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The first particle-level measurement of the momentum profiles of Upsilon(1S), Upsilon(2S), and Upsilon(3S) mesons inside jets shows that all tested Monte Carlo models overestimate the fraction of jet momentum carried by the quarkonium and u

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2026-08-01 01:48 UTC pith:W4WRDU62

load-bearing objection First Upsilon-in-jet fragmentation measurement: solid, useful, and mostly careful, but the 'PYTHIA fails' conclusion is visually argued and lands in the one region where the unfolding model uncertainty is largest. the 3 major comments →

arxiv 2607.25653 v1 pith:W4WRDU62 submitted 2026-07-28 hep-ex

Measurement of the fragmentation properties of jets containing Upsilon(nS) mesons in proton-proton collisions at sqrt{s} = 13 TeV

CMS Collaboration This is my paper
classification hep-ex
keywords Upsilon(nS) mesonsjet fragmentationlongitudinal momentum fractiontransverse momentum profilequarkonium productionNRQCDparton showerproton-proton collisions
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 establishes the first measurement of how Upsilon(1S), Upsilon(2S), and Upsilon(3S) mesons are distributed in momentum inside the jets that contain them, using 138 inverse femtobarns of proton-proton collisions at 13 TeV. Two observables are extracted: z, the fraction of the jet momentum carried by the Upsilon along the jet axis, and p_rel^T, the momentum component perpendicular to the jet axis. The unfolded, particle-level distributions are compared with four configurations of the PYTHIA Monte Carlo generator, combining two production mechanisms (NRQCD matrix elements versus NRQCD fragmentation in the parton shower) with two tunes. The paper finds that none of the tested configurations reproduces the data: the Upsilon mesons carry a smaller fraction of the jet momentum and a larger transverse momentum than predicted. The discrepancy is consistent across all three states and with earlier J/psi results, and the newer parton-shower treatment moves in the right direction but is still not sufficient.

Core claim

The paper claims to have measured, for the first time, the longitudinal and transverse fragmentation profiles of jets containing Upsilon(nS) mesons at particle level. The results show that Upsilon mesons are produced with more accompanying hadronic activity than current NRQCD-based Monte Carlo models predict: the measured z distribution is shifted to lower values and the measured p_rel^T distribution is shifted to higher values relative to all four PYTHIA configurations tested. The authors interpret this as evidence that PYTHIA implementations of NRQCD give Upsilon mesons too large a share of the jet momentum, and they note that the newer parton-shower implementation of NRQCD, while improvin

What carries the argument

The analysis rests on two observables: z = (p_jet · p_Upsilon)/|p_jet|^2, the fraction of the jet three-momentum carried by the Upsilon along the jet axis, and p_rel^T = |p_jet × p_Upsilon|/|p_jet|, the magnitude of the Upsilon momentum transverse to the jet axis. Yields of the three Upsilon states are extracted from binned maximum-likelihood fits to the dimuon invariant-mass spectrum in each kinematic bin, using crystal-ball signal shapes and a Chebyshev background. Detector effects (efficiency, purity, and bin migrations) are corrected with the iterative D'Agostini unfolding method, with response matrices built from a detector simulation. The particle-level results are then compared with t

Load-bearing premise

The unfolding of detector effects assumes that the detector response — the efficiency, purity, and bin-by-bin migrations — is correctly described by the PYTHIA8.240 simulation with the CP1 tune; if the true z and p_rel^T shapes differ from this model in ways not captured by the pT reweighting, the unfolded distributions could be biased, most severely near z ≈ 1 where the model uncertainty is largest.

What would settle it

A closure test using pseudo-data generated from a model whose z distribution has been artificially shifted toward lower values to match the data, unfolded with the nominal response matrix: if the unfolding fails to recover the input shift, then the central discrepancy seen in the data may be partly an artifact of the unfolding model dependence. Conversely, if an alternative measurement using a smaller jet radius (for example R=0.2) reproduces the same soft-fragmentation pattern, the result would be confirmed as a physical effect rather than a jet-algorithm artifact.

