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REVIEW 3 major objections 4 minor 3 cited by

This review argues that the PYTHIA event generator has grown into facility-scale research infrastructure, embedded in the software chains of most major collider experiments and used by tens of thousands of physicists.

Reviewed by Pith at T0; open to challenge. T0 means a machine referee read the full paper against a public rubric. the ladder, T0–T4 →

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T0 review · deepseek-v4-flash

2026-08-02 19:32 UTC pith:EKKUQPEY

load-bearing objection A well-written, honest infrastructure manifesto whose central claim is plausible but rests on a citation proxy that overcounts experimental collaboration members, and whose classification pipeline is under-specified. the 3 major comments →

arxiv 2603.01744 v2 pith:EKKUQPEY submitted 2026-03-02 hep-ph

The PYTHIA Facility

Christian Bierlich , Leif L\"onnblad , Torbj\"orn Sj\"ostrand This is my paper
classification hep-ph
keywords PYTHIAMonte Carlo event generatorhigh-energy physics simulationresearch software infrastructurestring fragmentationcitation analysissoftware sustainabilityLarge Hadron Collider physics
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.

PYTHIA began in the late 1970s as a program for simulating high-energy particle collisions; this paper argues it has become something larger: a shared virtual-reality facility for particle physics, on par with accelerators and detectors as research infrastructure. To support the claim, the authors analyse nearly ten thousand papers citing the PYTHIA 8 manuals since 2018, involving more than 47,000 unique authors, and map the program's embedding in experimental frameworks, other event generators, tuning and validation tools, and machine-learning workflows. They describe an operational model that now resembles a small facility: a dozen authors, board governance, regular releases, an issue desk, summer schools, and community-engagement structures. The paper then draws the institutional conclusion that long-lived simulation software of this scale requires sustained funding, formal career paths, and a governance model, especially as the field moves toward the High-Luminosity LHC, the Electron-Ion Collider, and future circular colliders. A sympathetic reader is meant to accept that PYTHIA is infrastructure and should be supported as such.

Core claim

On its own terms, PYTHIA is no longer just an event generator but a 'widely embedded research infrastructure': a shared virtual-reality facility for particle physics. The evidence: PYTHIA 8 manuals cited ~10,000 times since 2018 across 9,641 works and 47,295 unique authors, over 40,000 lifetime. Subject and text-embedding analysis shows use across LHC physics, heavy ions, flavour, Higgs/electroweak, BSM, astroparticle, future colliders, and machine learning; an inventory shows PYTHIA embedded in dozens of tools as optional or structural backend. Value, the authors argue, lies in stability, interoperability, and continuity.

What carries the argument

The central object is the PYTHIA Monte Carlo event generator itself, with the string model of hadronization—the conversion of colour strings into hadrons—as its physical core. Around this core, the facility argument hangs on modular architecture: standard interfaces for steering, input and output; event-record formats; matching and merging between matrix elements and parton showers; event-by-event reweighting; and user hooks that let external code change the generation flow. These features let PYTHIA serve as a replaceable or structural backend in dozens of independent software products, turning a standalone program into shared infrastructure.

Load-bearing premise

The entire facility-scale conclusion rests on treating citations to the PYTHIA manuals as a faithful measure of real dependence on PYTHIA; the paper itself concedes that some papers cite without using and some use without citing, so the size of the user base could be substantially over- or understated.

What would settle it

Take a random sample of, say, 200 papers in the 2018+ citation corpus and read them to determine whether PYTHIA was actually used to generate simulated events or to validate results, as opposed to being cited as a background reference. If the active-use fraction is far below the level implied by the facility claim, the central argument fails; if it is high and indirect use through other programs is common, the argument is supported.

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

If this is right

  • If PYTHIA is facility-scale infrastructure, its maintenance can no longer be treated as an academic side project; it needs explicit governance, funding streams, and career ladders for its developers.
  • The modular-interface design implies that PYTHIA can remain a stable baseline while individual components (parton showers, hadronization, tunings) are replaced or emulated by newer tools or ML surrogates.
  • Event-by-event weight variations make systematic uncertainty evaluation cheaper and more reproducible, allowing many parameter variations to be derived from a single simulated sample, including after detector simulation.
  • The same infrastructure will be needed by the next generation of facilities—an electron-ion collider, the High-Luminosity LHC, and possible future circular colliders—which raises the stakes for long-term software sustainability.
  • Because the user base is split between very large collaborations and small fast-moving groups, one-size-fits-all support will fail; the facility must maintain both stable production interfaces and rapid-prototyping flexibility.

Where Pith is reading between the lines

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

  • If the facility framing is accepted, a natural extension is that other long-lived simulation codes with similar integration patterns should also be evaluated as infrastructure, and the paper's citation-corpus method could be applied to them for comparison.
  • The paper's own evidence suggests that ML-based surrogates trained on PYTHIA output will increasingly treat PYTHIA as the reference standard; one consequence the authors leave implicit is that PYTHIA's long-term value may shift from predictive tool to benchmark dataset, which changes which features need the most investment.
  • A testable extension: instrument actual usage through opt-in telemetry or download analytics to cross-check the citation proxy; if real use of the program is much larger than the citation count, the facility claim is even stronger than the paper states.
  • The text-classification method (keyword scoring plus embedding centroids) could be validated by an independent reproducibility study in which another group re-derives the domain assignments from the same corpus, since the thresholds and keyword lists are described but not fully specified.

