4 papers
Extracting conformal data from finite-size tensor-network flow in critical two-dimensional classical models
Sing-Hong Chan, Pochung Chen
We present a general framework for extracting conformal data from critical two-dimensional classical lattice models using finite-size tensor-network flow. The central idea is to id…
Learning phases with Quantum Monte Carlo simulation cell
Amrita Ghosh, Mugdha Sarkar, Ying-Jer Kao +1
We propose the use of the ``spin-opstring", derived from Stochastic Series Expansion Quantum Monte Carlo (QMC) simulations as machine learning (ML) input data. It offers a compact,…
Tensor Network Finite-Size Scaling for Two-Dimensional 3-state Clock Model
Debasmita Maiti, Sing-Hong Chan, Pochung Chen
We benchmark recently proposed tensor network based finite-size scaling analysis in Phys. Rev. B {\bf 107}, 205123 (2023) against two-dimensional classical 3-state clock model. Due…
The Cytnx Library for Tensor Networks
Kai-Hsin Wu, Chang-Teng Lin, Ke Hsu +5
We introduce a tensor network library designed for classical and quantum physics simulations called Cytnx (pronounced as sci-tens). This library provides almost an identical interf…