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Search for emerging jets in $pp$ collisions at $\sqrt{s} = 13.6$ TeV with the ATLAS experiment

T0 review · 2 major / 3 minor · reviewed 2026-08-16 · deepseek-v4-flash

Pith's one-line read No emerging jets found: Z' dark mediator excluded to 2.6 TeV

desk verdict A clean ATLAS null search that closes two unprobed emerging-jet channels and debuts a reusable transformer tagger, with the caveat that the quoted exclusions are benchmark-specific rather than universal dark-QCD bounds. read the letter →

arxiv 2505.02429 v2 pith:VHD3MX5W submitted 2025-05-05 hep-ex

classification hep-ex
keywords emergingjetsdarkQCDlong-livedparticlesdisplacedverticesZ'mediatort-channelscalartransformerjettaggerLHCsearch
verification ladder T0 review T1 audit T2 compute T3 formal

The pith

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The reading

This search aims to establish whether dark-sector “emerging jets”—jets crowded with displaced vertices from long-lived dark pions decaying back to Standard Model particles—are produced in proton collisions through two channels not previously targeted: an s-channel Z' vector mediator and a t-channel scalar mediator. Using 51.8 inverse femtobarns of 13.6 TeV proton–proton collision data, it finds no significant excess over the Standard Model background and reports the first direct exclusions for both production modes. If correct, Z' mediators between 600 and 2550 GeV are ruled out for quark and dark-quark couplings of 0.01 and 0.1 (for dark pion decay lengths of 5–50 mm), and scalar mediators between 600 and 1375 GeV are ruled out for a quark–dark-quark coupling of 0.1.

What carries the argument

The central object is the emerging-jet topology: a jet containing several displaced vertices produced by dark pions that travel macroscopic distances before decaying into Standard Model quarks. Two selection strategies carry the analysis: a cut-based chain using the prompt-track fraction, the number of displaced vertices, the energy-correlation function ECF2, and the number of subjets, with background estimated by the ABCD method; and a transformer-based jet tagger trained on 12 million jets that classifies each jet with a score p_EJ, with background estimated from a measured per-jet mistag rate. A dedicated trigger selecting jets with a very low prompt-track fraction extends sensitivity to lower dijet masses, while a standard single-jet trigger covers the high-mass region.

What would settle it

Recompute the 95% confidence-level exclusion limits after re-running the same selections on signal samples with a different dark-sector mass hierarchy or a different number of dark quark flavours; if the boundary moves by more than the quoted uncertainties, the reported numbers depend on the unstudied parameter choice.

Watch

Extended reading notes

Core claim

The paper claims that, after a fully data-driven background estimate, the observed event counts agree with the Standard Model prediction in every signal region, so no evidence for emerging jets is found. The strongest result is a set of 95% confidence-level exclusion limits on mediator production: for a dark pion proper decay length between 5 and 50 mm, Z' masses from 600 to 2550 GeV are excluded at couplings g_q = 0.01 and g_qD = 0.1, and for a quark–dark-quark coupling of 0.1, Phi masses from 600 to 1375 GeV are excluded. The paper also claims that at m_Z' = 1500 GeV with a 50 mm dark pion decay length, quark couplings above 0.003 are excluded when the dark coupling exceeds 0.03, a sensitivity more than twenty times stronger than existing dijet resonance searches. These constitute the first direct constraints on emerging-jet pair production through an s-channel Z' mediator and the first search for t-channel scalar-mediated emerging jets.

Load-bearing premise

The quoted mass limits assume the simulated dark sector is configured with seven dark quark flavours, three dark colours, the mass hierarchy m_rhoD = 2 Lambda_D = 2 m_qD = 4 m_piD, and dark pions forced to decay to down quarks, and the paper states that the impact of varying these parameters was not explicitly studied.

Editorial extensions

If this is right

  • The excluded Z' mass range, up to 2550 GeV, is the first direct bound on this specific emerging-jet production channel, where previously only pair-produced bi-fundamental mediators had been constrained.
  • The ML-based strategy is more powerful than the cut-based one, excluding Z' masses up to 2550 GeV versus 2150 GeV and giving an order-of-magnitude stronger limits on the t-channel scalar mediator.
  • The search probes quark–dark-quark couplings down to about 0.003, more than twenty times smaller than what dijet resonance searches reach, opening a previously inaccessible part of dark-sector parameter space.
  • The limits stay nearly flat for dark pion decay lengths between 1 and 100 mm and only weaken above 100 mm, when a growing fraction of dark pions decay beyond the inner tracker.
  • The results are expected to remain sensitive to a broader set of dark QCD parameters, since variations in the dark colour and flavour numbers mostly change the dark pion multiplicity rather than the core signature.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

  • The transformer tagger's auxiliary tasks—classifying track origin and grouping tracks into vertices—could be transferred directly to other long-lived-particle searches at the same experiment, potentially sharpening their sensitivity without retraining from scratch.
  • The analysis is limited by the 61% systematic uncertainty attached to the mistag-rate parameterisation in the high-mass region; a finer parameterisation in terms of more jet observables could bring a notable gain in the reported limits.
  • With only a fraction of the full Run 3 dataset used here, simply doubling the integrated luminosity would push the Z' exclusion boundary beyond 2550 GeV, assuming the background estimates scale as expected.
  • The quoted exclusion numbers rest on one specific dark-sector benchmark (N_f = 7, N_c = 3, and the stated mass hierarchy); a reanalysis using alternative benchmark points would be a natural test of how much of the reported region actually survives.
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Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, and a circularity audit.

