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PHEGAS: a phase-space generator for automatic cross-section computation

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Costas G. Papadopoulos

High Energy Physics - Phenomenology · Submitted 28 Jul 2000

abstract compiled · 2026-09-23 · no language-model review

The authors' main claim A phase-space generation algorithm, capable to efficiently integrate the squared amplitude of any scattering process, is presented.

how it is stated · asserted 1.00 read the record →

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arXiv IDhep-ph/0007335 (version 1)
Pith IDH4NMPUTV, Pith's permanent record of this paper and its review
CitationCostas G. Papadopoulos. "PHEGAS: a phase-space generator for automatic cross-section computation." arXiv:hep-ph/0007335 (2000). https://pith.science/paper/H4NMPUTV
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The compiled record

The paper's own sentences, arranged. Each label is drawn from a closed vocabulary; the number beside it is the probability the classifier gave that label. Numbers in the tables are the authors', checked by code. No sentence in this record was written by a model.

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Compiled by classifier-1.13-20260917 via OpenRouter, question bank abstract-p1-20260923, 2026-09-23: 1 request, 2,903 input tokens, $0.0001 reported.

What the abstract itself states, as probabilities: claims first 0.04 · states limitation 0.11 · human participants 0.02 · controlled comparison 0.01 · randomized assignment 0.01 · states quantitative result 0.10 · compares with prior results 0.07 · mentions code or data availability 0.15.

The abstract, sentence by sentence

arXiv listing abstract v1. Results and the main claim are underlined; .

A phase-space generation algorithm, capable to efficiently integrate the squared amplitude of any scattering process, is presented. The algorithm has been implemented in a Monte Carlo program, PHEGAS, which, using HELAC, a helicity amplitude computational package,can be used for automatic cross-section computation and event generation. Results for several scattering processes with four, five and six particles in the final state are briefly presented.

background contribution method result interpretation main claim

What the classifier reports for each sentence. The number is the probability it gave the label.
#sentencerolethe authors' own workstates the main conclusionstrength
s0 A phase-space generation algorithm, capable to efficiently integrate the squared amplitude of any scattering process, is presented. contribution 0.96 0.88 0.52 asserted 1.00
s1 The algorithm has been implemented in a Monte Carlo program, PHEGAS, which, using HELAC, a helicity amplitude computational package,can be used for automatic cross-section computation and event generation. method 0.63 0.87 0.20 asserted 0.94
s2 Results for several scattering processes with four, five and six particles in the final state are briefly presented. result 0.99 0.90 0.13 asserted 0.99

What kind of paper the classifier reports this is: method or tool 1.00 · evidence from simulation or computation 1.00.

What was examined, and what was not

sources read
  • arXiv listing abstract v1
not examined
  • full text
  • figures and tables
  • references and citing sentences
  • relations to other papers
levels run
  • P abstract
not run
  • S sections
  • T body sentences
  • C citations
  • R cross-paper relations

Every quoted sentence on this record is the authors'. Every label is from Pith's closed vocabulary, with the probability shown beside it. Every number in the measurements table is the authors', checked by code. Record as JSON

The paper
Original abstract

A phase-space generation algorithm, capable to efficiently integrate the squared amplitude of any scattering process, is presented. The algorithm has been implemented in a Monte Carlo program, PHEGAS, which, using HELAC, a helicity amplitude computational package,can be used for automatic cross-section computation and event generation. Results for several scattering processes with four, five and six particles in the final state are briefly presented.

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References
How the literature uses it

26 arXiv papers cite this in 33 sentences

Each citing sentence is taken from the citing paper's LaTeX source and typed by Pith's classifier. A label appears at probability 0.8 or more (0.95 for support), a contest at 0.7 or more; the quoted words are the citing authors'. How each label was checked · JSON

Papers citing it · 11 sentences without a confident label

Uses its method or tool 12 papers
Compares with it 1 paper
Cites it as background 5 papers

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