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REVIEW 3 major objections 4 minor 56 references

String-shoving simulations place the strongest ultra-long-range ridge at the lowest pp multiplicities.

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2026-08-03 17:27 UTC pith:JHY6MZP3

load-bearing objection Low-MPI dijets carry the real ridge signal; the claimed high-multiplicity failure of string shoving is muddied by the template-fit subtraction. the 3 major comments →

arxiv 2512.09195 v2 pith:JHY6MZP3 submitted 2025-12-09 hep-ph

Finite V_(rm 2Delta) puzzle in low-multiplicity pp collisions from ultra-long-range azimuthal correlations in the string-shoving model

Antonio Ortiz , Dushmanta Sahu , Gyula Bencedi This is my paper
classification hep-ph
keywords string shovingridge correlationslow-multiplicity pp collisionsV2Δtemplate fitflattenicitymultiparton interactionscollectivity
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 argues that the string-shoving mechanism in PYTHIA8 can produce a non-zero elliptic-flow coefficient V2Δ at ultra-long pseudorapidity separations, and that its signature should be most visible in the sparsest proton-proton collisions — events with only one or a few parton-parton scatterings. The authors show that V2Δ decreases with increasing charged-particle multiplicity, opposite to the weak multiplicity dependence seen in LHC data, and they connect this tension to biases in the template-fit method and in N_ch-based event selection. If correct, the low-multiplicity ridge in pp collisions need not signal a thermalized quark-gluon plasma; repulsive interactions among a few overlapping color strings could be enough. The paper also advocates replacing N_ch with global event-topology estimators such as flattenicity to obtain cleaner comparisons with data.

Core claim

Using PYTHIA8 with the string-shoving mechanism, the authors find that the second-order two-particle correlation coefficient V2Δ measured at 5<|Δη|<6 is largest in the lowest-multiplicity event classes, particularly for N_mpi≈1 dijet events, and declines monotonically as N_ch increases. This stands in contrast to LHC data, which show only a weak multiplicity dependence. They trace the model's decreasing trend to three effects: random cancellation of many small string pushes, dilution of a fixed anisotropic momentum over more particles, and an over-subtraction in the template-fit method because the low-multiplicity reference already contains flow-like correlations. The paper concludes that st

What carries the argument

The string-shoving mechanism: repulsive transverse pressure between overlapping color strings in PYTHIA8 that generates a collective push and mimics flow without a quark-gluon plasma. The extraction uses the template-fit method, which assumes high-multiplicity events are a scaled low-multiplicity 'non-flow' reference plus an additional Fourier term; V2Δ is read off the n=2 coefficient. The event-activity estimators N_ch (midrapidity charged multiplicity), N_mpi (number of parton-parton scatterings), and flattenicity (an event-shape variable measuring multiplicity fluctuations across V0-like cells) serve as alternative classifiers.

Load-bearing premise

The template-fit method assumes the low-multiplicity reference contains no genuine long-range flow; the paper itself shows that the string-shoving low-multiplicity template already carries flow-like correlations, so subtracting it can artificially suppress V2Δ at higher multiplicities.

What would settle it

If experimental analyses using an event-shape estimator like flattenicity (which the paper argues is less biased) were to show V2Δ increasing or flat with activity, the string-shoving prediction of a decreasing trend would be contradicted. Alternatively, a simulation with string shoving that uses a low-multiplicity template with flow explicitly removed (e.g., from a non-shoving baseline) should yield a flatter V2Δ(N_ch) if the over-subtraction explanation is correct.

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

If this is right

  • If string shoving is right, the low-multiplicity ridge observed in pp collisions does not require quark-gluon plasma formation.
  • N_ch-based event selection artificially dilutes the collective signal, so studies comparing models and data should use global estimators like flattenicity.
  • String shoving has a built-in saturation: it fades in dense, isotropic environments, consistent with a gradual onset of collectivity where hydrodynamics becomes relevant at high multiplicity.
  • The decreasing V2Δ trend in the model is partly an artifact of over-subtraction, so template-fit results should be reinterpreted with a flow-free reference.