Referee Report

2 major / 3 minor

Summary. The paper reports a search for emerging jets—jets containing multiple displaced vertices from decays of long-lived dark mesons—using 51.8 fb⁻¹ of pp collisions at √s = 13.6 TeV recorded by ATLAS in 2022–2023. Two production modes are targeted: s-channel production of a Z′ boson decaying to a dark-quark pair, and t-channel exchange of a scalar mediator Φ producing dark quarks plus up to two SM quarks. Two complementary strategies are used: a cut-based selection on jet observables (PTF, ECF2, N_vtx, N_subjet) with a data-driven ABCD background estimate, and an ML-based strategy using a GN2-style transformer tagger with a data-driven mistag-rate background estimate. Both strategies are split into low- and high-m_jj regions with distinct triggers, including a dedicated emerging-jet trigger introduced for Run 3. No significant excess is observed: the yields in the four signal regions (Table 8) agree with the data-driven predictions (e.g., cut-based high-m_jj: 8 observed vs 7.5 ± 1.1 ± 1.1 predicted; ML-based low-m_jj: 24 vs 31.8 ± 0.8 ± 7.5). The background methods are validated in control regions and signal-adjacent validation regions (Tables 5–7). Using profile-likelihood fits and the CLs procedure, 95% CL exclusions are set for the specified benchmark dark sector: Z′ masses 600–2550 GeV for g_q = 0.01, g_qD = 0.1 with cτ between 5 and 50 mm, and Φ masses 600–1375 GeV for κ = 0.1.

Significance. The core null result is robust and model-independent: the observed yields agree with fully data-driven background predictions in all four signal regions, and the background uncertainties are quantified through ABCD closure tests, ML-inverted and VR-tag validation regions, and alternative mistag-rate parameterizations. The search is methodologically significant: it is the first application of a GN2-type transformer tagger to a beyond-the-Standard-Model signature in ATLAS, the first ATLAS ML tagger to exploit the large-impact-parameter tracking pass, and the first ML-based identification of displaced vertices in an ATLAS LLP search; the tagger demonstrably generalizes to the t-channel signal, which is absent from its training. The statistical model (profile likelihood, CLs, pyhf) is standard, and the asymptotic approximation is checked against pseudo-experiments. If the results stand, they provide the first direct constraints on emerging-jet pair production via an s-channel Z′ mediator and the first search for t-channel scalar-mediated emerging jets.

major comments (2)
  1. [§3.1, §8, Table 1, Abstract/Conclusions] The headline exclusions (Z′ up to 2550 GeV, Φ up to 1375 GeV) are computed for a single dark-sector benchmark with N_c = 3, N_f = 7, the mass hierarchy m_rhoD = 2Λ_D = 2m_qD = 4m_piD, dark pions forced to decay to down quarks, and no dark baryons, yet the Abstract and Conclusions quote these ranges as conditions only on the mediator couplings and on cτ. Section 8 states that the impact of varying N_c, N_f, and the mass hierarchy “has not been explicitly studied” and that these parameters are “primarily expected to affect the dark pion multiplicity” (Ref. [26]), which is a qualitative argument. Since the dark-pion multiplicity and pT spectrum directly determine N_vtx, displaced-track counts, PTF, ECF2, N_subjet, and the transformer tagger's track-level features, alternative dark-sector parameter points could shift the signal acceptance and hence the quoted mass ranges by an amount the paper does not quantify. I do not regard this as an internal inconsistency, because the benchmark is fully specified in Table 1 and Section 3.1, but the manuscript should carry the benchmark condition explicitly whenever the 2550 GeV/1375 GeV numbers are quoted in the Abstract and Conclusions, and should reference the m_piD scan of Figure 12 as partial robustness evidence or soften the final claim of Section 8 that the results “are therefore expected to remain sensitive across a broader range of dark QCD parameter choices.”
  2. [§6.2 and §8] In the ML-based strategy, the n_tag < 2 control region used to measure the mistag rate is not included as Poisson terms in the profile likelihood of Section 8; the robustness of the background extraction therefore rests on the <10% signal-contamination check and on the 23–61% parameterization systematics rather than on a simultaneous CR fit. Given the small SR yields this is adequate, but explicitly stating why the CR was not incorporated into the fit would strengthen the statistical presentation.
minor comments (3)
  1. [§1] A passage of heavily corrupted text beginning “figure QZ a diagram illustrati¯g…” appears in Section 1 near Figures 1–2 and is repeated, including duplicated paragraphs on the trigger regions and paper structure; this makes part of the introduction unreadable and must be corrected in the published version.
  2. [§9] In the first paragraph of the Conclusions, “Φ masses up to 1350 GeV are excluding” should read “are excluded.”
  3. [§5.1.1] The performance statement for the ECF2/pT > 40 GeV requirement (approximately 40% background rejection at over 90% signal efficiency) is not tied to a displayed distribution; a small table or figure of the signal and background efficiencies as a function of the ECF2/pT threshold would aid the reader.

