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arxiv: 2605.05936 · v1 · submitted 2026-05-07 · ⚛️ physics.ins-det · hep-ex· physics.app-ph· physics.data-an

Recognition: unknown

Analysis of Mixed Radiation Fields at the MoEDAL Experiment Based on Real-Time Data from a Timepix Detector Network

Benedikt Bergmann , Petr Burian , Josef Jane\v{c}ek , Claude Leroy , Petr M\'anek , James Pinfold , Stanislav Posp\'i\v{s}il , Richard Soluk
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Michal Suk
Authors on Pith no claims yet

Pith reviewed 2026-05-08 03:45 UTC · model grok-4.3

classification ⚛️ physics.ins-det hep-exphysics.app-phphysics.data-an
keywords Timepix detectorsMoEDAL experimentmixed radiation fieldsneutron fluencesLHCmagnetic monopoleshighly ionizing particlesspatial tracking
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The pith

Timepix detector network measures composition, energies, and directions of neutrons and hadrons in the MoEDAL area at the LHC.

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

The paper establishes that a network of Timepix silicon pixel detectors can deliver real-time data on the fluences, spectral properties, and directional distributions of fast neutrons, other hadrons, and highly ionizing particles around the MoEDAL experiment. This information is needed to quantify the background that can produce tracks in MoEDAL's passive nuclear track detectors indistinguishable from those expected from Dirac magnetic monopoles. The detectors work by recording cluster shapes and energy deposits in individual frames, which are then decomposed into particle types and trajectories. First results include maps across different locations in the experimental area and reconstructions of particle paths from single frames.

Core claim

The Timepix detector network enables real-time measurements of mixed radiation fields, including the composition, spectral properties, and directional characteristics of individual radiation components across different regions of the MoEDAL experimental area, with first results on spatial tracking capabilities.

What carries the argument

The Timepix hybrid silicon pixel detector network, which decomposes mixed fields of neutrons, hadrons, and highly ionizing particles by analyzing cluster shapes and energy deposits in real time.

If this is right

  • Neutron and hadron fluences can be quantified in real time at multiple points inside the MoEDAL experimental area.
  • Directional distributions of highly ionizing particles can be mapped to identify their sources.
  • Particle trajectories and energy-loss profiles can be reconstructed from individual detector frames.
  • Background for monopole searches in nuclear track detectors can be assessed by distinguishing particles that produce similar tracks.

Where Pith is reading between the lines

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

  • Continuous operation of the network could support decisions on when to run or pause passive detector exposures during high-background periods.
  • The same decomposition technique might be applied in other LHC regions where mixed radiation backgrounds affect precision measurements.
  • Pairing the measured spectra with detailed Monte Carlo models of the cavern could reduce remaining uncertainties in the particle-type assignment.

Load-bearing premise

Observed cluster shapes and energy deposits allow unambiguous separation of particle types and energies in the mixed field without significant misidentification or unaccounted systematic effects.

What would settle it

A dataset in which a large fraction of clusters produce ambiguous shapes that match two or more particle categories at comparable rates, causing the decomposition to yield inconsistent fluence values when cross-checked against independent monitors.

read the original abstract

The primary objective of this work is the determination of fluences and characteristics of fast neutrons, other hadrons, and highly ionizing particles in the environment of the MoEDAL experiment at the Large Hadron Collider. These particles constitute an experimental background for the passive Nuclear Track Detectors (NTDs) used by MoEDAL to search for tracks potentially produced by Dirac magnetic monopoles, in particular by particles indistinguishable in NTD from monopoles. The study is based on data acquired by the Timepix hybrid silicon pixel detector network, which represents the first and only active detector system installed and operated as part of the MoEDAL experiment from 2013 to 2018. The Timepix detector network enables real-time measurements of mixed radiation fields, including the composition, spectral properties, and directional characteristics of individual radiation components across different regions of the MoEDAL experimental area. The paper presents detailed results of the radiation field analysis with emphasis on neutrons and highly ionizing particles, including their directional distributions. The first results demonstrating the spatial tracking capabilities of the Timepix detectors are also reported, illustrating the reconstruction of particle direction and energy-loss profiles from individual detector frames.