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

If this is right

  • The particle-level z and p_rel^T distributions become reference data that any future model of bottomonium production in jets must reproduce.
  • The observed shift to smaller z implies that current PYTHIA NRQCD implementations underestimate the soft radiation and hadronic activity produced alongside Upsilon mesons in jets.
  • The p_rel^T measurement adds sensitivity to transverse-momentum-dependent fragmentation functions, going beyond collinear fragmentation at moderate-to-large jet transverse momentum.
  • These data constrain the long-distance matrix elements of NRQCD and are expected to provide input to the long-standing quarkonium polarization puzzle.
  • The partial improvement seen with the parton-shower-based NRQCD implementation indicates that this direction is promising but requires further theoretical development.

Where Pith is reading between the lines

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

  • A natural next step would be to test whether the discrepancy originates in the long-distance matrix elements or in the parton-shower algorithm itself, by comparing the measured distributions with analytic NRQCD fragmentation functions computed beyond leading order.
  • The reported model uncertainty exceeds 50% at z ≈ 1, so the size of the deficit in the collinear region is the least constrained part of the result; an unfolding study using an alternative prior with a data-driven response matrix would test whether the deficit survives.
  • If the same soft-fragmentation pattern appears for different jet radii or for charmonium states, it would suggest a common mechanism in heavy-quark fragmentation, perhaps related to colour reconnection or hadronization dynamics.
  • The method could be transferred to open heavy-flavour hadrons (such as B mesons) to compare quarkonium fragmentation with ordinary heavy-quark fragmentation in the same kinematic region.

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 / 6 minor

Summary. The manuscript reports a CMS measurement of the fragmentation properties of jets containing Upsilon(1S), Upsilon(2S), and Upsilon(3S) mesons in proton-proton collisions at sqrt(s)=13 TeV with 138 fb^-1 of data. The observables are the longitudinal momentum fraction z and the transverse momentum p_rel^T of the Upsilon relative to the jet axis, measured in three jet-pT bins. Yields are extracted from dimuon invariant-mass fits, the detector response is unfolded with the D'Agostini method, and systematic uncertainties are evaluated for object reconstruction, event reconstruction, and unfolding. The unfolded distributions are normalized to unit area and compared with PYTHIA8.240 and PYTHIA8.310 predictions using the CP1 and CP5 tunes. The central claim is that none of these predictions reproduces the data: the Upsilon mesons are observed to carry a smaller longitudinal momentum fraction and a larger transverse momentum than predicted, and the discrepancies are described as important and as providing new constraints on NRQCD.

Significance. If the result holds, it provides the first bottomonium-in-jet fragmentation measurement at the LHC and extends the known J/psi-in-jet puzzle to the Upsilon sector, with sensitivity to NRQCD long-distance matrix elements and TMD fragmentation. The paper has notable strengths: three Upsilon states, three jet-pT bins, both longitudinal and transverse profiles, a detailed systematic accounting, and a HEPData record. However, the central 'unsatisfactory description' conclusion rests on visual comparison in Figures 6-8 rather than on a quantitative test, and it is made precisely in a kinematic region where the unfolding model uncertainty is stated to be the dominant uncertainty and to reach peak values above 50%. The paper's main claim is therefore not quantitatively established as written.

