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REVIEW 2 major objections 5 minor 69 references

This paper claims that the Run 2 calibration of large-radius jets—reconstructed from Unified Flow Objects and groomed with soft drop—reduces the jet energy and mass scale uncertainty to about one percent up to transverse momenta of 1 TeV, a

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2026-08-01 01:12 UTC pith:RHHYPRZV

load-bearing objection The reference Run 2 large-R jet calibration for ATLAS boosted-object physics; central claim is sound, but the forward-folding mass-shape assumption and the R_trk high-pT bridge deserve referee scrutiny. the 2 major comments →

arxiv 2607.25893 v1 pith:RHHYPRZV submitted 2026-07-28 hep-ex

The calibration of large-radius jets using the Run 2 dataset with the ATLAS detector

ATLAS Collaboration This is my paper
classification hep-ex
keywords jet calibrationlarge-radius jetsjet energy scalejet mass scalesoft dropUnified Flow Objectsin-situ calibrationboosted objects
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.

The paper claims that large-radius jets in the ATLAS Run 2 data can be calibrated so that both their energy scale and their invariant mass scale agree with the particle-level truth to within about one percent for jet transverse momenta up to 1 TeV, degrading to only two to three percent at 2 TeV. This is achieved by a two-step chain: a Monte Carlo-based correction that restores closure to better than one percent across the detector, followed by in-situ balance measurements (Z+jet, photon+jet, multijet balance) whose combination gives a data-to-simulation response ratio of about 0.985. The jet mass scale is then checked by forward-folding fits to the W-boson and top-quark mass peaks, which find a mass scale compatible with unity within about one percent. If the claim is correct, analyses using boosted objects inherit a ~1% jet scale and its uncertainty, rather than the several-percent uncertainties typical of earlier large-radius jet calibrations.

Core claim

The central discovery is that the energy and mass response of large-radius jets in collision data agrees with the Monte Carlo prediction to about one percent once the complete calibration chain is applied. The in-situ combination of Z+jet, photon+jet, and multijet balance yields a flat data-to-MC response ratio of about 0.985 with no significant pT dependence, and the jet mass scale extracted from the W and top peaks is compatible with unity within about one percent. Consequently, after applying the in-situ energy correction, no additional in-situ mass correction is needed for large-radius UFO soft-drop jets.

What carries the argument

The load-bearing mechanism for the mass-scale claim is the forward-folding mass response model, Eq. (3): m_fold = s·m_reco + (m_reco − m_truth·⟨R_m⟩)·(r−s), where s and r absorb the MC-to-data mass scale and resolution ratios. Templates built from this non-gaussian response are fitted to the W-peak (50–120 GeV) and top-peak (120–300 GeV) regions, converting observed mass peaks into a jet mass scale and its uncertainty. For the energy scale, the analogous mechanism is the weighted combination of three balance methods, with pseudo-experiments propagating correlations, which produces the global R_data/R_MC ≈ 0.985 curve.

Load-bearing premise

The jet mass response shape from Monte Carlo—including threshold effects, non-gaussian tails, and mass-dependent widths—is assumed to describe data up to an overall scale and resolution rescaling; if that shape differs between data and simulation, the fitted mass scale and its ~1% uncertainty would be biased.

What would settle it

Run the forward-folding fits separately on the W-peak (50–120 GeV) and the top-peak (120–300 GeV) regions using a larger dataset than Run 2; if the two extracted mass scales differ by more than their combined uncertainty, the two-parameter non-gaussian response model does not describe the data and the ~1% jet mass scale claim fails. The same comparison can be made by checking the template fit residuals in the sidebands of both peaks.

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

If this is right

  • Boosted-object analyses can take the large-radius jet energy and mass scales as known to about 1% up to 1 TeV, removing the jet scale as a dominant systematic.
  • The in-situ correction factor (data-to-MC response ≈ 0.985) becomes part of the default calibration for Run 3 data, so future measurements inherit this scale.
  • The combination and nuisance-parameter reduction (from 194 to 23 uncertainty sources) makes the jet energy scale uncertainty practical to propagate in searches and measurements.
  • Because the mass scale is consistent with unity, no further in-situ mass correction is applied, and the MC-based mass response is used as the reference for the jet mass.

Where Pith is reading between the lines

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

  • The high-pT jet mass scale (above ~350 GeV) relies on an extrapolation: track-based R_trk measurements on calorimeter jets are bridged to large-radius UFO jets by an MC-computed additional uncertainty, because R_trk cannot be applied directly to UFO jets. A dedicated in-situ mass-scale probe on UFO jets at high pT would test this bridge.
  • If the calibration is correct, the W and top mass peaks in boosted ttbar events should stay centered at the same masses across pile-up conditions; the paper shows this for Run 2, and Run 3 data with higher pile-up can confirm or refute it.
  • The two-parameter forward-folding model (scale and resolution only) assumes the non-gaussian response shape is transferable from MC to data. Fitting the same peaks with a third shape parameter, or checking the template fit in the sidebands, would expose any missing shape dependence.
  • The success of this chain suggests the same calibration strategy—MC closure plus balance-based in-situ correction plus forward-folding validation—could be applied to future jet definitions or to substructure observables beyond the mass.

