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REVIEW 3 major objections 4 minor 77 references

A search for long-lived particles in compressed supersymmetry excludes top squarks to 1100 GeV and wino-like neutralinos to 550 GeV.

Reviewed by Pith at T0; open to challenge. T0 means a machine referee read the full paper against a public rubric. the ladder, T0–T4 →

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T0 review · deepseek-v4-flash

2026-08-03 22:54 UTC pith:3FMQJEG5

load-bearing objection New compressed LLP exclusion from CMS using low-pT displaced tracks; solid analysis, but the alpha_p optimization wording must be clarified before the limits are fully credible. the 3 major comments →

arxiv 2511.08212 v2 pith:3FMQJEG5 submitted 2025-11-11 hep-ex

Search for long-lived particles using displaced vertices with low-momentum tracks in proton-proton collisions at sqrt{s} = 13 TeV

CMS Collaboration This is my paper
classification hep-ex
keywords long-lived particlesdisplaced verticeslow-momentum trackstop squarkwino-like neutralinocompressed supersymmetrymissing transverse momentumtransfer factor method
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved

The pith

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

This paper reports a search for long-lived particles that decay inside the detector to a displaced vertex with low-momentum tracks, accompanied by large missing transverse momentum and an initial-state radiation jet. The analysis targets supersymmetric coannihilation scenarios where the mass difference between the long-lived particle and the invisible lightest particle is only 12–25 GeV, a region previous searches had difficulty reaching. Using 100 fb−1 of 13 TeV proton-proton collision data, the observed event yields agree with a data-driven background prediction, and the search excludes top squarks with masses below 400–1100 GeV and wino-like neutralinos below 220–550 GeV, depending on model parameters. The paper also introduces a transfer-factor method that predicts backgrounds in multiple signal regions purely from data, and reports the most stringent limits to date for these two models.

Core claim

The paper's central claim is that long-lived particles with small mass splittings can be efficiently detected by reconstructing displaced vertices from tracks with transverse momentum as low as 0.5 GeV, even when the decay products are soft. In the top squark NLSP model, the search excludes top squark masses less than 400–1100 GeV, and for the bino-wino NLSP model it excludes wino-like neutralino masses less than 220–550 GeV, with the exact bound depending on the mass difference, the mass, and the lifetime of the long-lived particle. The observed limits are the strongest reported for these two coannihilation scenarios.

What carries the argument

The key mechanism is a purely data-driven background estimation based on transfer factors. Events are divided into four 'planes' by the number of good tracks in the displaced vertex (0, 1, 2, or ≥3), and within each plane into regions by missing transverse momentum (pTmiss > 700 GeV) and vertex displacement significance (S_vtx_xy > 20). Transfer factors—ratios of event counts between planes—are measured at low pTmiss (200–400 GeV) and applied to high-pTmiss control regions to predict backgrounds in the signal regions; the S_vtx_xy distribution is taken from low-pTmiss data as a proxy. The signal reconstruction relies on the inclusive vertex finder tuned to accept low-momentum tracks with lar

Load-bearing premise

The background prediction relies on the assumption that the ratio of event counts between planes with different numbers of good tracks, and the fraction of events with high vertex displacement significance, are the same at low missing transverse momentum (200–400 GeV) as at high missing transverse momentum (>700 GeV).

What would settle it

Measure, in a dedicated high-pTmiss control sample with zero good tracks, the fraction of events that would have S_vtx_xy > 20 and compare it with the low-pTmiss proxy used in the paper; a statistically significant upward trend with pTmiss would mean the tight-plane background predictions are biased low, and the quoted exclusions would shrink.

Watch this falsifier — get emailed when new claim-graph text bears on it.