Where Pith is reading between the lines

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

  • If flattenicity-based event classes are adopted in future LHC measurements, the data may show a stronger multiplicity dependence than the N_ch-based results, providing a direct test of the string-shoving contribution at low multiplicities.
  • The over-subtraction mechanism described here could also affect other small-system ridge studies that use template fits, suggesting a systematic re-analysis of existing low-multiplicity ridge data with alternative non-flow references.
  • The finding that dijet events produce the strongest shoving signal implies that jets may seed the geometry for collective-like correlations, connecting the ridge to jet fragmentation in a way that can be studied with jet-triggered correlations.

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. This paper uses PYTHIA8 (v8.312, string-shoving extension, g=10) to compute the second-order two-particle correlation V2Δ for |Δη| in [5,6] in pp collisions at 13 TeV, studying its dependence on three event-activity estimators: midrapidity Nch, generator-level Nmpi, and flattenicity. The template-fit method is used to extract V2Δ from Δφ projections. The authors report that V2Δ decreases with Nch, while ALICE data show a much weaker multiplicity dependence; that the raw correlation is strongest for the lowest-Nmpi (dijet-like) event class, contrary to the usual high-multiplicity collectivity picture; and that Nch is more biased toward jet-like topologies than Nmpi or flattenicity. They conclude that string shoving may explain the low-multiplicity ridge and that hydrodynamics becomes relevant only at high multiplicity.

Significance. If the quantitative result were robust, this would be a valuable constraint on the origin of collectivity in small systems: it would demonstrate that a non-fluid, initial-state mechanism can generate ultra-long-range azimuthal correlations specifically in low-multiplicity events, and that the event-activity estimator is not a neutral choice. The paper is transparent in listing its PYTHIA parameters (Table I) and in scanning the shoving strength g (Fig. 5), which makes the model dependence of the signal falsifiable. The main weakness is that the central V2Δ(Nch) trend rests on a template subtraction whose low-multiplicity reference is shown by the authors themselves to contain long-range flow-like correlations; no matched no-shoving control or closure test is provided. The low-Nmpi ridge is visible in raw yields, so that part of the conclusion is less affected, but the quantitative model-data comparison and the 'hydro becomes relevant at high multiplicity' inference are not cleanly established.

major comments (3)
  1. [Sec. III (Fig. 2), Eq. (2), Summary item 5] The central evidence for a decreasing V2Δ(Nch) trend is the template-fit extraction in Fig. 1. Equation (2) requires the low-multiplicity template Y^LM to contain no genuine long-range correlation. The paper demonstrates otherwise: the string-shoving LM template already contains flow-like correlations, which are then subtracted from all higher Nch classes (Sec. III, Fig. 2 discussion; Summary item 5). This over-subtraction can produce the decreasing trend by construction. The Monash-LM-template check in Fig. 2 is not a matched control: Monash differs in tune, hadronization, and non-flow shape from the string-shoving sample, so it does not isolate the shoving effect. I acknowledge that the low-Nmpi ridge is visible in raw yields (Fig. 4) and is therefore independent of the template subtraction; my concern is specifically the quantitative V2Δ(Nch) trend and its interpretation as evidence a
  2. [Sec. II.B and Figs. 1-4] No statistical or systematic uncertainties are reported for the PYTHIA V2Δ values, and no closure test of the template fit is provided. The model-data differences that drive the conclusions are at the level of V2Δ ~ 0.0005–0.002 (Figs. 1-2), so without error bars it is unclear whether the quoted trends are significant relative to stochastic fluctuations. A closure test, in which a known V2Δ is injected into the signal class and recovered by Eq. (2), is especially important given that the reference itself contains long-range correlations. Even with 10 billion events, systematic uncertainties from the choice of template and event-class boundaries must be quantified before comparing to ALICE data.
  3. [Sec. II.C, Eq. (3), and Fig. 4] The recommendation that flattenicity is a better estimator than Nch is only partly supported by the presented evidence. Flattenicity was constructed in Ref. [36] to select MPI-dominated, topologically isotropic events, so the statement that it reduces Nch-type bias is, to some extent, built into its definition. More importantly, the comparison in Fig. 4 is between classifiers acting on different acceptances: Nch is midrapidity, while flattenicity is built from V0-like cell multiplicities that overlap the forward/backward intervals used to construct V2Δ (2.6<η<3.2 and -3.0<η<-2.0). This overlap can introduce an autocorrelation in the flattenicity-selected per-trigger yields. To make the claim robust, the authors should quantify the acceptance overlap or repeat the flattenicity definition using a disjoint acceptance and show that the conclusions are unchanged.
minor comments (4)
  1. [Table II] The table header says 'Flattenicity Range' but the text says the reported quantity is 1-ρ_nch. Please state explicitly in the table/caption whether the ranges refer to 1-ρ_nch or ρ_nch, since the values (0.00–0.78, etc.) are hard to interpret otherwise.
  2. [Figs. 1-2] The figure legends are incomplete in the printed text: the hydro band in Fig. 1 is mentioned in the caption but no legend entry is visible in the figure itself. Please also state in the captions that the PYTHIA points carry no uncertainty bars.
  3. [Sec. II.B, Eq. (1)-(2)] Equation (2) omits the explicit |Δη| integration; please state clearly that the fit is applied to the Δφ projection integrated over 5.0<|Δη|<6.0, as described in the text, so that the notation is self-contained.
  4. [References] Refs. [34] and [41] appear to refer to the same paper (Bierlich, Gustafson, Lönnblad, JHEP 10 (2016) 139 / arXiv:1612.05132). Please consolidate to avoid duplicate citations.

