Uncovering Hidden Patterns: Approximate Resurgent Resummation from Truncated Series

We analyze truncated series generated as divergent formal solutions of non-linear ordinary differential equations. Motivating the study is a specific non-linear, first-order differential equation, which is the basis of the resurgent formulation of renormalized perturbation theory in quantum field theory. We use the Borel–Padé approximant and classical analysis to determine the analytic structure of the solution using the first few terms of its asymptotic series. Afterward, we build an approximant, consistent with the resurgent properties of the equation. The procedure gives an approximate expression for the Borel–Ecalle resummation of the solution useful for practical applications. Connections with other physical applications are also discussed.

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Publication Details

Journal
Mathematics
Published
2024-10-02
DOI
https://doi.org/10.3390/math12193087
Primary Topic
Algorithms and Data Compression
Type
article
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article

Uncovering Hidden Patterns: Approximate Resurgent Resummation from Truncated Series

Alessio Maiezza, Juan Carlos Vásquez
Mathematics
Algorithms and Data Compression
article

Uncovering Hidden Patterns: Approximate Resurgent Resummation from Truncated Series

Alessio Maiezza, Juan Carlos Vásquez
article en

Abstract

We analyze truncated series generated as divergent formal solutions of non-linear ordinary differential equations. Motivating the study is a specific non-linear, first-order differential equation, which is the basis of the resurgent formulation of renormalized perturbation theory in quantum field theory. We use the Borel–Padé approximant and classical analysis to determine the analytic structure of the solution using the first few terms of its asymptotic series. Afterward, we build an approximant, consistent with the resurgent properties of the equation. The procedure gives an approximate expression for the Borel–Ecalle resummation of the solution useful for practical applications. Connections with other physical applications are also discussed.

MathematicsVol. 12(19)
Istituto Nazionale di Fisica Nucleare (IT), Amherst College (US), University of L'Aquila (IT), Istituto Nazionale di Fisica Nucleare, Laboratori Nazionali del Gran Sasso (IT)
Openalex Percentile: Top 85%
Algorithms and Data Compression
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Uncovering Hidden Patterns: Approximate Resurgent Resummation from Truncated Series — Alessio Maiezza, Juan Carlos Vásquez · Mathematics (2024) | TGRS Research Map | TGRS