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Heavy neutrino mixing prospects at hadron colliders: a machine learning study

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Pith's one-line read XGBoost applied to simulated same-sign and opposite-sign dilepton events from WR decays in the inverse seesaw left-right model gives projected heavy neutrino mass reaches up to 17.1 and 19.5 TeV at a 100 TeV collider.

arxiv 2504.12141 v1 pith:VDXSPXRM submitted 2025-04-16 hep-ph

Si-Yu Chen , Yu-Peng Jiao , Shi-Yu Wang , Qi-Shu Yan , Hong-Hao Zhang , Yongchao Zhang This is my paper · ORCID
classification hep-ph
keywords heavymixinglearningmachineneutrinoneutrinosalphachannels
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

The paper studies a hypothetical extension of the Standard Model called the inverse seesaw left-right symmetric model. In this model, there are heavy right-handed gauge bosons (WR) and heavy neutrino partners (N1 and N2). When two protons collide, a WR can be produced and decay into a charged lepton and a heavy neutrino; the neutrino then decays into another lepton and two jets. The final state has two leptons and two jets, and the leptons can have the same electric charge (same-sign, SS) or opposite charges (opposite-sign, OS). The same-sign case would be a clear sign of lepton-number violation, a process forbidden in the Standard Model.

The authors simulate these events at three future collider energies (14, 27, and 100 TeV) including detector effects, and train a machine learning algorithm (XGBoost) to separate the signal from Standard Model backgrounds. They find that XGBoost can suppress backgrounds very strongly while keeping most signal events. From the classification scores, they compute the collider's sensitivity to the heavy neutrino mass and to the mixing angle between the two heavy neutrino states.

The headline numbers are that at a 100 TeV collider, the OS and SS channels could probe neutrino masses up to 17.1 and 19.5 TeV, respectively, and mixing angles up to the maximal value in the OS channel. However, these numbers hold under specific benchmark assumptions: a fixed WR mass of 20 TeV, a tiny mass splitting between the two neutrinos, and no systematic uncertainties.

Extended reading notes

Core claim

The paper's central claim is that at a 100 TeV proton-proton collider with 30 ab^-1, the OS and SS dilepton channels of the Keung-Senjanovic process can probe the inverse-seesaw heavy neutrino mass up to 17.1 TeV and 19.5 TeV, respectively, at 95% C.L., under the benchmark assumptions m_WR = 20 TeV, a tiny mass splitting, and maximal allowed mixing angle. Quote from the abstract: 'the heavy neutrinos can be probed up to 17.1 TeV and 19.5 TeV in the OS and SS channels, respectively.'

Load-bearing premise

The analysis treats the two heavy neutrino mass eigenstates as nearly degenerate, setting the mass splitting to Δm = 10^-7 GeV in the simulations (Sec 3.2, Fig. 4 caption) so that the interference term in Eq (2.15) controls the OS/SS ratio. If the physical mass splitting is much larger, the interference decoheres, R_ℓℓ approaches 1, and the predicted sensitivity to the mixing angle s_α (especially the SS-channel suppression at large α) no longer holds. The conclusion itself admits this: 'these conclusions in this paper are valid only under conditions in which interference of heavy neutrino states occurs.'

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

The central projections rest on explicit benchmark choices and simplifying assumptions rather than on data fits: m_WR fixed per collider (6.5/9/20 TeV), a tiny mass splitting Δm = 10^-7 GeV to ensure coherence, g_R = g_L, V_R^CKM = I, and a simplified significance formula without systematics. The ML thresholds are tuned on simulated test data. The headlined reach numbers are therefore conditional projections, not unconditional discovery potentials.

free parameters (5)
  • m_WR (right-handed W boson mass) = 6.5 TeV (14 TeV), 9 TeV (27 TeV), 20 TeV (100 TeV)
    Benchmark values chosen per collider (Table 1). The mass reach results are conditional on these choices; they are not scanned.
  • Δm (heavy neutrino mass splitting) = 10^-7 GeV
    Assumed tiny to activate the interference regime (Sec 3.2). The OS/SS ratio and mixing-angle sensitivity depend strongly on this value.
  • θ (lepton flavor mixing angle) = π/4
    Set to π/4 so that couplings to e and μ are equal (Sec 2.4). Sensitivities for ee, μμ, eμ channels scale with c_θ^4, s_θ^4, s_θ^2 c_θ^2.
  • g_R/g_L ratio = 1
    Assumed equal gauge couplings (Sec 2.3). Signal cross sections scale with g_R^4.
  • ML thresholds and hyperparameters (max_depth, n_estimators) = see Table 5 and Table 6
    Selected by grid search on the test set (Sec 4.1). The quoted significances are evaluated at these optimized thresholds, so they are part of the analysis procedure.
assumptions (5)
  • domain assumption The right-handed gauge coupling equals the left-handed one, g_R = g_L.
    Used in cross section calculations and when quoting LHC limits (Sec 2.3).
  • domain assumption The right-handed CKM matrix is the identity matrix.
    Adopted in Sec 3.1 for V_R^CKM; the authors call it a good approximation.
  • domain assumption No W-W_R mixing and no heavy-light neutrino mixing.
    Assumed in Sec 2.3 and 3.1, reducing the couplings to the simple KS process.
  • domain assumption The OS/SS ratio formula in Eq (2.15), taken from Refs [21,22], correctly describes the interference of two nearly degenerate heavy neutrinos.
    Central to the predicted dependence on s_α; borrowed from the literature, not re-derived here.
  • ad hoc to paper The significance formula Z = N_S/sqrt(N_S+N_B) with Z=2 approximates 95% C.L., and systematic uncertainties can be neglected.
    Used in Sec 4.2 to define the sensitivity regions; a simplified statistical treatment.

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Cite this review

Pith. "Pith review of Heavy neutrino mixing prospects at hadron colliders: a machine learning study." pith.science (2026). https://pith.science/paper/VDXSPXRM

@misc{pith2026250412141,
  author       = {Pith},
  title        = {Pith review of: Heavy neutrino mixing prospects at hadron colliders: a machine learning study},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/VDXSPXRM}},
  note         = {Machine review of arXiv:2504.12141}
}
abstract

We apply machine learning to the searches of heavy neutrino mixing in the inverse seesaw in the framework of left-right symmetric model at the high-energy hadron colliders. The Majorana nature of heavy neutrinos can induce the processes $pp \to W_R^\pm \to \ell_\alpha^\pm N \to \ell_\alpha^\pm \ell_\beta^{\mp,\,\pm} jj$, with opposite-sign (OS) and same-sign (SS) dilepton and two jets in the final state. The distributions of the charged leptons $\ell = e ,\, \mu$ and jets and their correlations are utilized as input for machine learning analysis. It is found that for both the OS and SS processes, XGBoost can efficiently distinguish signals from the standard model backgrounds. We estimate the sensitivities of heavy neutrino mass $m_N$ and their mixing in the OS and SS $ee$, $\mu\mu$ and $e\mu$ final states at $\sqrt{s} = 14$ TeV, 27 TeV and 100 TeV. It turns out that the heavy neutrinos can be probed up to 17.1 TeV and 19.5 TeV in the OS and SS channels, respectively. The sine of the mixing angle of heavy neutrinos can be probed up to the maximal value of $\sqrt2/2$ and 0.69 in the OS and SS channels, respectively.

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