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 / 2 minor

Summary. The paper describes the deployment and analysis of a Timepix hybrid silicon pixel detector network at the MoEDAL experiment (2013–2018) to measure mixed radiation fields in the LHC cavern. It claims to extract fluences, composition, spectral properties, and directional distributions of fast neutrons (via recoil protons), other hadrons, and highly ionizing particles as backgrounds to the passive NTDs used for monopole searches, together with first results on spatial tracking from individual frames.

Significance. If the cluster-based particle identification proves robust, the work supplies the first active, real-time radiation-field data complementing MoEDAL’s passive detectors, enabling better background characterization for the monopole search and demonstrating directional and tracking capabilities of Timepix in a high-radiation environment.

major comments (1)
  1. [Analysis and results sections (cluster decomposition and fluence extraction)] The central claim requires reliable attribution of observed clusters to neutrons (via recoil protons), charged hadrons, and highly ionizing particles based on morphology and energy deposit. The manuscript provides no confusion matrices, Monte Carlo closure tests, or in-situ validation against independent monitors (e.g., other LHC radiation monitors). This is load-bearing for all reported fluences, composition maps, spectra, and directional results.
minor comments (2)
  1. [Abstract] The abstract states the measurement goals and data period but contains no quantitative results, error budgets, or key numerical findings; adding a concise summary of the main fluence values and uncertainties would improve readability.
  2. [Methods and figures] Notation for cluster parameters (e.g., size, TOT, LET) should be defined consistently in the text and figure captions to avoid ambiguity when describing the classification criteria.

Simulated Author's Rebuttal

1 responses · 0 unresolved

We thank the referee for the careful and constructive review of our manuscript. The major comment identifies a key aspect of the analysis that requires clearer documentation. We respond point-by-point below and will revise the manuscript accordingly.

read point-by-point responses

  1. Referee: [Analysis and results sections (cluster decomposition and fluence extraction)] The central claim requires reliable attribution of observed clusters to neutrons (via recoil protons), charged hadrons, and highly ionizing particles based on morphology and energy deposit. The manuscript provides no confusion matrices, Monte Carlo closure tests, or in-situ validation against independent monitors (e.g., other LHC radiation monitors). This is load-bearing for all reported fluences, composition maps, spectra, and directional results.

    Authors: We agree that explicit validation strengthens the reliability of the reported fluences and directional distributions. The cluster attribution in the manuscript follows morphological and energy-deposition criteria established in prior Timepix literature for mixed radiation fields, with parameters tuned on calibration data from known neutron and hadron sources. However, the current text does not present confusion matrices, dedicated Monte Carlo closure tests, or direct comparisons to other LHC monitors. In the revised manuscript we will add: (i) a dedicated subsection detailing the classification algorithm and its calibration sources, (ii) quantitative estimates of identification uncertainties derived from the available calibration datasets, and (iii) any feasible cross-checks against published LHC radiation-monitor data for the same periods. These additions will clarify the robustness of the results while preserving the original analysis. revision: yes

Circularity Check

0 steps flagged

No circularity: empirical data extraction from detector measurements

full rationale

The paper reports experimental results from Timepix detector data on radiation fluences, composition, spectra, and directions in the MoEDAL area. No derivation chain exists that reduces a claimed prediction or first-principles result to fitted parameters or self-citations by construction. Cluster morphology and energy deposit analysis is presented as a direct measurement technique applied to observed frames, without equations that define outputs as inputs or rename fitted quantities as predictions. Self-citations, if present, support instrument calibration or prior detector characterization but do not bear the load of the central claims, which remain falsifiable against independent monitors. The analysis is self-contained as an empirical report.

