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Large momentum expansion of two-loop self-energy diagrams with arbitrary masses

High Energy Physics - Phenomenology · Submitted 30 Jul 1993

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

The authors' main claim For some two-loop diagrams occurring in the Standard Model, comparison with results of numerical integration shows that our expansion works well in the region above the highest physical threshold.

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arXiv IDhep-ph/9307371 (version 1)
Pith IDLXB5GOEQ, Pith's permanent record of this paper and its review
CitationA.I. Davydychev, J.B. Tausk, V.A. Smirnov. "Large momentum expansion of two-loop self-energy diagrams with arbitrary masses." arXiv:hep-ph/9307371 (1993). https://pith.science/paper/LXB5GOEQ
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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, 2,922 input tokens, $0.0001 reported.

What the abstract itself states, as probabilities: claims first 0.04 · states limitation 0.73 · human participants 0.01 · controlled comparison 0.10 · randomized assignment 0.01 · states quantitative result 0.08 · compares with prior results 0.91 · mentions code or data availability 0.02.

The abstract, sentence by sentence

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

For two-loop two-point diagrams with arbitrary masses, an algorithm to derive the asymptotic expansion at large external momentum squared is constructed. By using a general theorem on asymptotic expansions of Feynman diagrams, the coefficients of the expansion are calculated analytically. For some two-loop diagrams occurring in the Standard Model, comparison with results of numerical integration shows that our expansion works well in the region above the highest physical 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 For two-loop two-point diagrams with arbitrary masses, an algorithm to derive the asymptotic expansion at large external momentum squared is constructed. contribution 0.92 0.94 0.47 asserted 1.00
s1 By using a general theorem on asymptotic expansions of Feynman diagrams, the coefficients of the expansion are calculated analytically. method 0.96 0.89 0.17 asserted 1.00
s2 For some two-loop diagrams occurring in the Standard Model, comparison with results of numerical integration shows that our expansion works well in the region above the highest physical threshold. result 0.94 0.93 0.38 asserted 0.96

What kind of paper the classifier reports this is: method or tool 0.96 · evidence from proof or derivation 0.99.

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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

For two-loop two-point diagrams with arbitrary masses, an algorithm to derive the asymptotic expansion at large external momentum squared is constructed. By using a general theorem on asymptotic expansions of Feynman diagrams, the coefficients of the expansion are calculated analytically. For some two-loop diagrams occurring in the Standard Model, comparison with results of numerical integration shows that our expansion works well in the region above the highest physical 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

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Cites it as background 1 paper

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