Circularity Check

0 steps flagged · score 0.0 of 10

No significant circularity: the exclusions compare fixed signal benchmarks against data-driven backgrounds and validated control regions.

full rationale

The paper's derivation chain is self-contained: signal cross sections, widths, and dark-sector parameters are fixed input benchmarks (Section 3.1), and no output limit is obtained by fitting those inputs to data. Backgrounds are estimated data-driven via the ABCD and mistag-rate methods (Sections 6.1 and 6.2) and are validated in signal-adjacent control regions, so the CLs limits in Section 8 are genuine comparisons of simulated signal plus fitted background against observed yields rather than predicted quantities that reduce to their inputs. The transformer tagger (Section 5.2) is trained on simulated MC with disjoint folds and its threshold is fixed before evaluating the signal regions, so it is not a fitted parameter renamed as a prediction. Citations to prior phenomenological work (Refs. [26] and [37]) supply external benchmark model parameters, not a self-citation chain bearing the central claim. The admitted lack of explicit variation of N_c, N_f, and the mass hierarchy (Section 8) is a model-dependence caveat affecting the generality of the quoted exclusions, not a circular argument, because the analysis does not use those parameters as free outputs and no prediction is equivalent to an input by construction.

Assumptions & free parameters 4 free parameters · 5 assumptions · 0 invented entities

All free parameters are fixed benchmark inputs from prior literature, not fitted to the observed data. The analysis does not introduce new physical entities; it searches for pre-existing dark sector proposals. The main unmodeled freedom is the dark-sector parameter choice, which the paper acknowledges in Section 8.

free parameters (4)
  • Dark sector benchmark parameters (Nc, Nf, mass hierarchy) = Nc=3, Nf=7, m_rhoD = 2 Lambda_D = 2 m_qD = 4 m_piD; m_piD in {5, 10, 20} GeV
    Set by hand following Refs [22,26]; signal acceptance and hence the exclusion limits depend on these choices.
  • Z' couplings g_q and g_qD = g_q = 0.01, g_qD = 0.1
    Benchmark couplings used for the quoted Z' exclusion; cross-section and limits scale with these values.
  • Phi coupling kappa_1j = kappa_1j = 0.1
    Benchmark for the t-channel model, chosen per Ref [37]; used for the quoted Phi exclusion.
  • Dark pion proper decay length c_tau_piD = 5-50 mm for quoted limits; samples generated at 1-1000 mm
    The quoted exclusions are conditional on this lifetime range, as stated in the abstract and Section 8.
assumptions (5)
  • domain assumption A dark sector with a confining SU(N_c) gauge group and N_f dark quark flavours exists and couples to the Standard Model via a mediator.
    Motivated by Refs [19-24] and previously searched by ATLAS and CMS; not independently verified.
  • domain assumption Dark pions are long-lived and decay back to Standard Model quarks with proper decay lengths in the 1-1000 mm range.
    Core of the emerging jet signature, following Ref [26]; the quoted exclusions assume 5-50 mm.
  • domain assumption The QCD multijet background is the dominant background and can be modelled data-driven via the ABCD or mistag-rate methods.
    Validated with closure tests in Sections 6.1 and 6.2; requires small correlations between the ABCD variables, which is tested in control regions.
  • standard math Monte Carlo generators (Pythia, MadGraph, Powheg, Sherpa) accurately model signal and control signatures.
    Standard high-energy physics practice, used for signal acceptance and background validation, with systematic variations applied.
  • domain assumption The GN2-derived transformer tagger trained on simulated multijet and signal samples generalizes to data.
    Validated with the VR tag selection (Table 7) and a qualitative comparison of p_EJ distributions in data and MC (Figure 6).

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Pith. "Pith review of Search for emerging jets in $pp$ collisions at $\sqrt{s} = 13.6$ TeV with the ATLAS experiment." pith.science (2026). https://pith.science/paper/VHD3MX5W

@misc{pith2026250502429,
  author       = {Pith},
  title        = {Pith review of: Search for emerging jets in $pp$ collisions at $\sqrts = 13.6$ TeV with the ATLAS experiment},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/VHD3MX5W}},
  note         = {Machine review of arXiv:2505.02429}
}
abstract

A search for emerging jets is presented using 51.8 fb$^{-1}$ of proton-proton collision data at $\sqrt{s} = 13.6$ TeV, collected by the ATLAS experiment during 2022 and 2023. The search explores a hypothetical dark sector featuring 'dark quarks', which are charged under a confining gauge group and couple to the Standard Model via a new mediator particle. These dark quarks undergo showering and hadronization within the dark sector, forming long-lived dark mesons that decay back into Standard Model particles. This results in jets which contain multiple displaced vertices known as emerging jets. The analysis targets events with pairs of emerging jets, produced either through a vector mediator, $Z'$, in the $s$-channel, or a scalar mediator, $\Phi$, in the $t$-channel. No significant excess over the Standard Model background is observed. Assuming a dark pion proper decay length between 5 and 50 mm, $Z'$ mediator masses between 600 and 2550 GeV are excluded for quark and dark quark coupling values of 0.01 and 0.1, respectively. For a quark-dark quark coupling of $0.1$, $\Phi$ mediator masses between 600 and 1375 GeV are excluded. These results provide the first direct constraints on emerging jet pair production via a $Z'$ mediator, and represent the first search to investigate emerging jet production via $t$-channel exchange of a scalar mediator.

Figures

Figures reproduced from arXiv: 2505.02429 by the authors.

Figure 2
Figure 2. Feynman diagrams for @⇡@¯⇡ production with up to two additional SM jets via a scalar ￾. regions based on the invariant mass of the two leading jets (< 99), each with distinct trigger strategies. The low-< 99 region (< 99 < 1 TeV) utilises a dedicated jet trigger, introduced for Run 3, specifically designed to select emerging jets. The high-< 99 region (< 99 > 1 TeV) relies on a standard single-jet trigger. Combining… view at source ↗

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Forward citations

Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Search for resonant production of lepton-enriched semivisible jets in proton-proton collisions at $\sqrt{s}$ = 13 TeV

    hep-ex 2026-08 conditional novelty 7.0 of 10

    A CMS search with 138 fb^-1 of 13 TeV data finds no lepton-enriched semivisible jet resonance and excludes Z' masses up to 4.7 TeV (SVJ l) and 1.8-3.5 TeV (SVJ tau) at 95% CL.

