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High Energy Physics - Phenomenology · arXiv:hep-ph/0405174 v1 · submitted 18 May 2004

Evidence for the saturation of the Froissart bound

M. M. Block, F. Halzen

The paper says

“The results strongly favor the high energy ln^2(s) fit of the form sigma_gamma p = c_0 + c_1 ln(nu/m) + c_2 ln^2(nu/m) + beta_P'/sqrt(nu/m), basically excluding a ln(s) fit of the form sigma_{\gamma p} = c_0 + c_1 ln(nu/m) + beta_P'/sqrt(\nu/m), where nu is the laboratory photon energy.”

from the abstract · picked out as the main claim by a classifier

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The paper

Abstract

It is well known that fits to high energy data cannot discriminate between asymptotic ln(s) and ln^2(s) behavior of total cross section. We show that this is no longer the case when we impose the condition that the amplitudes also describe, on average, low energy data dominated by resonances. We demonstrate this by fitting real analytic amplitudes to high energy measurements of the gamma p total cross section, for sqrt(s) > 4 GeV. We subsequently require that the asymptotic fit smoothly join the sqrt(s) = 2.01 GeV cross section described by Dameshek and Gilman as a sum of Breit-Wigner resonances. The results strongly favor the high energy ln^2(s) fit of the form sigma_gamma p = c_0 + c_1 ln(nu/m) + c_2 ln^2(nu/m) + beta_P'/sqrt(nu/m), basically excluding a ln(s) fit of the form sigma_{\gamma p} = c_0 + c_1 ln(nu/m) + beta_P'/sqrt(\nu/m), where nu is the laboratory photon energy. This evidence for saturation of the Froissart bound for gamma p interactions is confirmed by applying the same analysis to pi p data using vector meson dominance.

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

How the main claim is stated: asserted 0.95

What the abstract itself states, as probabilities: claims first 0.06 · states limitation 0.19 · human participants 0.01 · controlled comparison 0.13 · randomized assignment 0.01 · states quantitative result 0.26 · compares with prior results 0.85 · mentions code or data availability 0.02

The abstract, sentence by sentence

This table labels the abstract only (arXiv listing abstract v1). The number is the probability the classifier gave the label.

SentenceRoleThe authors' own workStates the main conclusionStrength
It is well known that fits to high energy data cannot discriminate between asymptotic ln(s) and ln^2(s) behavior of total cross section. background 0.92 0.04 0.02 asserted 1.00
We show that this is no longer the case when we impose the condition that the amplitudes also describe, on average, low energy data dominated by resonances. contribution 0.83 0.63 0.24 asserted 1.00
We demonstrate this by fitting real analytic amplitudes to high energy measurements of the gamma p total cross section, for sqrt(s) > 4 GeV. method 0.86 0.94 0.03 asserted 1.00
We subsequently require that the asymptotic fit smoothly join the sqrt(s) = 2.01 GeV cross section described by Dameshek and Gilman as a sum of Breit-Wigner resonances. method 0.98 0.80 0.04 asserted 0.91
The results strongly favor the high energy ln^2(s) fit of the form sigma_{gamma p} = c_0 + c_1 ln(nu/m) + c_2 ln^2(nu/m) + beta_{P'}/sqrt(nu/m), basically excluding a ln(s) fit of the form sigma_{\gamma p} = c_0 + c_1 ln(nu/m) + beta_P'/sqrt(\nu/m), where nu is the laboratory photon energy. result 1.00 0.94 0.86 asserted 0.95
This evidence for saturation of the Froissart bound for gamma p interactions is confirmed by applying the same analysis to pi p data using vector meson dominance. result 0.87 0.91 0.34 asserted 1.00

What kind of paper the classifier reports this is: theoretical result 0.72 · evidence from analysis of existing data 1.00

What was examined, and what was not

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  • arXiv listing abstract v1

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  • references and citing sentences
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  • P abstract

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  • S sections
  • T body sentences
  • C citations
  • R cross-paper relations

How the labels were made

Compiled by classifier-1.13-20260917 via OpenRouter, question bank abstract-p1-20260923, 2026-09-23: 1 request, 5,191 input tokens, $0.0002 reported.

Every quoted sentence on this record is the authors'. Every label is from Pith's closed vocabulary, with the probability shown beside it. This record as JSON

Cited by 4 Pith papers
How the literature uses it

4 arXiv papers cite this in 6 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 · 4 sentences without a confident label

Uses its data or values 1 paper
Cites it as support 1 paper

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