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High Energy Physics - Phenomenology

arXiv:2012.12246 (hep-ph)
[Submitted on 22 Dec 2020 (v1), last revised 15 Mar 2021 (this version, v3)]

Title:Artificial Proto-Modelling: Building Precursors of a Next Standard Model from Simplified Model Results

Authors:Wolfgang Waltenberger, André Lessa, Sabine Kraml
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Abstract:We present a novel algorithm to identify potential dispersed signals of new physics in the slew of published LHC results. It employs a random walk algorithm to introduce sets of new particles, dubbed "proto-models", which are tested against simplified-model results from ATLAS and CMS (exploiting the SModelS software framework). A combinatorial algorithm identifies the set of analyses and/or signal regions that maximally violates the SM hypothesis, while remaining compatible with the entirety of LHC constraints in our database. Demonstrating our method by running over the experimental results in the SModelS database, we find as currently best-performing proto-model a top partner, a light-flavor quark partner, and a lightest neutral new particle with masses of the order of 1.2 TeV, 700 GeV and 160 GeV, respectively. The corresponding global p-value for the SM hypothesis is approximately 0.19; by construction no look-elsewhere effect applies.
Comments: 54 pages, 14 figures, two references added in v2. v3 accepted for publication in JHEP. Homepage: this https URL
Subjects: High Energy Physics - Phenomenology (hep-ph); High Energy Physics - Experiment (hep-ex); Applications (stat.AP)
Cite as: arXiv:2012.12246 [hep-ph]
  (or arXiv:2012.12246v3 [hep-ph] for this version)
  https://doi.org/10.48550/arXiv.2012.12246
Journal reference: Journal of High Energy Physics 2021, 207 (2021)
Related DOI: https://doi.org/10.1007/JHEP03%282021%29207

Submission history

From: Wolfgang Waltenberger [view email]
[v1] Tue, 22 Dec 2020 18:45:22 UTC (2,916 KB)
[v2] Tue, 5 Jan 2021 12:05:20 UTC (2,915 KB)
[v3] Mon, 15 Mar 2021 11:21:18 UTC (962 KB)
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