  2. Search for emerging jets in $pp$ collisions at $\sqrt{s} = 13$ TeV with the ATLAS experiment

    hep-ex 2025-10 accept novelty 5.0 of 10

    No excess of emerging-jet events appears in ATLAS Run 2 data, excluding pair-produced dark scalar mediators up to about 2 TeV for 20 GeV dark pions with 20 mm decay length.

Reference graph

Works this paper leans on

107 extracted references · 2 canonical work pages · cited by 2 Pith papers

  1. [26]

    Schwaller, D

    P. Schwaller, D. Stolarski and A. Weiler,Emerging jets, JHEP05(2015) 059, arXiv: 1502.05409 [hep-ph]

  2. [1]

    V. C. Rubin, W. K. Ford Jr. and N. Thonnard,Rotational properties of 21 SC galaxies with a large range of luminosities and radii, from NGC 4605 (𝑅= 4 kpc) to UGC 2885 (𝑅= 122kpc), The Astrophysical Journal238 (1980) 471

  3. [2]

    Persic, P

    M. Persic, P. Salucci and F. Stel, The Universal rotation curve of spiral galaxies — I. The Dark matter connection, Monthly Notices of the Royal Astronomical Society281 (1996) 27, arXiv:astro-ph/9506004

  4. [3]

    Clowe et al.,A Direct Empirical Proof of the Existence of Dark Matter, The Astrophysical Journal648 (2006) L109, arXiv:astro-ph/0608407

    D. Clowe et al.,A Direct Empirical Proof of the Existence of Dark Matter, The Astrophysical Journal648 (2006) L109, arXiv:astro-ph/0608407

  5. [4]

    Jungman, M

    G. Jungman, M. Kamionkowski and K. Griest,Supersymmetric dark matter, Phys. Rept.267 (1996) 195, arXiv:hep-ph/9506380

  6. [5]

    Steigman, B

    G. Steigman, B. Dasgupta and J. F. Beacom, Precise relic WIMP abundance and its impact on searches for dark matter annihilation, Phys. Rev. D86(2012) 023506, arXiv:1204.3622 [hep-ph]

  7. [6]

    PandaX-II Collaboration, Dark Matter Results from 54-Ton-Day Exposure of PandaX-II Experiment, Phys. Rev. Lett.119 (2017) 181302, arXiv:1708.06917 [astro-ph.CO]

  8. [7]

    PICO Collaboration, Dark matter search results from the complete exposure of the PICO-60C3F8 bubble chamber, Phys. Rev. D100 (2019) 022001, arXiv:1902.04031 [astro-ph.CO]

Show all 107 references
  1. [8]

    DarkSide Collaboration, DarkSide-50 532-day dark matter search with low-radioactivity argon, Phys. Rev. D98(2018) 102006, arXiv:1802.07198 [astro-ph.CO]

  2. [9]

    CRESST Collaboration, First results from the CRESST-III low-mass dark matter program, Phys. Rev. D100 (2019) 102002, arXiv:1904.00498 [astro-ph.CO]

  3. [10]

    DarkSide Collaboration, Low-Mass Dark Matter Search with the DarkSide-50 Experiment, Phys. Rev. Lett.121 (2018) 081307, arXiv:1802.06994 [astro-ph.HE]

  4. [11]

    LUX Collaboration, Results from a Search for Dark Matter in the Complete LUX Exposure, Phys. Rev. Lett.118 (2017) 021303, arXiv:1608.07648 [astro-ph.CO]

  5. [12]

    XENON Collaboration, Search for Coherent Elastic Scattering of Solar8B Neutrinos in the XENON1T Dark Matter Experiment, Phys. Rev. Lett.126 (2021) 091301, arXiv: 2012.02846 [hep-ex]

  6. [13]

    Lai (on behalf of DEAP-3600 Collaboration),Recent results from DEAP-3600, JINST 18(2023) C02046, arXiv:2302.14484 [hep-ex]

    M. Lai (on behalf of DEAP-3600 Collaboration),Recent results from DEAP-3600, JINST 18(2023) C02046, arXiv:2302.14484 [hep-ex]

  7. [14]

    SuperCDMS Collaboration, Search for low-mass dark matter with CDMSlite using a profile likelihood fit, Phys. Rev. D99(2019) 062001, arXiv:1808.09098 [astro-ph.CO]

  8. [15]

    Fermi-LAT Collaboration, Searching for Dark Matter Annihilation from Milky Way Dwarf Spheroidal Galaxies with Six Years of Fermi Large Area Telescope Data, Phys. Rev. Lett.115 (2015) 231301, arXiv:1503.02641 [astro-ph.HE]

  9. [16]

    Collaboration, Search for Dark Matter Annihilation Signals in the H.E.S.S

    H.E.S.S. Collaboration, Search for Dark Matter Annihilation Signals in the H.E.S.S. Inner Galaxy Survey, Phys. Rev. Lett.129 (2022) 111101, arXiv:2207.10471 [astro-ph.HE]. 29

  10. [17]