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. The paper argues that the Monte Carlo event generator PYTHIA should be regarded not merely as a program but as facility-scale research infrastructure: a shared 'virtual-reality facility' for high-energy physics and beyond. It traces the Lund-origin history, analyses the contemporary user base through citations to the PYTHIA 8 manuals (≈9,641 works and 47,295 unique authors since 2018, with lifetime manual citations exceeding 40,000), maps integrations into experimental frameworks and other generator ecosystems (Tables 1–2), and discusses operations, standards, training, sustainability, and future directions toward the HL-LHC, EIC, and FCC. The central claim is that the scale and diversity of use, together with deep embedding in production chains, justifies describing PYTHIA as infrastructure rather than as a useful program.

Significance. If the user-base and ecosystem claims are accepted, the paper provides a valuable and unusual case study of long-lived research software as scientific infrastructure. Its strengths include an honest historical account, a substantial and internally consistent citation corpus (the 6,412 arXiv-tagged works sum to the stated totals), a broad mapping of integration modes, and a timely discussion of sustainability, governance, and career paths for research-software stewards. The paper also offers concrete, falsifiable statements about user composition and domain diversity. The main risk is that the quantitative backbone — especially the 'tens of thousands of researchers' claim — rests on a citation proxy whose biases are acknowledged but not quantified or corrected.

major comments (3)
  1. [§3.1, Abstract, §5] The 'tens of thousands of researchers' claim is load-bearing for the facility thesis, but it is derived from 47,295 unique authors by counting full author lists of 9,641 citing works. The paper itself concedes that 'some papers in the corpus are citing Pythia without actually using it' and that some use is indirect 'without citing Pythia'. With 2,266 hep-ex papers in the corpus, many containing thousands of collaboration authors, the unique-author count almost certainly overstates the number of people who directly use PYTHIA. The authors should quantify this: e.g., report the distribution of author counts per paper, show a sensitivity analysis excluding large-collaboration papers, or use a more conservative definition of 'publishing user base'. Without such an analysis, the abstract's 'serving tens of thousands of researchers' is not established.
  2. [§3.1, Fig. 6] The text-classification pipeline that produces Fig. 6 is under-specified and therefore not reproducible. The keyword lists are only described as 'specified by us'; the hashing scheme is 'fixed, deterministic' but unnamed; the centroid-assignment threshold is 'sufficiently similar' without a value; the iteration stopping rule is not given; and validation is by unspecified 'manual inspection' of representative papers. Since Fig. 6 is used to support the claim that PYTHIA serves diverse communities and that 'support cannot be optimized for a single typical workflow', the classification procedure is load-bearing. The authors should publish the keyword sets, the hash/embedding implementation, the similarity threshold, the iteration procedure, and a quantitative validation or at least the full confusion matrix on a labeled subsample.
  3. [§3.4, Tables 1–2] The ecosystem tables are presented as 'known by us' and 'representative', but the inclusion criteria are not stated. For example, Table 1 lists many generators but not others, and Table 2 covers major LHC and non-LHC frameworks while noting that 'several smaller or emerging frameworks' are omitted. The facility argument relies in part on the breadth of these integrations. The authors should state the systematic search or selection procedure (e.g., citation queries, personal knowledge, maintenance status, or release date cutoff) and, ideally, provide a machine-readable list with versions and evidence of integration. This would allow readers to judge completeness and would strengthen rather than weaken the ecosystem claim.
minor comments (4)
  1. [Abstract] The abstract contains a duplicated paragraph beginning 'We discuss the operational model...' — the same text appears twice. Please remove the duplicate.
  2. [§3.1, Fig. 7] Typographical errors: 'detetector' in the Fig. 7 axis label, and 'excotica' in Fig. 6. Also, 'This classification gives are more detailed overview' in §3.1 should read 'gives a more detailed overview'.
  3. [§4.5] Minor style: 'Moores Law' should be 'Moore's law'; 'Maintainence' in §4.4 should be 'Maintenance'. Also, the running header/title contains inconsistent spacing, e.g., 'Pythiatoday' and 'Pythiais' in §3.
  4. [Ref. [130]] Reference [130] is listed as 'Yannick, M.: Private Communication'. For a published arXiv paper this is unusually opaque; if the communication is not publicly documented, consider removing the citation or replacing it with a publicly available source.

Circularity Check

0 steps flagged

No circular derivation: the facility claim rests on disclosed bibliometric and ecosystem evidence, not on a self-referential fit.

full rationale

The paper contains no equation-level derivation chain that reduces to fitted inputs; it is a descriptive/historical and bibliometric analysis. The central claim—that PYTHIA functions as facility-scale software infrastructure—is supported by (i) citation counts to the PYTHIA manuals, (ii) a text-based classification of the citing corpus, and (iii) an inventory of external integrations (Tables 1–2). None of these are defined in terms of the conclusion. The user-base count is explicitly labeled a proxy: 'This is taken as a proxy of the publishing user base, i.e. the number of scientists publishing papers depending on Pythia,' with the over- and under-counting biases stated immediately afterward. The phrase 'serving tens of thousands of researchers' is a direct paraphrase of the 47,295 unique-author count rather than a prediction derived from a model, so there is no by-construction equivalence between an input and an output. The domain classification uses author-specified keywords and a deterministic hashing/cosine-similarity procedure, but the thresholds are not fitted to force the Figure 6 result; it is a standard clustering exercise. Self-citations occur (e.g., ref. [126] for the first implementation of parton-shower weight variations), but these are historical priority claims and are not load-bearing for the facility conclusion. The integration inventory relies on externally developed, independently published frameworks (Athena, CMSSW, Rivet, HepMC, etc.), providing independent support. The paper's own admitted limitations—proxy noise, incomplete enumeration of downstream uses ('known by us')—are measurement caveats, not circularity. Accordingly, no significant circularity is found.

