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

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.

arXiv comment54 pages, 14 figures, two references added in v2. v3 accepted for publication in JHEP. Homepage: https://smodels.github.io/protomodels

References in corpus (15)

• An Introduction to PYTHIA 8.2
• Threshold resummation for squark-antisquark and gluino-pair production at the LHC
• Squark and gluino hadroproduction
• Soft-gluon resummation for squark and gluino hadroproduction
• Supersymmetric top and bottom squark production at hadron colliders
• SModelS: a tool for interpreting simplified-model results from the LHC and its application to supersymmetry
• The performance of the CMS muon detector in proton-proton collisions at sqrt(s) = 7 TeV at the LHC
• Constraining new physics with searches for long-lived particles: Implementation into SModelS
• Constraining new physics with collider measurements of Standard Model signatures
• SModelS database update v1.2.3
• Searches for New Physics: Les Houches Recommendations for the Presentation of LHC Results
• Solving the LHC Inverse Problem with Dark Matter Observations
• The Simplified Likelihood Framework
• Taming systematic uncertainties at the LHC with the central limit theorem
• A Meta-analysis of the 8 TeV ATLAS and CMS SUSY Searches

Cited by in corpus (7)

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• Strength in numbers: optimal and scalable combination of LHC new-physics searches
• Global LHC constraints on electroweak-inos with SModelS v2.3
• Graph Reinforcement Learning for Exploring BSM Model Spaces