2020/07/31 by Andrea Amoretti, Gianluca Costagliola, Nicodemo Magnoli +1 · 1 citation
Mathematics · Physics and Astronomy · #Artificial intelligence #Class (philosophy) #Combinatorics #Computer science #Conformal map #Energy (signal processing) #Imaging phantom #Ising model #Markov Chains and Monte Carlo Methods #Mathematical analysis #Mathematics #Optics #Physics #Quantum many-body systems #Quantum mechanics #Statistical physics #Theoretical and Computational Physics #cond-mat.stat-mech #hep-th
paper · pdf · doi:10.1103/physrevd.102.036018
published in Physical review. D/Physical review. D. 102(3) (American Physical Society) · 17 pages, 5 figures; minor changes, version to appear on PRD
arxiv created 2020/08/08 · openalex publication_date 2020/08/21 · arxiv updated 2020/08/26 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
The authors explore a method for computing correlation functions that is complementary to the well-known bootstrap program and particularly well suited for determining the behavior of off-critical systems, i.e. systems perturbed around their conformal point. They do so for a class of perturbations of the 3D Ising model which are relevant for real experiments on systems in a so-called t\phantom\rule00exh\phantom\rule00exe\phantom\rule00exr\phantom\rule00exm\phantom\rule00exa\phantom\rule00exl t\phantom\rule00exr\phantom\rule00exa\phantom\rule00exp.