Axiom & Free-Parameter Ledger

4 free parameters · 4 axioms · 0 invented entities

The paper makes no physics derivation, so its ledger is methodological. The user-base numbers rest on a citation-to-usage proxy (acknowledged noisy), author-defined keyword domains, an unspecified hashed-embedding scheme, an unquantified centroid threshold, and a chosen citation window; none is externally pinned or released. No new physical entities are introduced; the 'facility' is an interpretive label for existing software. The self-referential framing — authors measuring and interpreting their own infrastructure's importance — is a transparency concern, not a derivation-circularity issue.

free parameters (4)
  • Domain keyword sets
    In §3.1 the domain keyword lists are 'specified by us' and never published; they drive the Figure 6 classification.
  • Centroid-assignment similarity threshold = not stated
    Papers are assigned to the nearest domain centroid when 'sufficiently similar'; the threshold is never quantified (§3.1).
  • Hashed term-frequency embedding scheme = not stated (hash dimension/function unnamed)
    The vector representation uses a 'fixed, deterministic hashing scheme' with logarithmic frequency scaling; the exact scheme determines the clusters (§3.1).
  • Citation window and manual selection = 2018–2026; manuals [1], [4], [5]
    The headline numbers (9,641 works; 47,295 authors) depend on the chosen window and the choice of three manuals to track (§3.1).
axioms (4)
  • domain assumption Citations to the PYTHIA manuals are an adequate proxy for usage
    Underpins the entire user-base analysis; the paper acknowledges both miscitation and uncited indirect use (§3.1).
  • domain assumption Hashed term-frequency vectors with cosine similarity capture a paper's scientific domain
    Standard text-mining assumption; no hyperparameter or stability validation is reported (§3.1).
  • domain assumption Author-assigned arXiv categories are meaningful classification labels
    Used as the backbone of Figures 5 and 7 (§3.1).
  • ad hoc to paper The three-prong model (theory–software–experiment) is the correct decomposition of the facility
    The organizing 'facility at the intersection of three prongs' (§1, Fig. 2) is asserted, not derived; it shapes which evidence is foregrounded.

pith-pipeline@v1.3.0-alltime-deepseek · 27975 in / 19411 out tokens · 179718 ms · 2026-08-02T19:32:09.357551+00:00 · methodology

0 comments
read the original abstract

The development and operation of large-scale particle physics facilities rely not only on accelerators and detectors, but also on sustained, high-precision simulation infrastructure. Originating in Lund in the late 1970s and continuously developed in Sweden for nearly five decades, PYTHIA has evolved into one of the most widely used Monte Carlo event generators in high-energy physics. Today it functions as a facility-scale software infrastructure underpinning the physics programmes of major international experiments, including those at the Large Hadron Collider, and plays a central role in validation, tuning, and uncertainty evaluation. In this article, we present PYTHIA as a Swedish contribution to big science facilities. We outline its historical development, analyze its contemporary user base through citation and text-based studies, and map its integration across experimental frameworks, generator ecosystems, validation infrastructures, and emerging machine-learning workflows. These analyses show that PYTHIA We discuss the operational model and sustainability challenges associated with maintaining long-lived research software at facility scale. As particle physics moves toward the High-Luminosity LHC era and future facilities such as the EIC and FCC, continued investment in robust, interoperable simulation infrastructure remains essential. We discuss the operational model and sustainability challenges associated with maintaining long-lived research software at facility scale. As particle physics moves toward the High-Luminosity LHC era and future facilities such as the EIC and FCC, continued investment in robust, interoperable simulation infrastructure remains essential.

discussion (0)

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Forward citations

Cited by 3 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. MAGE-HEP: Monte Carlo Analysis and Graphical Environment for High-Energy Physics

    hep-ph 2026-05 unverdicted novelty 5.0

    MAGE-HEP introduces a GUI-driven workflow environment for reproducible Monte Carlo analyses in high-energy physics organized by project-study-run hierarchy.

  2. Inferring identified hadron production in $pp$ collisions with physics-informed machine learning at the LHC

    hep-ph 2026-05 unverdicted novelty 5.0

    A physics-informed neural network infers pT spectra of pi, K, p, Lambda, and Ks in unmeasured rapidity regions from PYTHIA8 pp collisions at 13.6 TeV, achieving 1.5-5.83% yield uncertainties while reproducing yield ra...

  3. Open LHC Monte Carlo Event Generation

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Reference graph

Works this paper leans on

131 extracted references · 12 canonical work pages · cited by 3 Pith papers

  1. [1]

    SciPost Phys

    Bierlich, C.,et al.: A comprehensive guide to the physics and usage of PYTHIA 8.3. SciPost Phys. Codeb.2022, 8 (2022) https://doi.org/10.21468/ SciPostPhysCodeb.8 arXiv:2203.11601 [hep-ph]

    Pith/arXiv arXiv 2022

  2. [2]

    JHEP05, 026 (2006) https://doi.org/10.1088/1126-6708/2006/05/026 arXiv:hep-ph/0603175

    Sjostrand, T., Mrenna, S., Skands, P.Z.: PYTHIA 6.4 Physics and Man- ual. JHEP05, 026 (2006) https://doi.org/10.1088/1126-6708/2006/05/026 arXiv:hep-ph/0603175

    Pith/arXiv arXiv 2006

  3. [3]

    Com- put

    Sj¨ ostrand, T.: The PYTHIA Event Generator: Past, Present and Future. Com- put. Phys. Commun.246, 106910 (2020) https://doi.org/10.1016/j.cpc.2019. 106910 arXiv:1907.09874 [hep-ph]

    Pith/arXiv arXiv 2020

  4. [4]

