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@ARTICLE{Chekhovsky:635897,
      author       = {Chekhovsky, Vladimir and others},
      collaboration = {{CMS Collaboration}},
      title        = {{M}odel-agnostic search for dijet resonances with anomalous
                      jet substructure in proton–proton collisions at $\sqrt{s}$
                      = 13 {T}e{V}},
      journal      = {Reports on progress in physics},
      volume       = {88},
      number       = {6},
      issn         = {0034-4885},
      address      = {Bristol},
      publisher    = {IOP Publ.},
      reportid     = {PUBDB-2025-03581, arXiv:2412.03747. CMS-EXO-22-026.
                      CERN-EP-2024-291},
      pages        = {067802},
      year         = {2025},
      abstract     = {This paper presents a model-agnostic search for narrow
                      resonances in the dijet final state in the mass range
                      1.8–6 TeV. The signal is assumed to produce jets with
                      substructure atypical of jets initiated by light quarks or
                      gluons, with minimal additional assumptions. Search regions
                      are obtained by utilizing multivariate machine-learning
                      methods to select jets with anomalous substructure. A
                      collection of complementary anomaly detection
                      methods—based on unsupervised, weakly supervised, and
                      semisupervised algorithms—are used in order to maximize
                      the sensitivity to unknown new physics signatures. These
                      algorithms are applied to data corresponding to an
                      integrated luminosity of 138 fb$^{−1}$, recorded by the
                      CMS experiment at the LHC, at a center-of-mass energy of 13
                      TeV. No significant excesses above background expectations
                      are seen. Exclusion limits are derived on the production
                      cross section of benchmark signal models varying in
                      resonance mass, jet mass, and jet substructure. Many of
                      these signatures have not been previously sought, making
                      several of the limits reported on the corresponding
                      benchmark models the first ever. When compared to benchmark
                      inclusive and substructure-based search strategies, the
                      anomaly detection methods are found to significantly enhance
                      the sensitivity to a variety of models.},
      keywords     = {CMS (autogen) / ML (autogen) / anomaly (autogen) / dijet
                      (autogen) / resonance (autogen)},
      cin          = {CMS},
      ddc          = {530},
      cid          = {I:(DE-H253)CMS-20120731},
      pnm          = {611 - Fundamental Particles and Forces (POF4-611) / DFG
                      project G:(GEPRIS)390833306 - EXC 2121: Quantum Universe
                      (390833306) / HIDSS-0002 - DASHH: Data Science in Hamburg -
                      Helmholtz Graduate School for the Structure of Matter
                      $(2019_IVF-HIDSS-0002)$ / GRK 2497 - GRK 2497: Physik der
                      schwersten Teilchen am Large Hadron Collider (400140256)},
      pid          = {G:(DE-HGF)POF4-611 / G:(GEPRIS)390833306 /
                      $G:(DE-HGF)2019_IVF-HIDSS-0002$ / G:(GEPRIS)400140256},
      experiment   = {EXP:(DE-H253)LHC-Exp-CMS-20150101},
      typ          = {PUB:(DE-HGF)16},
      eprint       = {2412.03747},
      howpublished = {arXiv:2412.03747},
      archivePrefix = {arXiv},
      SLACcitation = {$\%\%CITATION$ = $arXiv:2412.03747;\%\%$},
      pubmed       = {pmid:40354794},
      doi          = {10.1088/1361-6633/add762},
      url          = {https://bib-pubdb1.desy.de/record/635897},
}