Leading order CFT analysis of multi-scalar theories in $$d>2$$ d > 2 View Full Text


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Article Info

DATE

2019-04

AUTHORS

A. Codello, M. Safari, G. P. Vacca, O. Zanusso

ABSTRACT

N/A

References to SciGraph publications

  • 2013-01. The a-theorem and the asymptotics of 4D quantum field theory in JOURNAL OF HIGH ENERGY PHYSICS
  • 2015-11. ϵ-expansions near three dimensions from conformal field theory in JOURNAL OF HIGH ENERGY PHYSICS
  • 2015-06. A semidefinite program solver for the conformal bootstrap in JOURNAL OF HIGH ENERGY PHYSICS
  • 2017-04. The analytic structure of conformal blocks and the generalized Wilson-Fisher fixed points in JOURNAL OF HIGH ENERGY PHYSICS
  • 2018-05. Bootstrapping hypercubic and hypertetrahedral theories in three dimensions in JOURNAL OF HIGH ENERGY PHYSICS
  • 2018-05. Seeking fixed points in multiple coupling scalar theories in the ε expansion in JOURNAL OF HIGH ENERGY PHYSICS
  • 2018-07. Taming the ϵ-expansion with large spin perturbation theory in JOURNAL OF HIGH ENERGY PHYSICS
  • 2008-12-09. Bounding scalar operator dimensions in 4D CFT in JOURNAL OF HIGH ENERGY PHYSICS
  • 2017-04. Leading CFT constraints on multi-critical models in d > 2 in JOURNAL OF HIGH ENERGY PHYSICS
  • 2016-07. Classical equation of motion and anomalous dimensions at leading order in JOURNAL OF HIGH ENERGY PHYSICS
  • 2014-12. Solving the 3d Ising Model with the Conformal Bootstrap II. c-Minimization and Precise Critical Exponents in JOURNAL OF STATISTICAL PHYSICS
  • 2017-10. Solving CFTs with weakly broken higher spin symmetry in JOURNAL OF HIGH ENERGY PHYSICS
  • 2017-05. A Mellin space approach to the conformal bootstrap in JOURNAL OF HIGH ENERGY PHYSICS
  • 2017-12. A functional perspective on emergent supersymmetry in JOURNAL OF HIGH ENERGY PHYSICS
  • Journal

    TITLE

    The European Physical Journal C

    ISSUE

    4

    VOLUME

    79

    Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1140/epjc/s10052-019-6817-1

    DOI

    http://dx.doi.org/10.1140/epjc/s10052-019-6817-1

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1113410395


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    Turtle is a human-readable linked data format.

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