If this is right

  • The compressed stop coannihilation parameter space with Δm = 12–25 GeV is closed for stop masses up to 400–1100 GeV, depending on the branching fraction.
  • The bino-wino coannihilation scenario with wino-like neutralino masses below 220–550 GeV is excluded for lifetimes around 0.2–200 mm.
  • The transfer-factor background method can be applied to future LLP searches that need multiple exclusive signal regions with limited simulation.
  • The result provides a target for Run 3 and future collider searches: extending the same low-momentum displaced-vertex strategy to higher masses and smaller mass gaps.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • The same technique could be applied to non-SUSY hidden-sector models that produce compressed spectra, such as dark photon or exotic Higgs decays, where final-state particles are soft.
  • A testable extension: measure the S_vtx_xy and track-count ratios as a function of pTmiss in the 0-good-track control plane with the full Run 3 dataset; any rising trend would indicate the transfer-factor prediction underestimates high-pTmiss backgrounds.
  • The 10–11% track/vertex reconstruction systematic, inherited from a K0S control sample, might be reducible with better detector simulation, which would sharpen the exclusions.
  • The low-pTmiss transfer factors assume no correlation between pTmiss and vertex multiplicity; if pileup conditions differ in later data-taking, the extrapolation should be revalidated.

Editorial analysis

A structured set of objections, weighed in public.

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

Referee Report

3 major / 4 minor

Summary. The paper reports a CMS search for long-lived particles (LLPs) in proton-proton collisions at 13 TeV using 100 fb^-1 of 2017-2018 data, targeting displaced vertices with low-momentum tracks, large missing transverse momentum, and an ISR jet. It interprets the search in two compressed-spectrum SUSY coannihilation benchmarks: a stop NLSP and a bino-wino NLSP with mass splittings of 12-25 GeV. The background is estimated entirely from data via a transfer-factor method that relates track-count planes and applies S_vtx_xy fractions measured at low pT_miss to the high-pT_miss signal regions. After a maximum-likelihood fit under the background-only hypothesis, the observed yields are consistent with the prediction (reported global p-value 0.5), and 95% CL limits are set excluding stop masses below 400-1100 GeV and bino-wino neutralino masses below 220-550 GeV depending on model parameters. The paper claims the most stringent limits to date for these two models and the first LHC sensitivity to such compressed LLP signatures using displaced vertices.

Significance. If the result holds, it closes a previously unexplored corner of LLP parameter space: compressed coannihilation scenarios with small mass splittings that have limited sensitivity in earlier displaced-vertex searches. The analysis is careful in several respects: the background estimate is data-driven with explicit transfer-factor equations; the SR-excluded material map is derived from data; the validation is performed in orthogonal planes; per-region discrepancies are reported transparently; and the tracking/vertexing efficiency is calibrated with K0S decays. These are substantive strengths. The main caveat is the optimization of the alpha_p selection: the text states it was optimized on 'event yields in the SRs' without clarifying whether those yields were observed or expected, and this ambiguity is load-bearing for the quoted exclusions. The transfer-factor closure also deserves quantitative support. With those points resolved, the result would meet the standard for a high-energy physics search paper.