    Sj¨ ostrand, T., Ask, S., Christiansen, J.R., Corke, R., Desai, N., Ilten, P., Mrenna, S., Prestel, S., Rasmussen, C.O., Skands, P.Z.: An introduction to PYTHIA 8.2. Comput. Phys. Commun.191, 159–177 (2015) https://doi.org/10.1016/j.cpc. 2015.01.024 arXiv:1410.3012 [hep-ph]

    Pith/arXiv arXiv 2015

  5. [5]

    Sj¨ ostrand, T., Mrenna, S., Skands, P.Z.: A Brief Introduction to PYTHIA 8.1. Comput. Phys. Commun.178, 852–867 (2008) https://doi.org/10.1016/j.cpc. 2008.01.036 arXiv:0710.3820 [hep-ph]

    Pith/arXiv arXiv 2008

  6. [6]

    Pythia Collaboration: Guidelines for Code Contributions and Authorship. Website. https://pythia.org/guidelines/

  7. [7]

    Bierlich, C., et al.: The Pythia public gitlab repository. Website. https://gitlab. com/Pythia8

  8. [8]

    Seymour, M., et al.: The MCnet Collaboration. Website. https://montecarlonet. org/

  9. [9]

    JHEP12, 156 (2024) https://doi.org/10.1007/JHEP12(2024)156 arXiv:2410.22148 [hep-ph]

    Bothmann, E.,et al.: Event generation with Sherpa 3. JHEP12, 156 (2024) https://doi.org/10.1007/JHEP12(2024)156 arXiv:2410.22148 [hep-ph]

    Pith/arXiv arXiv 2024

  10. [10]

    Bellm, J., et al.: The Physics of Herwig 7 (2025) arXiv:2512.16645 [hep-ph]

    arXiv 2025

  11. [11]

    JHEP07, 079 (2014) https://doi.org/10.1007/ JHEP07(2014)079 arXiv:1405.0301 [hep-ph]

    Alwall, J., Frederix, R., Frixione, S., Hirschi, V., Maltoni, F., Mattelaer, O., 30 Shao, H.-S., Stelzer, T., Torrielli, P., Zaro, M.: The automated computation of tree-level and next-to-leading order differential cross sections, and their matching to parton shower simulations. JHEP07, 079 (2014) https://doi.org/10.1007/ JHEP07(2014)079 arXiv:1405.0301 [hep-ph]

    Pith/arXiv arXiv 2014

  12. [12]

    JHEP11, 070 (2007) https: //doi.org/10.1088/1126-6708/2007/11/070 arXiv:0709.2092 [hep-ph]

    Frixione, S., Nason, P., Oleari, C.: Matching NLO QCD computations with Parton Shower simulations: the POWHEG method. JHEP11, 070 (2007) https: //doi.org/10.1088/1126-6708/2007/11/070 arXiv:0709.2092 [hep-ph]

    Pith/arXiv arXiv 2007

  13. [13]

    Belyaev, A., Christensen, N.D., Pukhov, A.: CalcHEP 3.4 for collider physics within and beyond the Standard Model. Comput. Phys. Commun.184, 1729– 1769 (2013) https://doi.org/10.1016/j.cpc.2013.01.014 arXiv:1207.6082 [hep- ph]

    Pith/arXiv arXiv 2013

  14. [14]

    JHEP07, 001 (2003) https://doi.org/10.1088/1126-6708/2003/07/001 arXiv:hep-ph/0206293

    Mangano, M.L., Moretti, M., Piccinini, F., Pittau, R., Polosa, A.D.: ALPGEN, a generator for hard multiparton processes in hadronic collisions. JHEP07, 001 (2003) https://doi.org/10.1088/1126-6708/2003/07/001 arXiv:hep-ph/0206293

    Pith/arXiv arXiv 2003

  15. [15]

    Shao, H.-S.: HELAC-Onia 2.0: an upgraded matrix-element and event generator for heavy quarkonium physics. Comput. Phys. Commun.198, 238–259 (2016) https://doi.org/10.1016/j.cpc.2015.09.011 arXiv:1507.03435 [hep-ph]

    Pith/arXiv arXiv 2016

  16. [16]

    JHEP09, 120 (2013) https://doi.org/10.1007/JHEP09(2013)120 arXiv:1211.7049 [hep-ph]

    Alioli, S., Bauer, C.W., Berggren, C.J., Hornig, A., Tackmann, F.J., Vermilion, C.K., Walsh, J.R., Zuberi, S.: Combining Higher-Order Resummation with Mul- tiple NLO Calculations and Parton Showers in GENEV A. JHEP09, 120 (2013) https://doi.org/10.1007/JHEP09(2013)120 arXiv:1211.7049 [hep-ph]

    Pith/arXiv arXiv 2013

  17. [17]

    JHEP10, 155 (2012) https://doi.org/10.1007/JHEP10(2012)155 arXiv:1206.3572 [hep-ph]

    Hamilton, K., Nason, P., Zanderighi, G.: MINLO: Multi-Scale Improved NLO. JHEP10, 155 (2012) https://doi.org/10.1007/JHEP10(2012)155 arXiv:1206.3572 [hep-ph]

    Pith/arXiv arXiv 2012

  18. [18]

    JHEP09, 074 (2018) https: //doi.org/10.1007/JHEP09(2018)074 arXiv:1712.00178 [hep-ph]

    Andersen, J.R., Brooks, H.M., L¨ onnblad, L.: Merging High Energy with Soft and Collinear Logarithms using HEJ and PYTHIA. JHEP09, 074 (2018) https: //doi.org/10.1007/JHEP09(2018)074 arXiv:1712.00178 [hep-ph]

    Pith/arXiv arXiv 2018

  19. [19]

    Kilian, W., Ohl, T., Reuter, J.: WHIZARD: Simulating Multi-Particle Processes at LHC and ILC. Eur. Phys. J. C71, 1742 (2011) https://doi.org/10.1140/epjc/ s10052-011-1742-y arXiv:0708.4233 [hep-ph]

