24–28 Aug 2026
Hiyoshi Campus, Keio University, Yokohama, Japan
Asia/Tokyo timezone

Extracting Conformal Data from Critical 2D Classical Models using Tensor-Network-Based Finite-size Scaling

26 Aug 2026, 12:20
1h 40m
Multipurpose Room 3, Kyoseikan (Hiyoshi Campus, Keio University, Yokohama, Japan)

Multipurpose Room 3, Kyoseikan

Hiyoshi Campus, Keio University, Yokohama, Japan

4-1-1 Hiyoshi, Kohoku-Ku,Yokohama, Kanagawa 223-8526, JAPAN
Board: 1
Poster Presentation Poster

Speaker

Sing Hong Chan (National Tsing Hua University)

Description

Critical 2D classical lattice models are analyzed through a method-agnostic finite-size-scaling framework built on tensor-network transfer matrices. The key idea is an explicit crossover length scale that separates the finite-size-scaling regime from the finite-entanglement-scaling regime induced by bond-dimension truncation. Working within this self-consistent finite-size window, the central charge, scaling dimensions, and conformal spins can be estimated and cross-validated across three independent tensor renormalization schemes — HOTRG, PTMRG, and CTRG — on the critical Ising and three-state clock models. Universal behavior emerges robustly below the crossover scale, with accurate conformal data extracted up to relatively high conformal levels. Moreover, a natural operational definition of entanglement scaling is provided by our analysis.

Authors

Prof. Pochung Chen (NTHU) Sing Hong Chan (National Tsing Hua University)

Presentation materials

There are no materials yet.