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

2 major / 5 minor

Summary. This paper presents the ATLAS Run 2 calibration of large-radius jets reconstructed from Unified Flow Objects (UFOs) and groomed with soft drop. The calibration chain consists of a Monte Carlo (MC) step that restores reconstructed jets to particle level, followed by in-situ corrections from collision data. The MC energy calibration achieves closure within 1% (Fig. 1), while the MC mass calibration has residual non-closure up to 5% for low-energy jets (Sec. 4.2). Three in-situ energy-scale methods (Z+jet, gamma+jet, multijet balance) are combined, yielding R_data/R_MC ≈ 0.985 with no significant pT dependence and combined JES uncertainty below 1% up to 1 TeV and 2–3% up to 2 TeV (Sec. 8.1, Fig. 18). The jet mass scale is measured by forward-folding fits to the W and top peaks (Sec. 7, Eq. 3) and extrapolated to higher pT using R_trk on calorimeter jets with an MC-derived bridging uncertainty (Sec. 8.2). The central claim is that the residual JES and JMS uncertainties are close to 1% up to 1 TeV and 2–3% up to 2 TeV.

Significance. If the result holds, this is an important reference calibration for boosted-object analyses at the LHC. The paper benefits from the full Run 2 dataset (140 fb^-1), three independent in-situ balance channels with external reference objects (Z, photon, small-R jets), detailed uncertainty breakdowns, and explicit checks of pile-up dependence. The energy-scale combination is internally consistent, with the reported chi2/dof near unity. The main weakness is the jet-mass-scale determination: the forward-folding procedure assumes the non-Gaussian MC response shape transfers to data up to a scale and resolution rescaling, but no goodness-of-fit or closure test is shown to validate this assumption. This is load-bearing for the claimed ~1% JMS uncertainty and for the abstract's statement that no further in-situ mass correction is needed.

major comments (2)
  1. [Section 7, Eq. (3)] The JMS measurement rests entirely on the forward-folding formula m_fold = s*m_reco + (m_reco - m_truth*<R_m>)*(r-s), with only s and r floated. The paper does not report the chi2/dof of the template fits, nor does it show fitted-template overlays, and there is no closure test using pseudo-data with a known injected JMS. Given the stated residual MC non-closure of up to 5% in Sec. 4.2, a data/MC shape mismatch in the non-Gaussian response (threshold effects, tails) could be absorbed by s and bias the JMS≈1 result and its ~1% uncertainty. Please provide per-pT-bin fit quality, template overlays, and a pseudo-data injection test or an explicit shape-mismatch systematic.
  2. [Section 8.2] The high-pT JMS extrapolation uses R_trk measurements on large-R calorimeter jets, bridged to UFO jets by an MC-derived additional uncertainty (up to 10% for m<50 GeV and ≤1% otherwise). Because the paper states R_trk does not apply to large-R UFO jets, this bridging cannot be validated in data. This is load-bearing for the 2–3% JMS uncertainty quoted up to 2 TeV. Please describe in more detail how the bridging uncertainty was derived (e.g., the comparison of UFO vs. calorimeter jet mass response across generators and topologies) and provide a sensitivity test showing that the uncertainty covers the observed response differences.
minor comments (5)
  1. [Section 2.2] Typo: 'top-quark in asosciation with a W boson' should be 'in association'.
  2. [Section 4] Typo: 'reconstructed large-R jets with pT>100 GeV are matched to particle-level large-R jets with with ptrueT>100 GeV' has a duplicated 'with'.
  3. [Section 8.3] Stray character: 'T The uncertainty in the jet energy scale ranges...' should be cleaned up.
  4. [Section 7] The description 'the fit is performed by marginalizing over each parameter' is ambiguous; please clarify whether a 2D scan or a profile likelihood is used.
  5. [Section 6, Fig. 14] The discontinuity in the non-closure uncertainty is attributed to a sign change in the definition; please state the definition explicitly so the reader can interpret the plot correctly.