Axiom & Free-Parameter Ledger

0 free parameters · 1 axioms · 0 invented entities

Only the abstract is available; therefore the full set of calibration constants, selection cuts, and response models cannot be audited. The work appears to rest on standard silicon-detector response assumptions rather than new postulates.

axioms (1)
  • domain assumption Timepix cluster morphology and energy deposition allow reliable separation of neutrons, hadrons, and highly ionizing particles in mixed fields
    Invoked implicitly by the claim that fluences and directional distributions can be extracted from the data.

pith-pipeline@v0.9.0 · 5554 in / 1206 out tokens · 68941 ms · 2026-05-08T03:45:26.238788+00:00 · methodology

discussion (0)

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Reference graph

Works this paper leans on

13 extracted references · 10 canonical work pages

  1. [1]

    Acharya, B.,et al.: The physics programme of the MoEDAL experiment at the LHC. Int. J. Mod. Phys. A29(23), 1430050 (2014) https://doi.org/10.1142/ S0217751X14300506

    2014

  2. [2]

    Llopart, X.,et al.: Timepix, a 65k programmable pixel readout chip for arrival time, energy and/or photon counting measurements. Nucl. Instrum. Methods Phys. Res. Sect. A581(1-2), 485–494 (2007) https://doi.org/10.1016/j.nima. 2007.08.079

    work page doi:10.1016/j.nima 2007

  3. [3]

    Technical report, CERN (2013)

    Campbell, M., et al.: Analysis of the radiation field in ATLAS using 2008- 2011 data from the ATLAS-MPX network. Technical report, CERN (2013). ATL-COM-GEN-2012-010. https://cds.cern.ch/record/1544435

    work page arXiv 2008

  4. [4]

    Heijne, E.,et al.: Comparison of measurement and simulation of ATLAS cavern radiation background. J. Instrum.17(01), 01027 (2022) https://doi.org/10.1088/ 1748-0221/17/01/P01027

    2022

  5. [5]

    Jak˚ ubek, J.: Precise energy calibration of pixel detector working in time-over- threshold mode. Nucl. Instrum. Methods Phys. Res. Sect. A633, 262–266 (2011) https://doi.org/10.1016/j.nima.2010.06.183

    work page doi:10.1016/j.nima.2010.06.183 2011

  6. [6]

    Hol´ y, T.,et al.: Pattern recognition of tracks induced by individual quanta of ionizing radiation in Medipix2 silicon detector. Nucl. Instrum. Methods Phys. Res. Sect. A591(1), 287–290 (2008) https://doi.org/10.1016/j.nima.2008.03.074

    work page doi:10.1016/j.nima.2008.03.074 2008

  7. [7]

    IEEE Trans

    Bergmann, B.,et al.: Ionizing energy depositions after fast neutron interactions in silicon. IEEE Trans. Nucl. Sci.63(4), 2372–2378 (2016) https://doi.org/10. 1109/TNS.2016.2574961 16

    work page arXiv 2016

  8. [8]

    Bergmann, B.,et al.: ATLAS-TPX: a two-layer pixel detector setup for neutron detection and radiation field characterization. J. Instrum.11(10), 10002–10002 (2016) https://doi.org/10.1088/1748-0221/11/10/P10002

    work page doi:10.1088/1748-0221/11/10/p10002 2016

  9. [9]

    Master’s thesis, Faculty of Electrical Engineering, Czech Technical University in Prague (2018)

    M´ anek, P.: Machine learning approach to ionizing particle recognition using hybrid active pixel detectors. Master’s thesis, Faculty of Electrical Engineering, Czech Technical University in Prague (2018). http://hdl.handle.net/10467/76434

    2018

  10. [10]

    Bergmann, B.,et al.: 3D track reconstruction capability of a silicon hybrid active pixel detector. Eur. Phys. J. C77(6), 421 (2017) https://doi.org/10.1140/epjc/ s10052-017-4993-4

    work page doi:10.1140/epjc/ 2017

  11. [11]

    IEEE Trans

    Bergmann, B.,et al.: Characterization of the radiation field in the ATLAS exper- iment with Timepix detectors. IEEE Trans. Nucl. Sci.66(7), 1861–1869 (2019) https://doi.org/10.1109/TNS.2019.2918365

    work page doi:10.1109/tns.2019.2918365 2019

  12. [12]

    Maezawa, F

    Bergmann, B.,et al.: Timepix3 as solid-state time-projection chamber in particle and nuclear physics. PoSICHEP2020, 720 (2021) https://doi.org/10.22323/1. 390.0720

    work page doi:10.22323/1 2021

  13. [13]

    Duda, R.O., Hart, P.E.: Use of the Hough transformation to detect lines and curves in pictures. Commun. ACM15(1), 11–15 (1972) https://doi.org/10.1145/ 361237.361242 17

    work page arXiv 1972