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arxiv: 2605.25729 · v1 · pith:PHDL3LSDnew · submitted 2026-05-25 · ✦ hep-ex

Methods for Centrality Determination Using Forward Detectors in the BM@N Experiment

Dim Idrisov , Fedor Guber , Nikolay Karpushkin , Peter Parfenov This is my paper

Pith reviewed 2026-06-29 19:33 UTC · model grok-4.3

classification ✦ hep-ex
keywords centrality determinationforward detectorsBM@N experimentheavy-ion collisionsGlauber modelBayesian approachFHCalXe+CsI collisions
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The pith

Modified Bayesian and forward-detector methods determine collision centrality in BM@N with agreement to Glauber models within 5%.

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

The paper develops improved methods for determining the centrality of heavy-ion collisions using data from the BM@N experiment. It modifies a Bayesian approach based on charged particle multiplicity to also estimate event registration efficiency as a function of impact parameter. Two new methods use signals from forward detectors like the Forward Hadron Calorimeter and a quartz hodoscope. These are tested on xenon beam data and compared to the standard Monte Carlo Glauber approach. The agreement within 5% shows the methods are reliable and can help reduce autocorrelation effects in fluctuation studies.

Core claim

The developed methods for centrality determination, including a modified Bayesian approach and two approaches based on forward detectors, agree with the classical Monte Carlo Glauber approach within 5% when applied to Xe+CsI collisions at 3.8 A GeV, confirming their reliability and mutual consistency.

What carries the argument

The two-dimensional method combining track hit counts and spectator deposited energy in the FHCal, along with the method using quartz hodoscope and FHCal signals, for estimating centrality.

If this is right

  • These methods can be used for data processing in the BM@N experiment and other heavy-ion experiments at intermediate energies.
  • The use of forward detectors provides an independent tool for assessing initial collision geometry.
  • They can reduce autocorrelation effects in studies of proton multiplicity fluctuations.
  • The modified Bayesian approach allows estimation of event registration efficiency versus impact parameter.

Where Pith is reading between the lines

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

  • The methods might allow better comparison of data across different experiments by providing consistent centrality measures.
  • If applied to other energies, they could test how centrality determination scales with beam energy.
  • Reducing autocorrelation could lead to more accurate measurements of fluctuations in particle production.

Load-bearing premise

The assumption that the event registration efficiency depends on impact parameter in a way that can be estimated from charged particle multiplicity using the modified Bayesian method.

What would settle it

A direct comparison showing disagreement larger than 5% between the new methods and the Glauber approach in the same dataset would falsify the claim of reliability.

Figures

Figures reproduced from arXiv: 2605.25729 by Dim Idrisov, Fedor Guber, Nikolay Karpushkin, Peter Parfenov.

Figure 1
Figure 1. Figure 1: Schematic view of the BM@N setup in the 2023 Xe run. Main components: [PITH_FULL_IMAGE:figures/full_fig_p003_1.png] view at source ↗
Figure 2
Figure 2. Figure 2: Results of fitting the charged particle multiplicity using the Monte Carlo [PITH_FULL_IMAGE:figures/full_fig_p005_2.png] view at source ↗
Figure 3
Figure 3. Figure 3: Results of fitting the charged particle multiplicity using the direct reconstruction [PITH_FULL_IMAGE:figures/full_fig_p007_3.png] view at source ↗
Figure 4
Figure 4. Figure 4: Calculated efficiency as a function of impact parameter. [PITH_FULL_IMAGE:figures/full_fig_p008_4.png] view at source ↗
Figure 5
Figure 5. Figure 5: Correlation between spectator energy deposited in FHCal and impact parameter [PITH_FULL_IMAGE:figures/full_fig_p010_5.png] view at source ↗
Figure 6
Figure 6. Figure 6: (Left) Fit results for the two-dimensional distribution of hit counts and energy [PITH_FULL_IMAGE:figures/full_fig_p011_6.png] view at source ↗
Figure 7
Figure 7. Figure 7: Centrality classes for the two-dimensional distribution of track hit counts and [PITH_FULL_IMAGE:figures/full_fig_p011_7.png] view at source ↗
Figure 8
Figure 8. Figure 8: Comparison of total energy in the calorimeter from model and experiment after [PITH_FULL_IMAGE:figures/full_fig_p012_8.png] view at source ↗
Figure 9
Figure 9. Figure 9: Centrality classes for the two-dimensional distribution of signals from the quartz [PITH_FULL_IMAGE:figures/full_fig_p012_9.png] view at source ↗
Figure 10
Figure 10. Figure 10: Impact parameter distributions for three centrality classes(0-10%, 30-40%, [PITH_FULL_IMAGE:figures/full_fig_p013_10.png] view at source ↗
Figure 11
Figure 11. Figure 11: Dependence of the mean impact parameter on centrality for various methods. [PITH_FULL_IMAGE:figures/full_fig_p013_11.png] view at source ↗
read the original abstract