    ATLAS Collaboration, Search for new phenomena in events with an energetic jet and missing transverse momentum in𝑝𝑝 collisions at√𝑠= 13TeV with the ATLAS detector, Phys. Rev. D103 (2021) 112006, arXiv:2102.10874 [hep-ex]

  11. [18]

    CMS Collaboration, Search for new particles in events with energetic jets and large missing transverse momentum in proton–proton collisions at√𝑠= 13TeV, JHEP11(2021) 153, arXiv: 2107.13021 [hep-ex]

  12. [19]

    M. J. Strassler and K. M. Zurek,Echoes of a hidden valley at hadron colliders, Phys. Lett. B651(2007) 374, arXiv:hep-ph/0604261

  13. [20]

    M. J. Strassler and K. M. Zurek,Discovering the Higgs through highly-displaced vertices, Phys. Lett. B661(2008) 263, arXiv:hep-ph/0605193

  14. [21]

    T. Han, Z. Si, K. M. Zurek and M. J. Strassler, Phenomenology of hidden valleys at hadron colliders, JHEP07(2008) 008, arXiv: 0712.2041 [hep-ph]

  15. [22]

    Bai and P

    Y. Bai and P. Schwaller,Scale of dark QCD, Phys. Rev. D89 (2014) 063522, arXiv: 1306.4676 [hep-ph]

  16. [23]

    Beauchesne, E

    H. Beauchesne, E. Bertuzzo and G. Grilli di Cortona, Dark matter in Hidden Valley models with stable and unstable light dark mesons, JHEP 04(2019) 118, arXiv:1809.10152 [hep-ph]

  17. [24]

    Albouy et al., Theory, phenomenology, and experimental avenues for dark showers: a Snowmass 2021 report, Eur

    G. Albouy et al., Theory, phenomenology, and experimental avenues for dark showers: a Snowmass 2021 report, Eur. Phys. J. C82 (2022) 1132, arXiv:2203.09503 [hep-ph]

  18. [25]

    Cohen, M

    T. Cohen, M. Lisanti and H. K. Lou,Semivisible Jets: Dark Matter Undercover at the LHC, Phys. Rev. Lett.115 (2015) 171804, arXiv:1503.00009 [hep-ph]

  19. [27]

    ATLAS Collaboration, Search for resonant production of dark quarks in the dijet final state with the ATLAS detector, JHEP 02(2024) 128, arXiv:2311.03944 [hep-ex]

  20. [28]

    CMS Collaboration, Search for resonant production of strongly coupled dark matter in proton–proton collisions at13TeV, JHEP06 (2022) 156, arXiv:2112.11125 [hep-ex]

  21. [29]

    ATLAS Collaboration, Search for new physics in final states with semi-visible jets or anomalous signatures using the ATLAS detector, (2025), arXiv:2505.01634 [hep-ex]

  22. [30]

    ATLAS Collaboration, Search for non-resonant production of semi-visible jets using Run 2 data in ATLAS, Phys. Lett. B848 (2024) 138324, arXiv:2305.18037 [hep-ex]

  23. [31]

    ATLAS Collaboration,Search for long-lived, weakly interacting particles that decay to displaced hadronic jets in proton–proton collisions at√𝑠= 8TeV with the ATLAS detector, Phys. Rev. D92(2015) 012010, arXiv:1504.03634 [hep-ex]

  24. [32]

    CMS Collaboration, Search for new particles decaying to a jet and an emerging jet, JHEP 02 (2019) 179, arXiv:1810.10069 [hep-ex]. 30

  25. [33]

    CMS Collaboration, Search for dark QCD with emerging jets in proton–proton collisions at√𝑠= 13TeV, JHEP 07 (2024) 142, arXiv:2403.01556 [hep-ex]

  26. [34]

    Englert, M

    C. Englert, M. McCullough and M. Spannowsky, S-Channel Dark Matter Simplified Models and Unitarity, Phys. Dark Univ.14(2016) 48, arXiv: 1604.07975 [hep-ph]

  27. [35]

    Bernreuther, F

    E. Bernreuther, F. Kahlhoefer, M. Krämer and P. Tunney, Strongly interacting dark sectors in the early Universe and at the LHC through a simplified portal, JHEP 01 (2020) 162, arXiv:1907.04346 [hep-ph]

  28. [36]

    Cheng, L

    H.-C. Cheng, L. Li, E. Salvioni and C. B. Verhaaren,Light Hidden Mesons through the Z Portal, JHEP 11 (2019) 031, arXiv:1906.02198 [hep-ph]

  29. [37]

    Carmona, F

    A. Carmona, F. Elahi, C. Scherb and P. Schwaller,Dark showers from sneaky dark matter, (2025), arXiv: 2411.15073 [hep-ph]

  30. [38]

    ATLAS Collaboration, The ATLAS Experiment at the CERN Large Hadron Collider, JINST 3 (2008) S08003

  31. [39]

    ATLAS Collaboration,The ATLAS experiment at the CERN Large Hadron Collider: a description of the detector configuration for Run 3, JINST19(2024) P05063, arXiv: 2305.16623 [physics.ins-det]

  32. [40]

    ATLAS Collaboration, ATLAS Insertable B-Layer: Technical Design Report, ATLAS-TDR-19; CERN-LHCC-2010-013, 2010, url: https://cds.cern.ch/record/1291633, Addendum: ATLAS-TDR-19-ADD-1; CERN-LHCC-2012-009, 2012,url: https://cds.cern.ch/record/1451888

  33. [41]