    Pith/arXiv arXiv 2011

  20. [20]

    Landsberg, G.L.: Black holes at future colliders and in cosmic rays. Eur. Phys. J. C33, 927–931 (2004) https://doi.org/10.1140/epjcd/s2003-03-1108-5 arXiv:hep-ex/0310034

    Pith/arXiv arXiv 2004

  21. [21]

    JHEP08, 033 (2003) https://doi.org/10.1088/1126-6708/2003/08/ 033 arXiv:hep-ph/0307305 31

    Harris, C.M., Richardson, P., Webber, B.R.: CHARYBDIS: A Black hole event generator. JHEP08, 033 (2003) https://doi.org/10.1088/1126-6708/2003/08/ 033 arXiv:hep-ph/0307305 31

    Pith/arXiv arXiv 2003

  22. [22]

    Cavaglia, M., Godang, R., Cremaldi, L., Summers, D.: Catfish: A Monte Carlo simulator for black holes at the LHC. Comput. Phys. Commun.177, 506–517 (2007) https://doi.org/10.1016/j.cpc.2007.05.011 arXiv:hep-ph/0609001

    Pith/arXiv arXiv 2007

  23. [23]

    A black-hole event generator with rotation, recoil, split branes, and brane tension

    Dai, D.-C., Issever, C., Rizvi, E., Starkman, G., Stojkovic, D., Tseng, J.: Manual of BlackMax. A black-hole event generator with rotation, recoil, split branes, and brane tension. Version 2.02. Comput. Phys. Commun.236, 285–301 (2019) https://doi.org/10.1016/j.cpc.2018.10.021 arXiv:0902.3577 [hep-ph]

    Pith/arXiv arXiv 2019

  24. [24]

    Gingrich, D.M.: Monte Carlo event generator for black hole production and decay in proton-proton collisions. Comput. Phys. Commun.181, 1917–1924 (2010) https://doi.org/10.1016/j.cpc.2010.07.027 arXiv:0911.5370 [hep-ph]

    Pith/arXiv arXiv 1917

  25. [25]

    Lonnblad, L.: ARIADNE version 4: A Program for simulation of QCD cascades implementing the color dipole model. Comput. Phys. Commun.71, 15–31 (1992) https://doi.org/10.1016/0010-4655(92)90068-A

    doi:10.1016/0010-4655(92)90068-a 1992

  26. [26]

    Kato, K., Munehisa, T.: NLLjet : A Monte Carlo code for e+ e- QCD jets includ- ing next-to-leading order terms. Comput. Phys. Commun.64, 67–97 (1991) https://doi.org/10.1016/0010-4655(91)90051-L

    work page doi:10.1016/0010-4655(91)90051-l 1991

  27. [27]

    Nagy, Z., Soper, D.E.: Jets and threshold summation in Deductor. Phys. Rev. D98(1), 014035 (2018) https://doi.org/10.1103/PhysRevD.98.014035 arXiv:1711.02369 [hep-ph]

    Pith/arXiv arXiv 2018

  28. [28]

    Jung, H.,et al.: The CCFM Monte Carlo generator CASCADE version 2.2.03. Eur. Phys. J. C70, 1237–1249 (2010) https://doi.org/10.1140/epjc/ s10052-010-1507-z arXiv:1008.0152 [hep-ph]

    Pith/arXiv arXiv 2010

  29. [29]

    SciPost Phys

    Beekveld, M.,et al.: Introduction to the PanScales framework, ver- sion 0.1. SciPost Phys. Codeb.2024, 31 (2024) https://doi.org/10.21468/ SciPostPhysCodeb.31 arXiv:2312.13275 [hep-ph]

    Pith/arXiv arXiv 2024

  30. [30]

    JHEP10, 091 (2023) https://doi.org/10

    Herren, F., H¨ oche, S., Krauss, F., Reichelt, D., Schoenherr, M.: A new approach to color-coherent parton evolution. JHEP10, 091 (2023) https://doi.org/10. 1007/JHEP10(2023)091 arXiv:2208.06057 [hep-ph]

    Pith/arXiv arXiv 2023

  31. [31]

    Ingelman, G., Edin, A., Rathsman, J.: LEPTO 6.5: A Monte Carlo gen- erator for deep inelastic lepton - nucleon scattering. Comput. Phys. Com- mun.101, 108–134 (1997) https://doi.org/10.1016/S0010-4655(96)00157-9 arXiv:hep-ph/9605286

    Pith/arXiv arXiv 1997

  32. [32]

    Jung, H.: Hard diffractive scattering in high-energy e p collisions and the Monte Carlo generator RAPGAP. Comput. Phys. Commun.86, 147–161 (1995) https: //doi.org/10.1016/0010-4655(94)00150-Z

    work page doi:10.1016/0010-4655(94)00150-z 1995

  33. [33]

    Bravar, A., Kurek, K., Windmolders, R.: POLDIS: A Monte Carlo for POLarized 32 (semiinclusive) deep inelastic scattering. Comput. Phys. Commun.105, 42–61 (1997) https://doi.org/10.1016/S0010-4655(97)00063-5 arXiv:hep-ph/9704313

    Pith/arXiv arXiv 1997

  34. [34]

    Charchula, K., Schuler, G.A., Spiesberger, H.: Combined QED and QCD radia- tive effects in deep inelastic lepton - proton scattering: The Monte Carlo generator DJANGO6. Comput. Phys. Commun.81, 381–402 (1994) https: //doi.org/10.1016/0010-4655(94)90086-8

    work page doi:10.1016/0010-4655(94)90086-8 1994

  35. [35]