major comments (3)
  1. [Section 8; Section 9] The statements that 'none of the predictions described in Section 3 is able to reproduce the data' and that 'the results show important discrepancies' are based on visual inspection of Figures 6-8. No chi-squared, pull, or significance test is provided for any of the 18 distributions (3 states x 3 pT bins x 2 observables). This is load-bearing because the unfolding model uncertainty is the dominant uncertainty and reaches >50% in the collinear z~1 region (Section 7.3). The authors should add a quantitative comparison, e.g. a chi-squared per distribution computed with the full covariance matrix that includes the unfolding model uncertainty, or a pull distribution. If the significance disappears when the high-z model uncertainty is included, the conclusion should be weakened accordingly. MC statistical and, where available, theory uncertainties should be included or explicitly stated to be
  2. [Section 7.3] The model uncertainty is estimated by reweighting the PYTHIA8.240 CP1 sample to match data only in the transverse momenta of the jet and the Upsilon. This procedure may not cover mismodelling of the z and p_rel^T shapes themselves, which is exactly the physics under test. Since the claimed discrepancy is largest in the collinear region where the model uncertainty exceeds 50%, the robustness of the unfolded result there is not demonstrated. Please provide an additional closure test with an alternative response model or an injected shape difference, or at least show the data/MC comparison with the model uncertainty broken out per bin, so that the reader can see how much of the discrepancy is significant after this dominant systematic is included.
  3. [Section 6, Eq. (6)] The notation in Eq. (6), R_i = sum_j (E_j/P_i) A_ij T_j, is not fully defined. The text says E_j and P_i 'parameterize the efficiency' and 'purity', respectively, but it does not explain the index conventions or why the efficiency carries a particle-level index and the purity a detector-level index. Please define these quantities explicitly and state how the transfer matrix A_ij is normalized. This is not a challenge to the method, but the current presentation is ambiguous for a reader wishing to reproduce the correction chain.
minor comments (6)
  1. [Section 5, Eq. (4)] The text below Eq. (4) refers to 'the parameters n and alpha are set', but the function is written with an exponent nu. Use the same symbol (nu) in both the formula and the text.
  2. [Section 8] Typo: 'transverse momentum wih respect' should be 'with respect'.
  3. [Figures 6-8] The figures would be much more informative with ratio panels showing (data - MC)/(total uncertainty) or data/MC with the total uncertainty band. Without these, the claimed discrepancies are difficult to assess quantitatively, especially in the high-z and high-p_rel^T regions.
  4. [Figure 5] The relative systematic uncertainties are plotted with negative values, but the text does not explain whether these arise from asymmetric variations, the direction of the shift, or the sign convention of the nuisance parameter. Please clarify how the positive and negative values are combined into the total uncertainty band.
  5. [Section 3] The statement that only PYTHIA8.240 samples include full GEANT4 simulation, while PYTHIA8.310 samples are particle-level only, is important and should be reinforced when Figures 6-8 are discussed. The reader may otherwise wonder why detector-level model comparisons in Figure 3 involve only PYTHIA8.240.
  6. [Section 9] The sentence 'These results are consistent in magnitude with previous measurements of jets containing J/psi mesons by the LHCb and CMS Collaborations' is not supported by a quantitative comparison in this paper. Either add a brief quantitative statement or soften to 'qualitatively consistent'.

Circularity Check

0 steps flagged

No significant circularity: the measured z and p_rel^T distributions are unfolded from data using MC response corrections, and the PYTHIA predictions are external benchmark models, not fitted outputs of the measurement.

full rationale

The paper's central claim is an experimental measurement: Υ(nS)-in-jet fragmentation distributions unfolded to particle level, compared with PYTHIA8.240 and PYTHIA8.310 predictions. The unfolding in Section 6 uses a response matrix, efficiency, and purity from PYTHIA8.240 CP1, but the measured z and p_rel^T distributions are determined by the data through the regularized inversion of Eq. (6); they are not set equal to the MC input by construction. The MC dependence of the corrections is explicitly quantified in Section 7.3 as a systematic 'model uncertainty,' reaching >50% in the collinear region z≈1, and it is not hidden or renamed as a prediction. The comparison in Section 8 is against the particle-level predictions of the same and other MC tunes, which are independent of the measured values. No parameter of the physics models is fitted to the measured z or p_rel^T distributions, so the 'unsatisfactory description' conclusion is not statistically forced. There is no load-bearing self-citation chain, no uniqueness theorem imported from the authors, and no ansatz smuggled in via citation. The caveats noted in the text—dominant unfolding model uncertainty at high z and the absence of evaluated scale/PDF uncertainties on the MC predictions—are legitimate correctness/robustness concerns, not circularity. The measurement is self-contained against external benchmarks, and the honest finding is no significant circularity.