Collision centrality is a key parameter for studying nuclear matter properties, as it determines the initial interaction geometry and the size of the produced system. Accurate centrality determination is essential for comparing experimental data obtained from different experiments and for benchmarking against theoretical models. This work presents a modification of the approach for centrality determination using charged particle multiplicity based on Bayes' theorem. The proposed improvements enable an estimation of event registration efficiency as a function of the impact parameter. Furthermore, two approaches utilizing forward detectors are proposed: a two-dimensional method based on the combined analysis of track hit counts and spectator deposited energy in the Forward Hadron Calorimeter FHCal, and a method employing signals from the quartz hodoscope and FHCal. These methods were applied to data from the first physics run Xe+CsI of the BM@N experiment (Baryonic Matter at Nuclotron) with a xenon beam at the energy of 3.8 A GeV. A comparison of the developed methods with the classical Monte Carlo Glauber approach demonstrates agreement within 5% across all considered methods, confirming their reliability and mutual consistency. The use of forward detectors for centrality determination may serve as an independent tool for assessing the initial collision geometry and can reduce autocorrelation effects in studies of proton multiplicity fluctuations. The developed approaches can be employed for data processing in the BM@N experiment, as well as in other heavy-ion experiments at intermediate energies.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

0 major / 2 minor

Summary. The manuscript presents a modified Bayesian approach to centrality determination from charged-particle multiplicity that incorporates an impact-parameter-dependent event registration efficiency, along with two forward-detector methods (a 2-D combination of track-hit multiplicity and FHCal deposited energy, and a hodoscope-plus-FHCal signal combination). These are applied to the first-physics Xe+CsI run at 3.8 A GeV in BM@N; direct comparison with a classical Monte-Carlo Glauber reference yields agreement within 5 % for all three methods, which the authors interpret as confirmation of reliability and mutual consistency.

Significance. If the reported 5 % agreement is supported by the quantitative comparisons and efficiency parametrizations supplied in the full text, the work supplies practical, forward-detector-based centrality estimators that can serve as an independent cross-check and reduce autocorrelation biases in multiplicity-fluctuation analyses. The explicit algorithmic descriptions and the direct Glauber benchmark constitute clear strengths for an experiment-specific methods paper.

minor comments (2)
  1. [Abstract] Abstract: the statement of 'agreement within 5 %' would be strengthened by a parenthetical note on the metric used (e.g., mean relative difference in centrality percentiles) and whether uncertainties are included.
  2. [Section describing the modified Bayesian method] The efficiency-vs-b parametrization and the 2-D hit/energy mapping are central to the new methods; ensure that the corresponding figures include the full set of selection cuts applied to the data sample.

Simulated Author's Rebuttal

0 responses · 0 unresolved

We thank the referee for the positive assessment of the manuscript and the recommendation for minor revision. No specific major comments were provided in the report.

Circularity Check

0 steps flagged

No significant circularity; derivation is self-contained against external benchmark

full rationale

The paper's central result is an empirical agreement (within 5%) between three new centrality estimators (modified Bayesian multiplicity, 2D hit/energy mapping, and hodoscope/FHCal combination) and the classical Monte Carlo Glauber model on Xe+CsI data. The Glauber reference is an independent, externally established simulation framework whose inputs and assumptions are not derived from the present data or methods; the paper supplies explicit algorithmic descriptions, efficiency parametrizations, and direct comparison without any step that reduces a claimed prediction to a fitted parameter or self-citation chain. No self-definitional, fitted-input, or uniqueness-imported patterns appear in the derivation chain.

Axiom & Free-Parameter Ledger

0 free parameters · 1 axioms · 0 invented entities

Review limited to abstract; ledger reflects elements explicitly named: reliance on Bayes theorem for efficiency estimation and Glauber model as external benchmark.

axioms (1)
  • domain assumption The Monte Carlo Glauber model provides a reliable reference for collision geometry against which new methods can be validated.
    Invoked as the comparison standard for the 5% agreement claim.

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Reference graph

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