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arxiv: 2605.03048 · v1 · submitted 2026-05-04 · ✦ hep-ex

Recognition: unknown

Improved muon energy estimation using a detailed model of multiple Coulomb scattering in the MicroBooNE LArTPC

MicroBooNE collaboration: P. Abratenko , D. Andrade Aldana , J. Asaadi , A. Ashkenazi , S. Balasubramanian , B. Baller , A. Barnard , G. Barr
show 183 more authors
D. Barrow J. Barrow V. Basque J. Bateman B. Behera O. Benevides Rodrigues S. Berkman A. Bhat M. Bhattacharya V. Bhelande A. Binau M. Bishai A. Blake B. Bogart T. Bolton M. B. Brunetti L. Camilleri D. Caratelli F. Cavanna G. Cerati A. Chappell Y. Chen J. M. Conrad M. Convery L. Cooper-Troendle J. I. Crespo-Anadon R. Cross M. Del Tutto S. R. Dennis P. Detje R. Diurba Z. Djurcic K. Duffy S. Dytman B. Eberly P. Englezos A. Ereditato J. J. Evans C. Fang B. T. Fleming W. Foreman D. Franco A. P. Furmanski F. Gao D. Garcia Gamez S. Gardiner G. Ge S. Gollapinni E. Gramellini P. Green H. Greenlee L. Gu W. Gu R. Guenette L. Hagaman M. D. Handley M. Harrison S. Hawkins A. Hergenhan O. Hen C. Hilgenberg G. A. Horton-Smith A. Hussain B. Irwin M. S. Ismail C. James X. Ji J. H. Jo R. A. Johnson A. Johnson D. Kalra G. Karagiorgi A. Kelly W. Ketchum M. Kirby T. Kobilarcik K. Kumar N. Lane J.-Y. Li Y. Li K. Lin B. R. Littlejohn L. Liu S. Liu W. C. Louis X. Luo T. Mahmud N. Majeed C. Mariani J. Marshall M. G. Manuel Alves D. A. Martinez Caicedo F. Martinez Lopez S. Martynenko A. Mastbaum I. Mawby N. McConkey B. McConnell L. Mellet J. Mendez J. Micallef A. Mogan T. Mohayai M. Mooney A. F. Moor C. D. Moore L. Mora Lepin M. A. Hernandez Morquecho M. M. Moudgalya S. Mulleriababu D. Naples A. Navrer Agasson N. Nayak M. Nebot-Guinot C. Nguyen L. Nguyen J. Nowak N. Oza O. Palamara N. Pallat V. Paolone A. Papadopoulou V. Papavassiliou H. B. Parkinson S. F. Pate N. Patel Z. Pavlovic E. Piasetzky K. Pletcher I. Pophale X. Qian J. L. Raaf V. Radeka A. Rafique M. Reggiani-Guzzo J. Rodriguez Rondon M. Rosenberg M. Ross-Lonergan I. Safa C. Sauer D. W. Schmitz A. Schukraft W. Seligman M. H. Shaevitz R. Sharankova J. Shi L. Silva E. L. Snider S. Soldner-Rembold J. Spitz M. Stancari J. St. John T. Strauss A. M. Szelc N. Taniuchi K. Terao C. Thorpe D. Torbunov D. Totani M. Toups A. Trettin Y.-T. Tsai J. Tyler M. A. Uchida T. Usher B. Viren J. Wang L. Wang M. Weber H. Wei A. J. White S. Wolbers T. Wongjirad K. Wresilo W. Wu E. Yandel T. Yang L. E. Yates H. W. Yu G. P. Zeller J. Zennamo C. Zhang Y. Zhang
Authors on Pith no claims yet

Pith reviewed 2026-05-08 02:05 UTC · model grok-4.3

classification ✦ hep-ex
keywords muon energy estimationmultiple Coulomb scatteringMicroBooNELArTPCneutrino detectorstrack reconstructionenergy resolution
0
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The pith

A refined model of multiple Coulomb scattering improves muon energy estimates in the MicroBooNE liquid argon detector.

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

The paper introduces several refinements to an existing method that estimates muon energy from the deflections caused by multiple Coulomb scattering along the track. These changes better account for detector effects that were previously treated in a more approximate way. A reader would care because accurate muon energy reconstruction directly affects the ability to measure neutrino interaction energies and cross sections in liquid argon time projection chambers. The new estimator reports bias below 1 percent for fully contained tracks and below 2 percent for exiting tracks, with resolution between 4 and 17 percent depending on energy and containment, roughly twice as good as the prior version over the same range. Validation against simulated data and goodness-of-fit tests on real data support that the improvements hold in practice.

Core claim

By implementing a more detailed multiple Coulomb scattering model that incorporates detector non-idealizations, the muon energy estimator achieves an estimated bias within 1 percent and resolution from 4.3 to 10 percent for contained events, and bias under 2 percent with resolution from 7 to 17 percent for exiting events with at least one meter of track, both over 0.1 to 2 GeV; these figures represent clear gains over previous MicroBooNE MCS estimators that showed twice the resolution and 20 percent bias in the same energy window.

What carries the argument

The detailed multiple Coulomb scattering model that tracks deflections along the muon path while including detector non-idealizations.

If this is right

  • Neutrino energy reconstruction in MicroBooNE analyses gains reduced bias and improved resolution for muon tracks.
  • Data-model agreement for muon tracks improves across the tested energy range.
  • The estimator can be applied to both contained and exiting tracks without large additional corrections.
  • Similar refinements could be tested on other liquid argon detectors that record muon tracks.

