2P3, IJCLab, Orsay, France, (2) ChaLearn, USA, (3) Lawrence Berkeley National Laboratory, Berkeley, USA, (4) University of Washington, Seattle, USA, (5) University of California, Berkeley, USA, (6) University of California, Irvine, USA, (7) University of California, San Diego, USA)
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Abstract:This competition in high-energy physics (HEP) and machine learning was the first to strongly emphasise uncertainties in $(H \rightarrow \tau^+ \tau^-)$ cross-section measurement. Participants were tasked with developing advanced analysis techniques capable of dealing with uncertainties in the input training data and providing credible confidence intervals. The accuracy of these intervals was evaluated using pseudo-experiments to assess correct coverage. The dataset is now published in Zenodo, and the winning submissions are fully documented.
Comments: To be published in SciPost Physics Proceedings
Subjects: High Energy Physics - Phenomenology (hep-ph); High Energy Physics - Experiment (hep-ex)
Cite as: arXiv:2509.22247 [hep-ph]
  (or arXiv:2509.22247v3 [hep-ph] for this version)
  https://doi.org/10.48550/arXiv.2509.22247

Submission history

From: Ragansu Chakkappai [view email]
[v1] Fri, 26 Sep 2025 12:05:56 UTC (417 KB)
[v2] Thu, 30 Oct 2025 17:01:19 UTC (413 KB)
[v3] Wed, 4 Mar 2026 15:24:44 UTC (408 KB)
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