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        Renormalized Perturbation Theory And Its Optimization By The Principle Of Minimal Sensitivity

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        Author(s)
        Stevenson, P.M.
        Language
        English
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        Abstract
        The results of renormalized perturbation theory, in QCD and other quantum field theories, are ambiguous at any finite order, due to renormalization-scheme dependence. The perturbative results depend upon extraneous scheme variables, including the renormalization scale, that the exact result cannot depend on. Such 'non-invariant approximations' occur in many other areas of physics, too. The sensible strategy is to find where the approximant is stationary under small variations of the extraneous variables. This general principle is explained and illustrated with various examples. Also dimensional transmutation, RG equations, the essence of renormalization and the origin of its ambiguities are explained in simple terms, assuming little or no background in quantum field theory. The minimal-sensitivity approach leads to 'optimized perturbation theory,' which is developed in detail. Applications to Re⁺e⁻, the infrared limit, and to the optimization of factorized quantities, are also discussed thoroughly.
        URI
        https://library.oapen.org/handle/20.500.12657/60889
        Keywords
        Physics;Particle Physics / High Energy Physics / Quantum Fields
        DOI
        10.1142/12817
        ISBN
        9789811255694, 9789811255687, 9789811255700
        Publisher
        World Scientific Publishing Company
        Publisher website
        https://www.worldscientific.com/
        Publication date and place
        Singapore, 2022
        Imprint
        World Scientific
        Classification
        Cosmology and the universe
        Pages
        296
        Rights
        https://creativecommons.org/licenses/by-nc/4.0/
        • Imported or submitted locally

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        • If not noted otherwise all contents are available under Attribution 4.0 International (CC BY 4.0)

        Credits

        • logo EU
        • This project received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 683680, 810640, 871069 and 964352.

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