Where Pith is reading between the lines

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

  • Lower bias in muon energy would propagate to smaller systematic uncertainties on neutrino oscillation parameters extracted from the same data set.
  • The method's performance on exiting tracks suggests it could be useful in experiments where many muons leave the detector volume.
  • If the model continues to match data in future runs, it could serve as a cross-check for other energy estimation techniques such as calorimetry.

Load-bearing premise

The Monte Carlo simulation faithfully reproduces all relevant detector effects and physics processes so that the reported bias and resolution numbers apply to actual data.

What would settle it

A comparison on fully contained muon tracks where the estimated energy from scattering is checked against the independent calorimetric energy measurement and shows systematic deviations larger than 1 percent.

read the original abstract

We present an improved technique for estimating a muon's energy by measuring the deflections along its path inside the MicroBooNE detector from multiple Coulomb scattering (MCS). This approach implements several innovations that better capture detector non-idealizations compared to previous MCS-based muon energy estimators. As a result, it achieves improved resolution, reduced bias, and better data-model agreement. Using model simulation, for fully contained events the estimated bias is within 1% and the estimated resolution varies from 4.3% to 10% as muon energy increases from 0.1 GeV to 2 GeV. For events with particles exiting the detector volume, at least a meter of reconstructed muon track, and a muon energy below 2 GeV, the estimated bias is less than 2% and the estimated resolution varies from 7% to 17% over muon energy. These demonstrate significant improvements over the performance of previous work using an MCS-based energy estimator at MicroBooNE, which achieves twice as large a resolution as well as a bias of 20% over the same energy region. Data-model goodness-of-fit studies are used to validate the estimator's performance on data, showing good agreement within model uncertainties.

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

1 major / 0 minor

Summary. The paper presents an improved muon energy estimator for the MicroBooNE LArTPC that uses multiple Coulomb scattering with a detailed model incorporating detector non-idealizations. Simulation studies report bias within 1% (fully contained) or <2% (exiting tracks) and resolution from 4.3-17% over 0.1-2 GeV, representing roughly a factor-of-two improvement over prior MCS estimators at MicroBooNE. Data-model agreement is validated via goodness-of-fit tests on reconstructed observables.

Significance. If the central claims hold, the work provides a concrete advance in scattering-based muon energy reconstruction for liquid-argon neutrino detectors. The reported gains in resolution and bias reduction, together with explicit handling of non-ideal detector effects, would directly benefit precision measurements of neutrino oscillations and cross sections at MicroBooNE and future LArTPC experiments. The simulation-based performance quantification and data-MC GOF validation constitute reproducible strengths of the manuscript.

major comments (1)
  1. Abstract and validation section: the headline bias (≤1-2 %) and resolution (4-17 %) figures are extracted exclusively from Monte Carlo events whose true energies are known. The only data-side check is a goodness-of-fit comparison between data and MC in a set of reconstructed observables that are not direct proxies for the muon energy scale or its resolution. An unaccounted mismatch in the detailed scattering or detector-response model could therefore shift the true (data) performance without failing the reported GOF test. A data-driven closure test on a subsample with independent energy information would be required to substantiate the performance claims on real data.

Simulated Author's Rebuttal

1 responses · 1 unresolved

We thank the referee for the positive evaluation of our work's significance and for the constructive major comment. We address it point by point below, with revisions to improve clarity on validation limitations.

read point-by-point responses

  1. Referee: Abstract and validation section: the headline bias (≤1-2 %) and resolution (4-17 %) figures are extracted exclusively from Monte Carlo events whose true energies are known. The only data-side check is a goodness-of-fit comparison between data and MC in a set of reconstructed observables that are not direct proxies for the muon energy scale or its resolution. An unaccounted mismatch in the detailed scattering or detector-response model could therefore shift the true (data) performance without failing the reported GOF test. A data-driven closure test on a subsample with independent energy information would be required to substantiate the performance claims on real data.

    Authors: We agree that the reported bias and resolution values are obtained from Monte Carlo where true energies are known; this is unavoidable in MicroBooNE because no independent, high-precision muon energy measurement exists for the selected sample on real data. The GOF tests are performed directly on the reconstructed scattering angles, track segments, and other inputs to the estimator itself, and they demonstrate agreement within the assigned model uncertainties. We have revised the validation section (and abstract) to explicitly state the reliance on simulation for quantitative performance metrics, to quantify the propagated model uncertainties on the energy estimate, and to discuss why a direct data-driven closure test cannot be performed with the current dataset. These changes make the validation strategy and its limitations transparent while preserving the strength of the MC-based results and the supporting GOF evidence. revision: partial

standing simulated objections not resolved
  • A data-driven closure test on a subsample with independent energy information, which is not available in the MicroBooNE dataset.

Circularity Check

0 steps flagged

No circularity in core derivation; minor self-citation of prior MicroBooNE MCS work is not load-bearing

full rationale

The estimator is built from a physics-based MCS model that incorporates detector effects; bias and resolution are measured by applying it to independent Monte Carlo events whose true energies are known by construction of the simulation. This is standard external validation, not a fit or self-definition of the reported metrics. Data validation uses GOF tests on reconstructed observables separate from the energy-scale quantities. Prior MicroBooNE MCS papers are cited for comparison only; the new performance claims rest on the updated model and MC results rather than reducing to those citations. No self-definitional, fitted-prediction, uniqueness-import, or ansatz-smuggling steps appear in the provided abstract or described chain.

Axiom & Free-Parameter Ledger

0 free parameters · 0 axioms · 0 invented entities

Abstract-only review provides no explicit list of free parameters, axioms, or new entities. The method rests on a detailed MCS model whose internal parameters and assumptions are not enumerated here.

pith-pipeline@v0.9.0 · 6542 in / 1277 out tokens · 88409 ms · 2026-05-08T02:05:35.043721+00:00 · methodology

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Reference graph

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