major comments (3)
  1. [Section 4, alpha_p optimization] The text states: 'This threshold is optimized to maximize the search sensitivity based on the event yields in the SRs and is not directly derived from Fig. 4.' If 'event yields in the SRs' means the observed yields that are later fit under the background-only hypothesis and used for CLs limits, then the alpha_p > 0.2 requirement is a selection on the data being tested, which can bias the background-only p-value and inflate the quoted exclusion ranges in Figs. 10-11. The statement that the threshold is 'not directly derived from Fig. 4' does not resolve this. Please state explicitly whether the optimization used expected signal and background from simulation, blinded control regions, or observed SR yields; if the latter, the selection is circular and the limits should be rederived with a frozen/blinded threshold. The ambiguity must be removed before the central exclusion claim can be asse
  2. [Section 5, Eqs. (3)-(11) and Fig. 7] The transfer factors are measured in the 200 < pT_miss < 400 GeV range and applied at pT_miss > 700 GeV, relying on the asserted independence of pT_miss and S_vtx_xy and on track-count ratios being pT_miss-independent. The validation in Fig. 7 is described only qualitatively ('For most of the regions... agree within statistical uncertainties'), and the paper does not report a quantitative closure test or a validation p-value. The observed departures in the search planes (tight B/D: 3 and 5 observed vs. 7.7 and 9.2 predicted; medium B: 98 vs. 78.8) are acknowledged but not propagated into the limit coverage. Please provide a quantitative pT_miss-dependence check for the transfer factors, a validation p-value for the orthogonal planes, and an explicit statement of how the observed deviations affect the CLs expected/observed limits.
  3. [Section 6, K0S calibration] The K0S-based efficiency systematic is derived after normalizing simulation to data at small Lxy, so the 10-11% envelope covers the Lxy-shape dependence but by construction absorbs the absolute reconstruction efficiency. The paper does not separately quantify the absolute normalization uncertainty in the signal efficiency. Since the quoted cross-section limits scale directly with signal efficiency, please state what part of the absolute efficiency is constrained by simulation only and what additional uncertainty (if any) is assigned to that absolute normalization.
minor comments (4)
  1. [Eq. (1)] The decay width is given in units of cm^-1, while cτ is quoted in length units. Please clarify the natural-unit convention and the relation cτ = B/Γ, including factors of c if needed.
  2. [Section 5, independence statement] The statement that pT_miss and S_vtx_xy are 'statistically independent' and that S_vtx_xy shapes are consistent across pT_miss ranges is not backed by a figure or a numerical test. Please include the relevant distribution comparison or a quantitative test statistic.
  3. [Section 7, p-value] The global p-value of 0.5 is quoted without specifying which regions enter the test statistic or whether nuisance parameters are profiled. Please define the statistic and the region set used for this p-value.
  4. [Section 4, vertex alpha_p discrepancy] The text notes that data vertices tend to have larger alpha_p than simulation because of pileup mismodeling. Since alpha_p is explicitly used in the optimization, please comment on how this data/simulation discrepancy affects the choice of the alpha_p threshold and the robustness of the assumed background model.

Circularity Check

0 steps flagged

No significant circularity: the analysis uses data-driven background estimates from control regions with orthogonal validation, and the cited theory inputs are external.

full rationale

The paper's central claim is an experimental exclusion, and the derivation chain is not circular. The background in the signal regions is not taken from the same regions: transfer factors are measured in the low-pT sideband (200 < pT_miss < 400 GeV) and in control regions B0/D0/B1/D1 of the nominal planes, multiplied across good-track plane indices, and the S_vtx_xy fraction is taken from low-pT data. The method is cross-checked in orthogonal validation planes, with an observed p-value of 0.5. Signal efficiencies are not normalized to the SR data: the K0S study normalizes data/simulation at small Lxy only to extract a shape-ratio systematic uncertainty (10–11%), and the material map explicitly excludes events contributing to the SRs. The only sentence that could look like selection on observed data is the alpha_p>0.2 optimization statement; however, Section 3 states that 'Simulated background events are used solely for selection optimization and systematic uncertainty studies and are not employed in the search results', so the SR-yield-based optimization is not a data-fitted input. Theoretical cross sections used for exclusions come from external NNLO+NNLL calculations, and no load-bearing self-citation or ansatz-smuggling step is present.

Axiom & Free-Parameter Ledger

4 free parameters · 7 axioms · 0 invented entities

This is an experimental search, so the ledger records what the measurement leans on. The model-dependence comes from the cited theory literature: the stop decay-width formula of Ref. [1] (Eq. 1) maps (m_stop, Delta m, B) to cTau, and the NNLO+NNLL cross sections of Ref. [53] convert cross-section upper limits into mass exclusions. The experimental premises are the S_vtx_xy/pT_miss independence and low-to-high pT transfer of background shapes (Section 5), the transferability of the KS efficiency calibration to signal-like vertices (Section 6), and the fidelity of the GEANT4 simulation after calibration. Analysis thresholds (alpha_p, S_vtx_xy, pT_miss, material-map density) are optimization choices; the KS normalization removes the absolute vertex efficiency by construction. The signal-model parameters (masses, Delta m, B, cTau) are scanned grid points, not fitted. No new physics entities are introduced.