    Chang, W., Aschenauer, E.-C., Baker, M.D., Jentsch, A., Lee, J.-H., Tu, Z., Yin, Z., Zheng, L.: Benchmark eA generator for leptoproduction in high-energy lepton-nucleus collisions. Phys. Rev. D106(1), 012007 (2022) https://doi.org/ 10.1103/PhysRevD.106.012007 arXiv:2204.11998 [physics.comp-ph]

    Pith/arXiv arXiv 2022

  36. [36]

    Nilsson-Almqvist, B., Stenlund, E.: Interactions Between Hadrons and Nuclei: The Lund Monte Carlo, Fritiof Version 1.6. Comput. Phys. Commun.43, 387 (1987) https://doi.org/10.1016/0010-4655(87)90056-7

    doi:10.1016/0010-4655(87)90056-7 1987

  37. [37]

    Gyulassy, M., Wang, X.-N.: HIJING 1.0: A Monte Carlo program for parton and particle production in high-energy hadronic and nuclear collisions. Comput. Phys. Commun.83, 307 (1994) https://doi.org/10.1016/0010-4655(94)90057-4 arXiv:nucl-th/9502021

    Pith/arXiv arXiv 1994

  38. [38]

    PoSHardProbes2018, 045 (2019) https: //doi.org/10.22323/1.345.0045 arXiv:1901.04220 [physics.comp-ph]

    B ´ ır´ o, G., Barnaf¨ oldi, G.G., Papp, G., Gyulassy, M., L´ evai, P., Wang, X.-N., Zhang, B.-W.: Introducing HIJING++: the Heavy Ion Monte Carlo Generator for the High-Luminosity LHC Era. PoSHardProbes2018, 045 (2019) https: //doi.org/10.22323/1.345.0045 arXiv:1901.04220 [physics.comp-ph]

    Pith/arXiv arXiv 2019

  39. [39]

    Lin, Z.-W., Ko, C.M., Li, B.-A., Zhang, B., Pal, S.: A Multi-phase transport model for relativistic heavy ion collisions. Phys. Rev. C72, 064901 (2005) https: //doi.org/10.1103/PhysRevC.72.064901 arXiv:nucl-th/0411110

    Pith/arXiv arXiv 2005

  40. [40]

    Petersen, H., Bleicher, M., Bass, S.A., Stocker, H.: UrQMD v2.3: Changes and Comparisons (2008) arXiv:0805.0567 [hep-ph]

    Pith/arXiv arXiv 2008

  41. [41]

    Zapp, K.C.: JEWEL 2.0.0: directions for use. Eur. Phys. J. C74(2), 2762 (2014) https://doi.org/10.1140/epjc/s10052-014-2762-1 arXiv:1311.0048 [hep-ph]

    Pith/arXiv arXiv 2014

  42. [42]

    Armesto, N., Cunqueiro, L., Salgado, C.A.: Q-PYTHIA: A Medium-modified implementation of final state radiation. Eur. Phys. J. C63, 679–690 (2009) https://doi.org/10.1140/epjc/s10052-009-1133-9 arXiv:0907.1014 [hep-ph]

    Pith/arXiv arXiv 2009

  43. [43]

    Sciarra, A., Elfner, H.: SMASH as an event generator for heavy-ion collisions. Front. in Phys.12, 1502621 (2024) https://doi.org/10.3389/fphy.2024.1502621 arXiv:2409.20024 [nucl-th]

    arXiv 2024

  44. [44]

    Putschke, J.H., et al.: The JETSCAPE framework (2019) arXiv:1903.07706 [nucl-th] 33

    Pith/arXiv arXiv 2019

  45. [45]

    Lei, A.-K., She, Z.-L., Yan, Y.-L., Zhou, D.-M., Zheng, L., Zhang, W.-C., Zheng, H., Bravina, L.V., Zabrodin, E.E., Sa, B.-H.: A brief introduction to PACIAE 4.0. Comput. Phys. Commun.310, 109520 (2025) https://doi.org/10.1016/j.cpc. 2025.109520 arXiv:2411.14255 [hep-ph]

    arXiv 2025

  46. [46]

    Lokhtin, I.P., Malinina, L.V., Petrushanko, S.V., Snigirev, A.M., Arsene, I., Tywoniuk, K.: Heavy ion event generator HYDJET++ (HYDrodynamics plus JETs). Comput. Phys. Commun.180, 779–799 (2009) https://doi.org/10.1016/ j.cpc.2008.11.015 arXiv:0809.2708 [hep-ph]

    Pith/arXiv arXiv 2009

  47. [47]

    Lokhtin, I.P., Snigirev, A.M.: A Model of jet quenching in ultrarelativistic heavy ion collisions and high-p(T) hadron spectra at RHIC. Eur. Phys. J. C45, 211– 217 (2006) https://doi.org/10.1140/epjc/s2005-02426-3 arXiv:hep-ph/0506189

    Pith/arXiv arXiv 2006

  48. [48]

    JHEP08, 103 (2011) https://doi.org/ 10.1007/JHEP08(2011)103 arXiv:1103.4321 [hep-ph]

    Flensburg, C., Gustafson, G., L¨ onnblad, L.: Inclusive and Exclusive Observables from Dipoles in High Energy Collisions. JHEP08, 103 (2011) https://doi.org/ 10.1007/JHEP08(2011)103 arXiv:1103.4321 [hep-ph]

    Pith/arXiv arXiv 2011

  49. [49]

    Renk, T.: Medium-modified Jet Shapes and other Jet Observables from in- medium Parton Shower Evolution. Phys. Rev. C80, 044904 (2009) https: //doi.org/10.1103/PhysRevC.80.044904 arXiv:0906.3397 [hep-ph]

