Skip to content
Universidad del Mar SIBUMAR Descubridor Institucional UMAR
  • Inicio
  • Búsqueda avanzada
  • Explorar
  • Login
    • English
    • Deutsch
    • Español
    • Français
    • Italiano
Advanced
  • Renormalization of crossing probabilities in the dilute Potts model
Cover Image

Renormalization of crossing probabilities in the dilute Potts model

Fuente: arXiv
Saved in:
Bibliographic Details
Main Author: Rigas, Pete
Format: Preprint
Published: 2021
Subjects:
Probability
Mathematical Physics
60K35, 82B02
Online Access:
Acceder al recurso
Tags: Add Tag
No Tags, Be the first to tag this record!
  • Cite this
  • Text this
  • Email this
  • Print
  • Export Record
    • Export to RefWorks
    • Export to EndNoteWeb
    • Export to EndNote
  • Save to List
  • Permanent link
  • Holdings
  • Description
  • Comments
  • Similar Items
  • Staff View

Internet

https://arxiv.org/abs/2111.10979

Similar Items

  • From logarithmic delocalization of the six-vertex height function under sloped boundary conditions to weakened crossing probability estimates for the Ashkin-Teller, generalized random-cluster, and $(q_σ,q_τ)$-cubic models
    by: Rigas, Pete
    Published: (2022)
  • The phase transition for the Gaussian free field is sharp
    by: Rigas, Pete
    Published: (2023)
  • Quantum inverse scattering for the 20-vertex model up to Dynkin automorphism: 3D Poisson structure, triangular height functions, weak integrability
    by: Rigas, Pete
    Published: (2024)
  • Poisson structure of the 4-vertex model, and the higher-spin XXX chain, and Yang-Baxter algebras
    by: Rigas, Pete
    Published: (2024)
  • Poisson structure and Integrability of a Hamiltonian flow for the inhomogeneous six-vertex model
    by: Rigas, Pete
    Published: (2023)
Universidad del Mar
Universidad del MarSistema Bibliotecario de la Universidad del MarDescubridor Institucional UMARImplementación y desarrollo: Mtro. Carlos Alonso Albores Pérez
InicioBúsqueda avanzadaExplorar
Visitas al Descubridor: 33,245© 2026 Universidad del Mar