    Abbott et al.,Production and integration of the ATLAS Insertable B-Layer, JINST 13(2018) T05008, arXiv:1803.00844 [physics.ins-det]

    B. Abbott et al.,Production and integration of the ATLAS Insertable B-Layer, JINST 13(2018) T05008, arXiv:1803.00844 [physics.ins-det]

  34. [42]

    Avoni et al.,The new LUCID-2 detector for luminosity measurement and monitoring in ATLAS, JINST 13(2018) P07017

    G. Avoni et al.,The new LUCID-2 detector for luminosity measurement and monitoring in ATLAS, JINST 13(2018) P07017

  35. [43]

    ATLAS Collaboration,The ATLAS trigger system for LHC Run 3 and trigger performance in 2022, JINST 19(2024) P06029, arXiv:2401.06630 [hep-ex]

  36. [44]

    ATLAS Collaboration, Software and computing for Run 3 of the ATLAS experiment at the LHC, Eur. Phys. J. C85 (2025) 234, arXiv:2404.06335 [hep-ex]

  37. [45]

    ATLAS Collaboration, ATLAS data quality operations and performance for 2015–2018 data-taking, JINST 15(2020) P04003, arXiv:1911.04632 [physics.ins-det]

  38. [46]

    ATLAS Collaboration, Emulating the impact of additional proton–proton interactions in the ATLAS simulation by presampling sets of inelastic Monte Carlo events, Comput. Softw. Big Sci.6(2022) 3, arXiv:2102.09495 [hep-ex]

  39. [47]

    Werner, F.-M

    K. Werner, F.-M. Liu and T. Pierog, Parton ladder splitting and the rapidity dependence of transverse momentum spectra in deuteron-gold collisions at the BNL Relativistic Heavy Ion Collider, Phys. Rev. C74(2006) 044902, arXiv:hep-ph/0506232 [hep-ph]

  40. [48]

    Bierlich et al.,A comprehensive guide to the physics and usage of PYTHIA 8.3, SciPost Phys

    C. Bierlich et al.,A comprehensive guide to the physics and usage of PYTHIA 8.3, SciPost Phys. Codeb. (2022) 8, arXiv:2203.11601 [hep-ph]. 31

  41. [49]

    Agostinelli et al.,Geant4 – a simulation toolkit, Nucl

    S. Agostinelli et al.,Geant4 – a simulation toolkit, Nucl. Instrum. Meth. A506 (2003) 250

  42. [50]

    ATLAS Collaboration, The ATLAS Simulation Infrastructure, Eur. Phys. J. C70 (2010) 823, arXiv: 1005.4568 [physics.ins-det]

  43. [51]

    Abercrombie et al.,Dark Matter benchmark models for early LHC Run-2 Searches: Report of the ATLAS/CMS Dark Matter Forum, Physics of the Dark Universe27(2020) 100371, ed

    D. Abercrombie et al.,Dark Matter benchmark models for early LHC Run-2 Searches: Report of the ATLAS/CMS Dark Matter Forum, Physics of the Dark Universe27(2020) 100371, ed. by A. Boveia, C. Doglioni, S. Lowette, S. Malik and S. Mrenna, arXiv:1507.00966 [hep-ex]

  44. [52]

    J. Alwall et al.,The automated computation of tree-level and next-to-leading order differential cross sections, and their matching to parton shower simulations, JHEP07 (2014) 079, arXiv: 1405.0301 [hep-ph]

  45. [53]

    M. L. Mangano, M. Moretti, F. Piccinini and M. Treccani, Matching matrix elements and shower evolution for top-pair production in hadronic collisions, JHEP 01(2007) 013, arXiv:hep-ph/0611129

  46. [54]

    NNPDF Collaboration, R. D. Ball et al.,Parton distributions with LHC data, Nucl. Phys. B867(2013) 244, arXiv:1207.1303 [hep-ph]

  47. [55]

    ATLAS Collaboration, ATLAS Pythia 8 tunes to7 TeV data, ATL-PHYS-PUB-2014-021, 2014, url: https://cds.cern.ch/record/1966419

  48. [56]

    Carloni and T

    L. Carloni and T. Sjöstrand,Visible effects of invisible hidden valley radiation, JHEP 09(2010) 105, arXiv:1006.2911 [hep-ph]

  49. [57]

    Carloni, J

    L. Carloni, J. Rathsman and T. Sjöstrand,Discerning secluded sector gauge structures, JHEP 04(2011) 091, arXiv:1102.3795 [hep-ph]

  50. [58]

    Sjöstrand et al.,An introduction to PYTHIA 8.2, Comput

    T. Sjöstrand et al.,An introduction to PYTHIA 8.2, Comput. Phys. Commun.191 (2015) 159, arXiv: 1410.3012 [hep-ph]

  51. [59]

    Frixione, G

    S. Frixione, G. Ridolfi and P. Nason, A positive-weight next-to-leading-order Monte Carlo for heavy flavour hadroproduction, JHEP 09(2007) 126, arXiv:0707.3088 [hep-ph]

  52. [60]

    Nason, A new method for combining NLO QCD with shower Monte Carlo algorithms, JHEP 11(2004) 040, arXiv:hep-ph/0409146

    P. Nason, A new method for combining NLO QCD with shower Monte Carlo algorithms, JHEP 11(2004) 040, arXiv:hep-ph/0409146

  53. [61]

    Frixione, P

    S. Frixione, P. Nason and C. Oleari, Matching NLO QCD computations with parton shower simulations: the POWHEG method, JHEP 11(2007) 070, arXiv:0709.2092 [hep-ph]