Circularity Check

0 steps flagged

No significant circularity: the in-situ anchors (Z, photon, small-R jets) are external, and the JES/JMS results are data measurements against which the calibration is tested.

full rationale

The derivation chain is self-contained relative to external references. The MC calibration closure (Fig. 1) is a calibration validation rather than a prediction, and the paper explicitly reports a residual mass non-closure reaching 5% even when evaluated on the samples used to derive the factors (Sec. 4.2), showing the closure is not forced. The in-situ JES is anchored to Z->ee/mu mu, isolated photons, and multijet systems of small-R jets whose own JES is calibrated via independent gamma+jet and Z+jet methods; the measured R_data/R_MC ~ 0.985 (Fig. 18) is a genuine data measurement, with data below MC, not an enforced agreement. The JMS forward-folding fit (Eq. 3) floats s and r against W and top mass peaks in data; s ~ 1 is a fitted outcome, and the MC non-Gaussian response shape is a stated modeling assumption rather than a circular input. The Sec. 8.2 R_trk extrapolation is explicitly acknowledged as inapplicable to large-R UFO jets and is used only with an MC-derived bridging uncertainty, making it a transparent cross-check/extrapolation rather than a hidden self-consistency constraint. Cited prior ATLAS works are published external studies, and no load-bearing uniqueness theorem or ansatz is imported via self-citation.

Axiom & Free-Parameter Ledger

3 free parameters · 7 axioms · 0 invented entities

The central uncertainty claims rest on: (i) simulation fidelity of the ATLAS Geant4 model, corrected by in-situ anchors rather than independently verified; (ii) the assumption that Pythia/Herwig/Sherpa differences bracket true modelling uncertainty; (iii) shape transferability of the jet-mass response in forward folding; (iv) the R_trk calorimeter-jet proxy for high-pT UFO jet mass. These are honest, mostly explicit assumptions of the established calibration genre; no new physical entities are postulated.

free parameters (3)
  • Combined MC mass calibration pT threshold = 500 GeV
    Sec. 4.2: W/Z-boson calibrations applied for pT<500 GeV, multijet for higher pT; a hand-chosen boundary motivated by statistical coverage, not derived.
  • R_trk JMS bridging uncertainty = up to ~10% for m<50 GeV; ≤1% otherwise
    Sec. 8.2: additional uncertainty added because R_trk cannot be applied to UFO jets; estimated from MC comparison of jet definitions — an ad hoc bridging uncertainty the 2-3%-at-2-TeV mass claim leans on.
  • Forward-folding fit parameters s, r = s∈[0.9,1.1] step 0.001; r∈[0.5,1.5] step 0.01; outcome JMS≈1
    Sec. 7: fitted to the W/top mass peaks in data; listed for transparency because these are measurement outputs used for validation, not hidden inputs.
axioms (7)
  • domain assumption Geant4-based simulation models the ATLAS detector response well enough that residual data-MC differences are covered by the assigned in-situ uncertainties.
    Sec. 4 (MC calibration premise) and Sec. 5 (in-situ validation premise); the forward-region response in data is explicitly not well-reproduced in simulation (Sec. 5.1).
  • domain assumption Generator differences (Powheg+Pythia/Herwig/Sherpa) bracket the true MC modelling uncertainty.
    Used throughout Secs. 5-8 as the modelling systematic; assumes no common-mode bias shared by all generators.
  • domain assumption The non-gaussian jet-mass response shape from MC is correct up to scale s and resolution r; no data-MC shape difference remains.
    Sec. 7, Eq. 3: forward-folding templates assume shape transferability; the paper's main fit-range checks probe the core, not the shape family.
  • domain assumption R_trk measurements on calorimeter jets can stand in for the UFO jet mass response with an MC-derived addition.
    Sec. 8.2: the paper states R_trk 'does not apply to large-R UFO jets' because tracks are part of the jet definition, so the JMS extrapolation to high pT is indirect.
  • domain assumption Particle-level jets defined with cτ>10 mm and excluding muons/neutrinos are the correct calibration target.
    Sec. 4: the MC calibration reference definition is a convention that shapes the entire calibration.
  • domain assumption The MC-derived jet-pT resolution correlation ρ (2-6%) transfers from simulation to data.
    Sec. 6: ρ enters the corrected asymmetry-method formulas; values are taken from Pythia MC, with a non-closure uncertainty assigned.
  • standard math Standard variance-algebra identities and quadrature error propagation are used throughout.
    Sec. 6 (correlation formula), Sec. 8 (combination and pseudo-experiment propagation).

pith-pipeline@v1.3.0-alltime-deepseek · 61905 in / 25000 out tokens · 228555 ms · 2026-08-01T01:12:12.144243+00:00 · methodology

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read the original abstract

The ATLAS experiment has developed an extensive procedure based on Monte Carlo simulation and collision data to calibrate the response of large-radius jets. This paper describes the Run 2 calibration of large-radius jets reconstructed from Unified Flow Objects and groomed with the Soft Drop algorithm, using data produced in proton-proton collisions at $\sqrt{s}=13$ TeV. Results are presented for the Monte Carlo-based correction and for the in situ methods that are used to validate the jet energy and mass scales and their resolutions in collision data. The residual uncertainty on the jet energy and mass scales is close to 1% for transverse momenta up to 1 TeV and is 2-3% up to 2 TeV, enabling sensitive searches to beyond the Standard Model particles and precise Standard Model measurements with boosted objects.

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