Circularity Check

0 steps flagged

No load-bearing circularity: the template-fit over-subtraction is acknowledged and partly controlled; the main claim is anchored by external ALICE data and by raw correlation structures.

full rationale

The central derivation is a Monte Carlo comparison rather than a first-principles chain: PYTHIA8 with string shoving is run with fixed parameters (g=10), per-trigger yields are computed directly, and the extracted V2Δ(Nch) is compared to ALICE data and to a hydrodynamic calculation. No parameter is fitted to the target V2Δ data and then renamed as a prediction. The one caveat that could look definitional — Eq. (2) defines V2Δ as the excess over a scaled low-multiplicity template Y^LM, and the paper admits that the string-shoving LM template already contains flow-like correlations, causing over-subtraction (Sec. III, Fig. 2 discussion; Summary item 5) — is explicitly acknowledged and is not the sole basis for the conclusion. The same section shows that using a Monash (non-flow) LM template still yields a decreasing V2Δ(Nch) ('the trend is still decreasing'), so the decreasing trend is not generated purely by the contaminated reference. The low-Nmpi sensitivity and the g-dependence of the ridge are also taken directly from raw Δφ distributions, independent of the template subtraction. The flattenicity recommendation cites the authors' prior work [36] for the estimator's design goal, but the paper's own new simulations (Figs. 3–4) and the external ALICE benchmark carry the argument; the self-citation is therefore not load-bearing. Overall, the paper is self-contained and benchmarked against external data; no circular reduction of a predicted quantity to a fitted input or self-citation chain is identifiable.

Axiom & Free-Parameter Ledger

5 free parameters · 5 axioms · 0 invented entities

The central claims rest on the string-shoving model and on template-fit/event-classifier assumptions. No new physical entities are introduced; flattenicity is borrowed from the authors' prior work. The model parameters (g, r0, deltay, proton radius) are set from prior tunes, and F/G are fitted per class in the analysis.

