{"ID":2869444,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2509.15121","arxiv_id":"2509.15121","title":"Shedding Light on Dark Matter at the LHC with Machine Learning","abstract":"We investigate a WIMP dark matter (DM) candidate in the form of a singlino-dominated lightest supersymmetric particle (LSP) within the $Z_3$-symmetric Next-to-Minimal Supersymmetric Standard Model (NMSSM). This framework gives rise to regions of parameter space where DM is obtained via co-annihilation with nearby higgsino-like electroweakinos and DM direct detection~signals are suppressed, the so-called ``blind spots''. On the other hand, collider signatures remain promising due to enhanced radiative decay modes of higgsinos into the singlino-dominated LSP and photons, rather than into leptons or hadrons. Compared to MSSM scenarios with light bino- and wino-like electroweakinos, the NMSSM allows for final states with multiple photons arising from cascade radiative decays, providing a distinctive collider signature. This motivates searches for radiatively decaying neutralinos, however, these signals face substantial background challenges, as the decay products are typically soft due to the small mass-splits ($Δm$) between the LSP and the higgsino-like coannihilation partners. We apply a data-driven Machine Learning (ML) analysis that improves sensitivity to these subtle signals, offering a powerful complement to traditional search strategies to discover a new physics scenario. Using an LHC integrated luminosity of $100~\\mathrm{fb}^{-1}$ at $14~\\mathrm{TeV}$, the method achieves a $5σ$ discovery reach for higgsino masses up to $225~\\mathrm{GeV}$ with $Δm\\!\\lesssim\\!12~\\mathrm{GeV}$, and a $2σ$ exclusion up to $285~\\mathrm{GeV}$ with $Δm\\!\\lesssim\\!20~\\mathrm{GeV}$. These results highlight~the power of collider searches to probe DM candidates that remain hidden from current~direct detection experiments, and provide a motivation for a search by the LHC collaborations using ML methods.","short_abstract":"We investigate a WIMP dark matter (DM) candidate in the form of a singlino-dominated lightest supersymmetric particle (LSP) within the $Z_3$-symmetric Next-to-Minimal Supersymmetric Standard Model (NMSSM). This framework gives rise to regions of parameter space where DM is obtained via co-annihilation with nearby higgs...","url_abs":"https://arxiv.org/abs/2509.15121","url_pdf":"https://arxiv.org/pdf/2509.15121v2","authors":"[\"Ernesto Arganda\",\"Martín de los Rios\",\"Andres D. Perez\",\"Subhojit Roy\",\"Rosa M. Sandá Seoane\",\"Carlos E. M. Wagner\"]","published":"2025-09-18T16:27:19Z","proceeding":"hep-ph","tasks":"[\"hep-ph\",\"cs.LG\",\"hep-ex\"]","methods":"[]","has_code":false}