{
  "abstract": "The stabilization of the electroweak scale strongly motivates the search for new heavy resonances and top-partner states. We investigate the discovery potential of exotic resonances mediating the production of vector-like quarks at the High-Luminosity LHC ($\\sqrt{s} = 13.6$ TeV), focusing on the $pp \\to X \\to t \\bar{t}_p$ cascade decay. Using a model-independent Effective Field Theory approach, we classify the intermediate mediator $X$ by its spin (0 and 1) and color (singlet and octet) representations. Parton-level kinematics demonstrate that the normalized differential cross-section with respect to the transverse momentum provides a robust observable for spin discrimination. To address the experimental challenges of highly boosted, semi-resolved hadronic decays, we introduce a cut-flow strategy based on an inclusive four-jet invariant mass reconstruction, $M(4j)$. Because this standard approach remains sensitive to systematic uncertainties, we implement a Generalized BSM Tagger based on Deep Neural Networks (DNNs). By exploiting non-linear multi-jet correlations, the DNN achieves robust background rejection factors ranging from $\\mathcal{O}(600)$ to $\\mathcal{O}(1000)$ while preserving the underlying partonic signatures. Projecting to an integrated luminosity of $3000\\text{ fb}^{-1}$, this combined strategy yields a projected statistical significance of $3.74σ$ for the dominant color-octet vector channel, establishing strong evidence potential and offering a robust phenomenological baseline for future HL-LHC searches.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": "2609.10130",
  "author_total": 2,
  "authors": [
    {
      "name": "Hadjer Boukhrouf"
    },
    {
      "name": "Zouina Belghobsi"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/74ye9qpx1pc0h.bib",
  "cited_by": 0,
  "doi": "10.48550/arxiv.2609.10130",
  "fulltext_url": null,
  "id": "74ye9qpx1pc0h",
  "issns": [],
  "landing_url": "https://arxiv.org/abs/2609.10130",
  "language": null,
  "licence": "LicenseRef-arXiv-nonexclusive-1.0",
  "licence_label": "arXiv licence",
  "licence_source": "article",
  "licence_url": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
  "metadata_licence": "CC0-1.0",
  "native_subjects": [
    [
      "arxiv",
      "hep-ph"
    ],
    [
      "openalex",
      "3106|Particle physics theoretical and experimental studies"
    ]
  ],
  "openalex": "W7212159300",
  "pdf_url": "https://arxiv.org/pdf/2609.10130",
  "pmcid": null,
  "pmid": null,
  "published": "2026-09-09",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/74ye9qpx1pc0h.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:20:12Z",
      "native_id": "2609.10130",
      "source": "arxiv",
      "url": "https://arxiv.org/abs/2609.10130"
    }
  ],
  "subjects": [
    {
      "field": "physics",
      "origin": "arxiv:hep-ph",
      "subfield": "high-energy"
    }
  ],
  "title": "Decoding Heavy Top-Philic Resonances at the HL-LHC: From Parton Kinematics to Deep Learning Signatures",
  "title_text": "Decoding Heavy Top-Philic Resonances at the HL-LHC: From Parton Kinematics to Deep Learning Signatures",
  "type": "preprint",
  "updated_at": "2026-10-30T12:20:12Z",
  "url": "https://research.draconitic.com/paper/74ye9qpx1pc0h",
  "venue": "arXiv",
  "versions": []
}