free parameters (4)
  • alpha_p > 0.2 vertex selection threshold = 0.2
    Optimized to maximize search sensitivity based on SR event yields (Section 4); the paper does not state whether the optimization was on blinded expected yields or observed yields, so the final limits include a potential selection-on-data component.
  • SR-defining thresholds (pT_miss > 700 GeV, S_vtx_xy > 20) = 700 GeV / 20
    Chosen to define the A/B/C/D regions (Fig. 6) and 'optimized to achieve the maximum sensitivity to the benchmark signal models' (Section 5). The exclusion boundaries depend on these choices.
  • KS calibration normalization = unstated (MC normalized to data at small Lxy)
    Section 6: 'The simulation is normalized such that the number of KS decay candidate vertices at small Lxy is the same in data and simulation.' This absorbs the absolute reconstruction efficiency, so the 10-11% systematic covers only the Lxy-shape envelope, not a constant efficiency offset.
  • Material-map density threshold = unstated
    Section 4: 'a requirement on the vertex density as a function of the transverse radius is applied to exclude regions with fewer vertices'; the density-cut value is not quoted and shifts the veto rate (systematic 1-3%).
axioms (7)
  • domain assumption pT_miss and S_vtx_xy are statistically independent for backgrounds; transfer factors and S_vtx_xy shapes measured at 200-400 GeV transfer to pT_miss > 700 GeV.
    Load-bearing premise of the data-driven background estimate (Section 5, Eqs. 3-11); validated in orthogonal planes with agreement 'within statistical uncertainties' for most, not all, regions.
  • domain assumption Vertex reconstruction efficiency measured with KS decays (alpha_p < 0.2, two-track) applies to signal vertices (alpha_p > 0.2, one or more good tracks including low-pT tracks).
    Calibration-population gap in Section 6: the KS study explicitly excludes SR-like alpha_p, and the systematic is set by the Lxy-shape envelope after normalizing MC to data; a b-jet cross-check is reported as consistent.
  • domain assumption The stop four-body decay-width parameterization of Ref. [1] (Eq. 1) correctly maps (m_stop, Delta m, B) to cTau.
    The stop-model exclusions in Fig. 10 rely on this external theory input to convert branching fraction and mass gap into lifetime.
  • domain assumption NNLO+NNLL production cross sections (Ref. [53]) are correct to their quoted uncertainties.
    Mass exclusions are obtained by comparing observed upper limits to these cross sections (Section 7); scale and PDF variations of only 1-5% are assigned.
  • domain assumption GEANT4 simulation of the CMS detector, after KS-based correction, models displaced low-pT track and vertex reconstruction in signal events.
    All signal efficiencies come from simulation; pileup is matched to data and the data-derived material map is applied to simulation (Sections 3, 4, 6).
  • domain assumption For the bino-wino model, only Z-mediated chi20 decays into fermion pairs are considered; H-mediated decays are ignored.
    Section 1 explicitly restricts the simulated decay channels; if H-mediated decays contribute significantly, the cTau-to-observable mapping and hence the exclusion contours shift.
  • standard math The CLs procedure with profile likelihood in COMBINE is the accepted statistical standard for setting exclusion limits.
    Used for all quoted 95% CL limits (Section 7); standard in the field and not in dispute.

pith-pipeline@v1.3.0-alltime-deepseek · 40666 in / 28372 out tokens · 292483 ms · 2026-08-03T22:54:36.821361+00:00 · methodology