    Pith/arXiv arXiv 2009

  50. [50]

    Harland-Lang, L.A., Khoze, V.A., Ryskin, M.G.: Exclusive LHC physics with heavy ions: SuperChic 3. Eur. Phys. J. C79(1), 39 (2019) https://doi.org/10. 1140/epjc/s10052-018-6530-5 arXiv:1810.06567 [hep-ph]

    Pith/arXiv arXiv 2019

  51. [51]

    Forthomme, L.: CepGen – A generic central exclusive processes event generator for hadron-hadron collisions. Comput. Phys. Commun.271, 108225 (2022) https: //doi.org/10.1016/j.cpc.2021.108225 arXiv:1808.06059 [hep-ph]

    arXiv 2022

  52. [52]

    Burmasov, N., Kryshen, E., Buehler, P., Lavicka, R.: Upcgen: A Monte Carlo simulation program for dilepton pair production in ultra-peripheral collisions of heavy ions. Comput. Phys. Commun.277, 108388 (2022) https://doi.org/10. 1016/j.cpc.2022.108388 arXiv:2111.11383 [hep-ph]

    arXiv 2022

  53. [53]

    In: International Conference on Advanced Monte Carlo for Radiation Physics, Particle Transport Simulation and Applications (MC 2000), pp

    Roesler, S., Engel, R., Ranft, J.: The Monte Carlo event generator DPMJET-III. In: International Conference on Advanced Monte Carlo for Radiation Physics, Particle Transport Simulation and Applications (MC 2000), pp. 1033–1038 (2000). https://doi.org/10.1007/978-3-642-18211-2 166

    work page doi:10.1007/978-3-642-18211-2 2000

  54. [54]

    Riehn, F., Engel, R., Fedynitch, A., Gaisser, T.K., Stanev, T.: Hadronic inter- action model Sibyll 2.3d and extensive air showers. Phys. Rev. D102(6), 063002 (2020) https://doi.org/10.1103/PhysRevD.102.063002 arXiv:1912.03300 [hep-ph]

    Pith/arXiv arXiv 2020

  55. [55]

    PoSICRC2025, 267 (2025) https:// 34 doi.org/10.22323/1.501.0267 arXiv:2508.08793 [astro-ph.HE]

    Alameddine, J.-M.,et al.: From collider to cosmic rays: Pythia 8/Angantyr for air shower simulations in CORSIKA 8. PoSICRC2025, 267 (2025) https:// 34 doi.org/10.22323/1.501.0267 arXiv:2508.08793 [astro-ph.HE]

    arXiv 2025

  56. [56]

    Bloor, S., Gonzalo, T.E., Scott, P., Chang, C., Raklev, A., Camargo-Molina, J.E., Kvellestad, A., Renk, J.J., Athron, P., Bal´ azs, C.: The GAMBIT Univer- sal Model Machine: from Lagrangians to likelihoods. Eur. Phys. J. C81(12), 1103 (2021) https://doi.org/10.1140/epjc/s10052-021-09828-9 arXiv:2107.00030 [hep-ph]

    Pith/arXiv arXiv 2021

  57. [57]

    JHEP06, 004 (2018) https://doi.org/10.1007/JHEP06(2018)004 arXiv:1801.04847 [hep-ph]

    Ilten, P., Soreq, Y., Williams, M., Xue, W.: Serendipity in dark pho- ton searches. JHEP06, 004 (2018) https://doi.org/10.1007/JHEP06(2018)004 arXiv:1801.04847 [hep-ph]

    Pith/arXiv arXiv 2018

  58. [58]

    JCAP07, 033 (2018) https://doi.org/10.1088/1475-7516/2018/07/033 arXiv:1802.03399 [hep- ph]

    Bringmann, T., Edsj¨ o, J., Gondolo, P., Ullio, P., Bergstr¨ om, L.: DarkSUSY 6 : An Advanced Tool to Compute Dark Matter Properties Numerically. JCAP07, 033 (2018) https://doi.org/10.1088/1475-7516/2018/07/033 arXiv:1802.03399 [hep- ph]

    Pith/arXiv arXiv 2018

  59. [59]

    Andreopoulos, C.,et al.: The GENIE Neutrino Monte Carlo Generator. Nucl. Instrum. Meth. A614, 87–104 (2010) https://doi.org/10.1016/j.nima.2009.12. 009 arXiv:0905.2517 [hep-ph]

    Pith/arXiv arXiv 2010

  60. [60]

    Hayato, Y., Pickering, L.: The NEUT neutrino interaction simulation program library. Eur. Phys. J. ST230(24), 4469–4481 (2021) https://doi.org/10.1140/ epjs/s11734-021-00287-7 arXiv:2106.15809 [hep-ph]

    Pith/arXiv arXiv 2021

  61. [61]

    Buss, O., Gaitanos, T., Gallmeister, K., Hees, H., Kaskulov, M., Lalakulich, O., Larionov, A.B., Leitner, T., Weil, J., Mosel, U.: Transport-theoretical Descrip- tion of Nuclear Reactions. Phys. Rept.512, 1–124 (2012) https://doi.org/10. 1016/j.physrep.2011.12.001 arXiv:1106.1344 [hep-ph]

    Pith/arXiv arXiv 2012

  62. [62]

    Golan, T., Sobczyk, J.T., Zmuda, J.: NuWro: the Wroclaw Monte Carlo Gen- erator of Neutrino Interactions. Nucl. Phys. B Proc. Suppl.229-232, 499–499 (2012) https://doi.org/10.1016/j.nuclphysbps.2012.09.136

    doi:10.1016/j.nuclphysbps.2012.09.136 2012

  63. [63]