  54. [62]

    Alioli, P

    S. Alioli, P. Nason, C. Oleari and E. Re,A general framework for implementing NLO calculations in shower Monte Carlo programs: the POWHEG BOX, JHEP06 (2010) 043, arXiv: 1002.2581 [hep-ph]

  55. [63]

    NNPDF Collaboration, R. D. Ball et al.,Parton distributions for the LHC run II, JHEP 04 (2015) 040, arXiv:1410.8849 [hep-ph]

  56. [64]

    ATLAS Collaboration, Studies on top-quark Monte Carlo modelling for Top2016, ATL-PHYS-PUB-2016-020, 2016,url: https://cds.cern.ch/record/2216168

  57. [65]

    D. J. Lange,The EvtGen particle decay simulation package, Nucl. Instrum. Meth. A462 (2001) 152

  58. [66]

    Bothmann et al.,Event generation with Sherpa 2.2, SciPost Phys.7 (2019) 034, arXiv: 1905.09127 [hep-ph]

    E. Bothmann et al.,Event generation with Sherpa 2.2, SciPost Phys.7 (2019) 034, arXiv: 1905.09127 [hep-ph]. 32

  59. [67]

    Gleisberg and S

    T. Gleisberg and S. Höche,Comix, a new matrix element generator, JHEP12(2008) 039, arXiv: 0808.3674 [hep-ph]

  60. [68]

    Buccioni et al.,OpenLoops 2, Eur

    F. Buccioni et al.,OpenLoops 2, Eur. Phys. J. C79(2019) 866, arXiv:1907.13071 [hep-ph]

  61. [69]

    Cascioli, P

    F. Cascioli, P. Maierhöfer and S. Pozzorini,Scattering Amplitudes with Open Loops, Phys. Rev. Lett.108 (2012) 111601, arXiv:1111.5206 [hep-ph]

  62. [70]

    Denner, S

    A. Denner, S. Dittmaier and L. Hofer, Collier: A fortran-based complex one-loop library in extended regularizations, Comput. Phys. Commun.212 (2017) 220, arXiv:1604.06792 [hep-ph]

  63. [71]

    Schumann and F

    S. Schumann and F. Krauss, A parton shower algorithm based on Catani–Seymour dipole factorisation, JHEP03(2008) 038, arXiv: 0709.1027 [hep-ph]

  64. [72]

    Höche, F

    S. Höche, F. Krauss, M. Schönherr and F. Siegert, A critical appraisal of NLO+PS matching methods, JHEP09(2012) 049, arXiv: 1111.1220 [hep-ph]

  65. [73]

    Höche, F

    S. Höche, F. Krauss, M. Schönherr and F. Siegert, QCD matrix elements + parton showers. The NLO case, JHEP04(2013) 027, arXiv: 1207.5030 [hep-ph]

  66. [74]

    Catani, F

    S. Catani, F. Krauss, B. R. Webber and R. Kuhn,QCD Matrix Elements + Parton Showers, JHEP 11(2002) 063, arXiv:hep-ph/0109231

  67. [75]

    Höche, F

    S. Höche, F. Krauss, S. Schumann and F. Siegert,QCD matrix elements and truncated showers, JHEP 05(2009) 053, arXiv:0903.1219 [hep-ph]

  68. [76]

    Anastasiou, L

    C. Anastasiou, L. Dixon, K. Melnikov and F. Petriello,High-precision QCD at hadron colliders: Electroweak gauge boson rapidity distributions at next-to-next-to leading order, Phys. Rev. D69(2004) 094008, arXiv:hep-ph/0312266

  69. [77]

    Frühwirth, Application of Kalman filtering to track and vertex fitting, Nucl

    R. Frühwirth, Application of Kalman filtering to track and vertex fitting, Nucl. Instrum. Meth. A262 (1987) 444

  70. [78]

    ATLAS Collaboration, Performance of the reconstruction of large impact parameter tracks in the inner detector of ATLAS, Eur. Phys. J. C83 (2023) 1081, arXiv:2304.12867 [hep-ex]

  71. [79]

    Cacciari, G

    M. Cacciari, G. P. Salam and G. Soyez,The anti-𝑘𝑡 jet clustering algorithm, JHEP04 (2008) 063, arXiv: 0802.1189 [hep-ph]

  72. [80]

    Cacciari, G

    M. Cacciari, G. P. Salam and G. Soyez,FastJet user manual, Eur. Phys. J. C72(2012) 1896, arXiv: 1111.6097 [hep-ph]

  73. [81]

    ATLAS Collaboration, Jet reconstruction and performance using particle flow with the ATLAS Detector, Eur. Phys. J. C77 (2017) 466, arXiv:1703.10485 [hep-ex]

  74. [82]

    ATLAS Collaboration, Topological cell clustering in the ATLAS calorimeters and its performance in LHC Run 1, Eur. Phys. J. C77 (2017) 490, arXiv:1603.02934 [hep-ex]

  75. [83]

    ATLAS Collaboration, Jet energy scale and resolution measured in proton–proton collisions at√𝑠= 13TeV with the ATLAS detector, Eur. Phys. J. C81(2021) 689, arXiv: 2007.02645 [hep-ex]. 33

  76. [84]

    ATLAS Collaboration,ATLAS flavour-tagging algorithms for the LHC Run 2𝑝𝑝 collision dataset, Eur. Phys. J. C83 (2023) 681, arXiv:2211.16345 [physics.data-an]