free parameters (5)
  • Ropewalk:gAmplitude (g) = 10 (g=3 and g=40 explored)
    String-shoving repulsion strength; chosen by hand as 'conservative', not fit to ALICE data. Conclusions are g-dependent at low Nmpi (Fig. 5).
  • Ropewalk:r0 = 0.41
    Transverse string radius in the shoving model; adopted from model defaults, not varied or fit here.
  • Ropewalk:deltay = 0.10
    Longitudinal step for shoving; model input, not varied.
  • PartonVertex:ProtonRadius = 0.70
    Proton radius used for parton vertices; model input.
  • Template-fit F and G = per event class
    Scaling factors in Eq. (2) fitted by chi-square to each Δφ projection; the extracted V2Δ depends on the choice of LM reference (string-shoving vs Monash).
axioms (5)
  • domain assumption String shoving model: overlapping color strings repel via gluon exchange, producing transverse collective push.
    Underlying mechanism under test; assumed by PYTHIA8 Ropewalk and by the interpretation of the low-Nmpi ridge (Sec. II.A, III).
  • domain assumption Template-fit ansatz (Eq. 2): high-multiplicity Δφ yield = F × low-multiplicity yield + G(1+Σ2VnΔ cos nΔφ), with flow-free LM reference.
    Used to extract V2Δ; the paper notes the LM reference from string shoving already contains flow, violating the flow-free assumption (Sec. II.B, III).
  • domain assumption Ultra-long-range |Δη|>5 correlations on the near side are free of jet/resonance non-flow.
    Central to claiming the ridge is not from jet fragmentation; stated in Sec. II.B.
  • domain assumption Flattenicity (Eq. 3) in the V0 acceptance is a valid proxy for MPI activity / global event topology.
    Adopted from the authors' prior work (Refs. [36,47]); the paper's recommendation to prefer flattenicity over Nch relies on this.
  • domain assumption PYTHIA8 Monash tune provides a baseline with negligible long-range flow, usable as a pure non-flow template.
    Used in Fig. 2 to construct an alternative LM template; if Monash also contains residual flow, the subtraction is again biased (Sec. III, Fig. 2).

pith-pipeline@v1.3.0-alltime-deepseek · 12899 in / 15328 out tokens · 142917 ms · 2026-08-03T17:27:24.370187+00:00 · methodology

0 comments
read the original abstract

Ultra-long range angular correlations have been recently reported by the ALICE collaboration in pp collisions at $\sqrt{s}=13$ TeV below ${\rm d}N_{\rm ch}/{\rm d}\eta=7$. The measurements have been performed as a function of the charged-particle multiplicity at midrapidity ($N_{\rm ch}$ in $|\eta|<0.8$), which is known to be strongly sensitive to local multiplicity fluctuations. The present work investigates the impact of the event-activity estimator on ultra-long range angular correlations. The study is conducted in the framework of PYTHIA8 with the string shoving mechanism since it gives a non-zero elliptic flow coefficient, $V_{2\Delta}$. The analysis is conducted as a function of $N_{\rm ch}$, the number of parton-parton scatterings ($N_{\rm mpi}$) and flattenicity. Surprisingly, for ultra-long range correlations, pp collisions with $N_{\rm mpi}=1$ (dijets) seems to be the most sensitive to string shoving. The effect diminishes with increasing $N_{\rm mpi}$. While in data, within uncertainties, $V_{2\Delta}$ exhibits a weak multiplicity dependence; the string shoving mechanism gives a $V_{2\Delta}$ that decreases with the increase in $N_{\rm ch}$. The present work therefore supports the picture stating that mechanisms such as string shoving might explain the low multiplicity limit, whereas, hydro becomes relevant in high-multiplicity pp collisions. This work also suggests that flattenicity might be more effective than $N_{\rm ch}$ to better handle non-flow effects.

Figures

Figures reproduced from arXiv: 2512.09195 by Antonio Ortiz, Dushmanta Sahu, Gyula Bencedi.

Figure 1
Figure 1. Figure 1: FIG. 1. The [PITH_FULL_IMAGE:figures/full_fig_p005_1.png] view at source ↗
Figure 2
Figure 2. Figure 2: FIG. 2. The [PITH_FULL_IMAGE:figures/full_fig_p005_2.png] view at source ↗
Figure 3
Figure 3. Figure 3: FIG. 3. The ultra-long range correlation per-triggered yield estimated as a function of ∆ [PITH_FULL_IMAGE:figures/full_fig_p007_3.png] view at source ↗
Figure 4
Figure 4. Figure 4: FIG. 4. The ultra-long range correlation per-triggered yield estimated as a function of ∆ [PITH_FULL_IMAGE:figures/full_fig_p008_4.png] view at source ↗
Figure 5
Figure 5. Figure 5: FIG. 5. The ultra-long range correlation per-triggered yield estimated as a function of ∆ [PITH_FULL_IMAGE:figures/full_fig_p009_5.png] view at source ↗

discussion (0)

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Reference graph

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