    Autiero, D.: The OPERA event generator and the data tuning of nuclear re- interactions. Nucl. Phys. B Proc. Suppl.139, 253–259 (2005) https://doi.org/ 10.1016/j.nuclphysbps.2004.11.168

    work page doi:10.1016/j.nuclphysbps.2004.11.168 2005

  64. [64]

    Casper, D.: The Nuance neutrino physics simulation, and the future. Nucl. Phys. B Proc. Suppl.112, 161–170 (2002) https://doi.org/10.1016/S0920-5632(02) 01756-5 arXiv:hep-ph/0208030

    Pith/arXiv arXiv 2002

  65. [65]

    Lange, D.J.: The EvtGen particle decay simulation package. Nucl. Instrum. Meth. A462, 152–155 (2001) https://doi.org/10.1016/S0168-9002(01)00089-4

    doi:10.1016/s0168-9002(01)00089-4 2001

  66. [66]

    Agostinelli, S.,et al.: GEANT4 - A Simulation Toolkit. Nucl. Instrum. Meth. A 506, 250–303 (2003) https://doi.org/10.1016/S0168-9002(03)01368-8 35

    doi:10.1016/s0168-9002(03)01368-8 2003

  67. [67]

    EPJ Nuclear Sci

    Ballarini, F.,et al.: The FLUKA code: Overview and new developments. EPJ Nuclear Sci. Technol.10, 16 (2024) https://doi.org/10.1051/epjn/2024015

    arXiv 2024

  68. [68]

    JHEP02, 057 (2014) https://doi.org/10.1007/ JHEP02(2014)057 arXiv:1307.6346 [hep-ex]

    Favereau, J., Delaere, C., Demin, P., Giammanco, A., Lema ˆ ıtre, V., Mertens, A., Selvaggi, M.: DELPHES 3, A modular framework for fast simulation of a generic collider experiment. JHEP02, 057 (2014) https://doi.org/10.1007/ JHEP02(2014)057 arXiv:1307.6346 [hep-ex]

    Pith/arXiv arXiv 2014

  69. [69]

    Church, E.D.: LArSoft: A Software Package for Liquid Argon Time Projection Drift Chambers (2013) arXiv:1311.6774 [physics.ins-det]

    Pith/arXiv arXiv 2013

  70. [70]

    PoSLHCP2021, 334 (2021) https://doi.org/10.22323/1.397.0334

    Carrera Jarr ´ ın, E.F.: LHC experiments and their Open Data. PoSLHCP2021, 334 (2021) https://doi.org/10.22323/1.397.0334

    work page doi:10.22323/1.397.0334 2021

  71. [71]

    In: 14th International Conference on Computing in High-Energy and Nuclear Physics, pp

    Calafiura, P., Lavrijsen, W., Leggett, C., Marino, M., Quarrie, D.: The Athena control framework in production, new developments and lessons learned. In: 14th International Conference on Computing in High-Energy and Nuclear Physics, pp. 456–458 (2005)

    2005

  72. [72]

    Leggett, C.,et al.: AthenaMT: upgrading the ATLAS software framework for the many-core world with multi-threading. J. Phys. Conf. Ser.898(4), 042009 (2017) https://doi.org/10.1088/1742-6596/898/4/042009

    work page doi:10.1088/1742-6596/898/4/042009 2017

  73. [73]

    Jones, C.D., Contreras, L., Gartung, P., Hufnagel, D., Sexton-Kennedy, L.: Using the CMS Threaded Framework In A Production Environment. J. Phys. Conf. Ser.664(7), 072026 (2015) https://doi.org/10.1088/1742-6596/664/7/072026

    work page doi:10.1088/1742-6596/664/7/072026 2015

  74. [74]

    Brun, R., Buncic, P., Carminati, F., Morsch, A., Rademakers, F., Safarik, K.: Computing in ALICE. Nucl. Instrum. Meth. A502, 339–346 (2003) https:// doi.org/10.1016/S0168-9002(03)00440-6

    work page doi:10.1016/s0168-9002(03)00440-6 2003

  75. [75]

    Buncic, P., Krzewicki, M., Vande Vyvre, P.: Technical Design Report for the Upgrade of the Online-Offline Computing System (2015)

    2015

  76. [76]

    Barrand, G.,et al.: GAUDI - A software architecture and framework for building HEP data processing applications. Comput. Phys. Commun.140, 45–55 (2001) https://doi.org/10.1016/S0010-4655(01)00254-5

    doi:10.1016/s0010-4655(01)00254-5 2001

  77. [77]

    In: 9th International Conference on Computing in High-Energy and Nuclear Physics (1997)

    Itoh, R.: BASF - BELLE AnalysiS Framework. In: 9th International Conference on Computing in High-Energy and Nuclear Physics (1997)

    1997

  78. [78]

    Com- put

    Gelb, M.,et al.: B2BII: Data Conversion from Belle to Belle II. Com- put. Softw. Big Sci.2(1), 9 (2018) https://doi.org/10.1007/s41781-018-0016-x arXiv:1810.00019 [hep-ex]

    Pith/arXiv arXiv 2018

  79. [79]

    Pinkenburg, C.: Analyzing ever growing datasets in PHENIX. J. Phys. Conf. Ser.331, 072027 (2011) https://doi.org/10.1088/1742-6596/331/7/072027 36

    work page doi:10.1088/1742-6596/331/7/072027 2011

  80. [80]

    In: 14th International Conference on Computing in High-Energy and Nuclear Physics, pp

    Pruneau, C., Calderon, M., Hippolyte, B., Lauret, J., Rose, A.: A new STAR event reconstruction chain. In: 14th International Conference on Computing in High-Energy and Nuclear Physics, pp. 268–271 (2005)

    2005

Showing first 80 references.