  77. [85]

    Cacciari, G

    M. Cacciari, G. P. Salam and G. Soyez,The catchment area of jets, JHEP04 (2008) 005, arXiv: 0802.1188 [hep-ph]

  78. [86]

    ATLAS Collaboration,Electron and photon performance measurements with the ATLAS detector using the 2015–2017 LHC proton–proton collision data, JINST14 (2019) P12006, arXiv: 1908.00005 [hep-ex]

  79. [87]

    ATLAS Collaboration, Development of ATLAS Primary Vertex Reconstruction for LHC Run 3, ATL-PHYS-PUB-2019-015, 2019,url: https://cds.cern.ch/record/2670380

  80. [88]

    ATLAS Collaboration, The performance of the jet trigger for the ATLAS detector during 2011 data taking, Eur. Phys. J. C76(2016) 526, arXiv:1606.07759 [hep-ex]

  81. [89]

    ATLAS Collaboration, Performance of the upgraded PreProcessor of the ATLAS Level-1 Calorimeter Trigger, JINST 15(2020) P11016, arXiv:2005.04179 [physics.ins-det]

  82. [90]

    ATLAS Collaboration, Performance of vertex reconstruction algorithms for detection of new long-lived particle decays within the ATLAS inner detector, ATL-PHYS-PUB-2019-013, 2019, url: https://cds.cern.ch/record/2669425

  83. [91]

    ATLAS Collaboration, Search for long-lived, massive particles in events with displaced vertices and multiple jets in𝑝𝑝 collisions at√𝑠= 13TeV with the ATLAS detector, JHEP06 (2023) 200, arXiv: 2301.13866 [hep-ex]

  84. [92]

    A. J. Larkoski, G. P. Salam and J. Thaler,Energy correlation functions for jet substructure, JHEP 06 (2013) 108, arXiv:1305.0007 [hep-ph]

  85. [93]

    ATLAS Collaboration, Transforming jet flavour tagging at ATLAS, (2025), arXiv: 2505.19689 [hep-ex]

  86. [94]

    Y. Li, D. Tarlow, M. Brockschmidt and R. Zemel,Gated Graph Sequence Neural Networks, 2017, arXiv: 1511.05493 [cs.LG]

  87. [95]

    A. F. Agarap,Deep Learning using Rectified Linear Units (ReLU), (2019), arXiv: 1803.08375 [cs.NE]

  88. [96]

    D. C. Kozen, ‘Union-Find’,The Design and Analysis of Algorithms, New York, NY: Springer New York, 1992 48,isbn: 978-1-4612-4400-4

  89. [97]

    ATLAS Collaboration, Study of the material of the ATLAS inner detector for Run 2 of the LHC, JINST 12(2017) P12009, arXiv:1707.02826 [hep-ex]

  90. [98]

    ATLAS Collaboration,Measurement of the Inelastic Proton–Proton Cross Section at√𝑠= 13TeV with the ATLAS Detector at the LHC, Phys. Rev. Lett.117(2016) 182002, arXiv: 1606.02625 [hep-ex]

  91. [99]

    Butterworth et al.,PDF4LHC recommendations for LHC Run II, J

    J. Butterworth et al.,PDF4LHC recommendations for LHC Run II, J. Phys. G43(2016) 023001, arXiv: 1510.03865 [hep-ph]

  92. [100]

    Mrenna and P

    S. Mrenna and P. Skands,Automated parton-shower variations in PYTHIA 8, Phys. Rev. D94(2016) 074005, arXiv:1605.08352 [hep-ph]

  93. [101]

    A. L. Read,Presentation of search results: the𝐶𝐿𝑠 technique, J. Phys. G28(2002) 2693. 34

  94. [102]

    Cowan, K

    G. Cowan, K. Cranmer, E. Gross and O. Vitells, Asymptotic formulae for likelihood-based tests of new physics, Eur. Phys. J. C71(2011) 1554, arXiv: 1007.1727 [physics.data-an], Erratum: Eur. Phys. J. C73 (2013) 2501

  95. [103]

    Heinrich, M

    L. Heinrich, M. Feickert and G. Stark,scikit-hep/pyhf: v0.7.6, version 0.7.6, https://github.com/scikit-hep/pyhf/releases/tag/v0.7.6

  96. [104]

    Heinrich, M

    L. Heinrich, M. Feickert, G. Stark and K. Cranmer, pyhf: pure-Python implementation of HistFactory statistical models, Journal of Open Source Software6(2021) 2823

  97. [105]

    ATLAS Collaboration,Search for new resonances in mass distributions of jet pairs using139fb−1 of𝑝𝑝 collisions at√𝑠= 13TeV with the ATLAS detector, JHEP03(2020) 145, arXiv: 1910.08447 [hep-ex]

  98. [106]

    ATLAS Collaboration, Constraints on dark matter models involving an𝑠-channel mediator with the ATLAS detector in𝑝𝑝 collisions at√𝑠= 13TeV, Eur. Phys. J. C84(2024) 1102, arXiv: 2404.15930 [hep-ex]

  99. [107]

    Demokritos

    ATLAS Collaboration,ATLAS Computing Acknowledgements, ATL-SOFT-PUB-2025-001, 2025, url: https://cds.cern.ch/record/2922210. 35 The ATLAS Collaboration G. Aad 104, E. Aakvaag 17, B. Abbott 123, S. Abdelhameed 119a, K. Abeling 55, N.J. Abicht 49, S.H. Abidi 30, M. Aboelela 45, A...

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