Axiom & Free-Parameter Ledger

3 free parameters · 4 axioms · 0 invented entities

No new particles or forces are introduced. The free parameters are all standard nuisance parameters for signal/background fits and unfolding regularization. The load-bearing assumptions are the NRQCD factorization framework and the use of a single PYTHIA tune for detector corrections.

free parameters (3)
  • Crystal Ball tail parameters ν, α in Eq. (4) = not stated; fitted from inclusive Υ(nS) sample
    Shape parameters of the signal pdf, fixed across all phase-space bins; they affect yields and hence the z/p_rel^T normalizations, but are standard fit nuisances.
  • Background Chebyshev coefficients p1, p2, p3 in Eq. (3) = fitted per bin
    Third-order polynomial background in the invariant-mass fits; standard nuisance parameters in yield extraction.
  • D'Agostini unfolding iteration count n = smallest n with χ2 p-value > 0.05
    Regularization parameter of the unfolding; chosen by a data-dependent criterion and part of the analysis pipeline rather than a physics parameter.
axioms (4)
  • domain assumption NRQCD factorization, Eq. (1)
    The paper's interpretation and MC generators assume production cross sections factorize into short-distance coefficients and LDMEs; introduced in Section 1 and used to motivate the measurement.
  • domain assumption PYTHIA8.240 CP1 as detector-response model for unfolding
    Sections 6 and 7.3: response matrices, efficiencies, and purities come from this single MC tune; model uncertainty is estimated only via pT reweighting, not an independent generator, making this the load-bearing assumption for the unfolded result.
  • domain assumption Particle-level phase space definition
    Section 6 defines the measured cross section: muons pT>6 GeV, dimuon pT>15 GeV, |y|<1.2, jet pT>60 GeV, |η|<1.5, and muons clustered in the jet; any interpretation is tied to this acceptance.
  • domain assumption Muon-subtracted jet energy correction reproduces inclusive jet response
    Section 4: subtracting muon four-momenta before applying standard jet energy corrections assumes the remaining hadronic jet responds like an inclusive jet; tested with recoil in data, but residual bias enters through the JES uncertainty.

pith-pipeline@v1.3.0-alltime-deepseek · 43286 in / 12770 out tokens · 137421 ms · 2026-08-01T01:48:39.002766+00:00 · methodology

0 comments
read the original abstract

A measurement of the fragmentation properties of jets containing $\Upsilon$(nS) mesons using proton-proton collision data at $\sqrt{s}$ = 13 TeV, corresponding to an integrated luminosity of 138 fb$^{-1}$, is presented. The $\Upsilon$(nS) mesons associated with jets are reconstructed via their decays producing pairs of oppositely charged muons. The longitudinal and transverse projections of the momenta of the $\Upsilon$(nS) mesons along the momenta of the corresponding jets are studied. The results are compared with Monte Carlo predictions, including recent developments in the modelling of quarkonia production in parton showers. The description of the data by these Monte Carlo predictions is found to be unsatisfactory, leaving room for improvements in the modelling of such processes.

Figures

Figures reproduced from arXiv: 2607.25653 by CMS Collaboration.

Figure 1
Figure 1. Figure 1: Example diagrams for the hard production of [PITH_FULL_IMAGE:figures/full_fig_p003_1.png] view at source ↗
Figure 2
Figure 2. Figure 2: Fits to the invariant mass distributions of [PITH_FULL_IMAGE:figures/full_fig_p009_2.png] view at source ↗
Figure 3
Figure 3. Figure 3: Detector-level longitudinal profile for Υ(1S) mesons (left) and transverse profile for Υ(3S) mesons (right) for two different ranges of the jet transverse momentum. The error bars on the data distributions represent the statistical uncertainties [PITH_FULL_IMAGE:figures/full_fig_p009_3.png] view at source ↗
Figure 4
Figure 4. Figure 4: Transfer matrices for the longitudinal profile of jets containing [PITH_FULL_IMAGE:figures/full_fig_p011_4.png] view at source ↗
Figure 5
Figure 5. Figure 5: Relative values of the systematic uncertainties discussed in the text, together with [PITH_FULL_IMAGE:figures/full_fig_p013_5.png] view at source ↗
Figure 6
Figure 6. Figure 6: Particle-level results for the longitudinal (left) and transverse profiles (right) of jets [PITH_FULL_IMAGE:figures/full_fig_p014_6.png] view at source ↗
Figure 7
Figure 7. Figure 7: Particle-level results for the longitudinal (left) and transverse profiles (right) of jets [PITH_FULL_IMAGE:figures/full_fig_p015_7.png] view at source ↗
Figure 8
Figure 8. Figure 8: Particle-level results for the longitudinal (left) and transverse profiles (right) of jets [PITH_FULL_IMAGE:figures/full_fig_p016_8.png] view at source ↗

discussion (0)

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