Constructing tree amplitudes of scalar EFT from double soft theorem

A bstract The well known Adler zero can fully determine tree amplitudes of non-linear sigma model (NLSM), but fails to fix tree pion amplitudes with higher-derivative interactions. In this paper we propose a novel method based on exploiting the double soft theorem for scalars, which can be applied to a wider range. To test the applicability, we use this method to construct tree NLSM amplitudes and tree amplitudes those pions in NLSM couple to bi-adjoint scalars. We also construct the simplest pion amplitudes which receive leading higher-derivative correction, with arbitrary number of external legs. All resulted amplitudes are formulated as universal expansions to appropriate basis.

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Publication Details

Journal
Journal of High Energy Physics
Published
2024-12-10
DOI
https://doi.org/10.1007/jhep12(2024)079
Citations
7
Primary Topic
Distributed and Parallel Computing Systems
Type
article
Field-Weighted Citation Impact
2.44

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article

Constructing tree amplitudes of scalar EFT from double soft theorem

Kang Zhou
7 citations
Journal of High Energy Physics
Distributed and Parallel Computing Systems
2.44
article

Constructing tree amplitudes of scalar EFT from double soft theorem

Kang Zhou
article en
7 citations

Abstract

A bstract The well known Adler zero can fully determine tree amplitudes of non-linear sigma model (NLSM), but fails to fix tree pion amplitudes with higher-derivative interactions. In this paper we propose a novel method based on exploiting the double soft theorem for scalars, which can be applied to a wider range. To test the applicability, we use this method to construct tree NLSM amplitudes and tree amplitudes those pions in NLSM couple to bi-adjoint scalars. We also construct the simplest pion amplitudes which receive leading higher-derivative correction, with arbitrary number of external legs. All resulted amplitudes are formulated as universal expansions to appropriate basis.

Journal of High Energy PhysicsVol. 2024(12)
Yangzhou University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 10%
Distributed and Parallel Computing Systems
2.44
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