English

GPU-First Heisenberg-Picture Tensor Network Dynamics for the 2D Transverse-Field Ising Model

Mathematical Software 2026-06-29 v1

Abstract

We present CppSim, a C++/GPU 2D Ising simulator for Heisenberg-picture tensor network time evolution on GPUs. The key computational contributions are: first, a zero-malloc GPU workspace that pre-allocates all buffers at startup; second, a custom GPU tensor permutation kernel replacing host-side index shuffling with a pure device-to-device operation, yielding a 7.6x trotter speedup; third, a hybrid QR strategy selecting Cholesky-QR for tall-skinny matrices and Householder-QR otherwise; fourth, adaptive Belief Propagation with log-space Bethe partition function evaluation and explicit sign tracking.

Cite

@article{arxiv.2606.30985,
  title  = {GPU-First Heisenberg-Picture Tensor Network Dynamics for the 2D Transverse-Field Ising Model},
  author = {Paolo D'Alberto},
  journal= {arXiv preprint arXiv:2606.30985},
  year   = {2026}
}

Comments

36 pages, 13 figures, 12 tables

R2 v1 2026-07-22T20:16:15.047Z