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Zero-threshold expansion of two-loop self-energy diagrams

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F.A. Berends, A.I. Davydychev, V.A. Smirnov, J.B. Tausk

High Energy Physics - Phenomenology · Submitted 6 Oct 1994

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

The authors' main claim An algorithm is constructed to derive a small momentum expansion for two-loop two-point diagrams in all cases where, due to the presence of physical thresholds, there are singularities at zero external momentum.

how it is stated · asserted 1.00 read the record →

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arXiv IDhep-ph/9410232 (version 1)
Pith ID2I24WKTW, Pith's permanent record of this paper and its review
CitationA.I. Davydychev, F.A. Berends, J.B. Tausk, V.A. Smirnov. "Zero-threshold expansion of two-loop self-energy diagrams." arXiv:hep-ph/9410232 (1994). https://pith.science/paper/2I24WKTW
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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, 2,912 input tokens, $0.0001 reported.

What the abstract itself states, as probabilities: claims first 0.04 · states limitation 0.44 · human participants 0.01 · controlled comparison 0.02 · randomized assignment 0.01 · states quantitative result 0.12 · compares with prior results 0.07 · mentions code or data availability 0.02.

The abstract, sentence by sentence

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

An algorithm is constructed to derive a small momentum expansion for two-loop two-point diagrams in all cases where, due to the presence of physical thresholds, there are singularities at zero external momentum. The coefficients of this ``zero-threshold'' expansion are calculated analytically for arbitrary masses. Numerical examples, using diagrams occurring in the Standard Model, illustrate the convergence of the expansion below the first non-zero threshold.

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 An algorithm is constructed to derive a small momentum expansion for two-loop two-point diagrams in all cases where, due to the presence of physical thresholds, there are singularities at zero external momentum. contribution 0.75 0.94 0.36 asserted 1.00
s1 The coefficients of this ``zero-threshold'' expansion are calculated analytically for arbitrary masses. result 0.73 0.94 0.33 asserted 1.00
s2 Numerical examples, using diagrams occurring in the Standard Model, illustrate the convergence of the expansion below the first non-zero threshold. result 0.78 0.92 0.19 asserted 1.00

What kind of paper the classifier reports this is: method or tool 0.93 · evidence from proof or derivation 1.00.

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  • references and citing sentences
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  • T body sentences
  • C citations
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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

An algorithm is constructed to derive a small momentum expansion for two-loop two-point diagrams in all cases where, due to the presence of physical thresholds, there are singularities at zero external momentum. The coefficients of this ``zero-threshold'' expansion are calculated analytically for arbitrary masses. Numerical examples, using diagrams occurring in the Standard Model, illustrate the convergence of the expansion below the first non-zero threshold.

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References
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3 arXiv papers cite this in 3 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 · 1 sentence without a confident label

Uses its method or tool 2 papers

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