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read the original abstract

A search for long-lived particles using final states including a displaced vertex with low-momentum tracks, large missing transverse momentum, and a jet from initial-state radiation is presented. This search uses proton-proton collision data at a center-of-mass energy of 13 TeV collected by the CMS experiment at the CERN LHC in 2017 and 2018, with a total integrated luminosity of 100 fb$^{-1}$. This analysis adopts specific supersymmetric (SUSY) coannihilation scenarios as benchmark signal models, characterized by a next-to-lightest SUSY particle (NLSP) with a mass difference of less than 25 GeV relative to the lightest SUSY particle, assumed to be a bino-like neutralino. In the top squark ($\tilde{\mathrm{t}}$) NLSP model, the NLSP is a long-lived $\tilde{\mathrm{t}}$, while in the bino-wino NLSP scenario, the mass-degenerate NLSPs are a wino-like long-lived neutralino and a short-lived chargino. The search excludes top squarks with masses less than 400$-$1100 GeV and wino-like neutralinos with masses less than 220$-$550 GeV, depending on the signal parameters, including the mass difference, mass, and lifetime of the long-lived particle. It sets the most stringent limits to date for the $\tilde{\mathrm{t}}$ and bino-wino NLSP models.

Figures

Figures reproduced from arXiv: 2511.08212 by CMS Collaboration.

Figure 1
Figure 1. Figure 1: Feynman diagrams for the et NLSP (left) and the bino-wino NLSP (right) production. The paper is organized as follows. Section 2 provides an overview of the CMS detector. Sec￾tion 3 describes the data, simulation, and event selections used in this search. The vertex recon￾struction and selection are discussed in Section 4. Section 5 presents the definitions of the signal regions (SRs) and the background est… view at source ↗
Figure 2
Figure 2. Figure 2: The LLP reconstruction efficiency as a function of the transverse displacement of the [PITH_FULL_IMAGE:figures/full_fig_p008_2.png] view at source ↗
Figure 3
Figure 3. Figure 3: Diagram that shows the key features of a displaced vertex. [PITH_FULL_IMAGE:figures/full_fig_p009_3.png] view at source ↗
Figure 4
Figure 4. Figure 4: The vertex αp distribution compared between data, simulation, and bino-wino NLSP sample with mLLP = 400 GeV, cτ = 20 mm, and ∆m = 15 GeV. All distributions are normalized to unity. The ratio of data to simulation is shown in the lower panel. The arrow indicates the value of the optimal αp threshold. To remove vertices that result from nuclear interactions of SM particles with the tracker mate￾rial, we veto… view at source ↗
Figure 5
Figure 5. Figure 5: Material map for the CMS tracker derived from data. A zoomed-in view is provided [PITH_FULL_IMAGE:figures/full_fig_p011_5.png] view at source ↗
Figure 6
Figure 6. Figure 6: Definition of the signal (orange) and control (blue) regions. Different planes are [PITH_FULL_IMAGE:figures/full_fig_p012_6.png] view at source ↗
Figure 7
Figure 7. Figure 7: The number of observed and predicted background events in the regions of the val [PITH_FULL_IMAGE:figures/full_fig_p014_7.png] view at source ↗
Figure 8
Figure 8. Figure 8: The spread of the ratio of data and simulation, defined as 68% of the size of its envelope, [PITH_FULL_IMAGE:figures/full_fig_p015_8.png] view at source ↗
Figure 8
Figure 8. Figure 8: The K0 S decay candidate vertex Lxy distribution compared between data and simula￾tion. The ratios between data and simulation are shown in the lower panel [PITH_FULL_IMAGE:figures/full_fig_p016_8.png] view at source ↗
Figure 9
Figure 9. Figure 9: The number of observed and predicted background events after the fit to the regions [PITH_FULL_IMAGE:figures/full_fig_p018_9.png] view at source ↗
Figure 10
Figure 10. Figure 10: Observed 95% CL upper limits on the et production cross section, as functions of met and ∆m, for B(et → bff ′ χe 0 1 ) of 10% (upper left), 50% (upper right), and 100% (lower). The observed (solid black) and expected (dashed red) exclusion curves are overlaid on the plots. The search excludes the region to the left of the exclusion curves [PITH_FULL_IMAGE:figures/full_fig_p020_10.png] view at source ↗
Figure 11
Figure 11. Figure 11: Observed 95% CL upper limits on the production cross section for the bino-wino [PITH_FULL_IMAGE:figures/full_fig_p021_11.png] view at source ↗

discussion (0)

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Reference graph

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