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

2026/06/29 by Paolo D'Alberto · 1 voice · 1 citation
Computer Science · #cs.MS

paper · pdf

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.

Citations

• Simulating and Sampling from Quantum Circuits with 2D Tensor Networks
• A Practical Introduction to Tensor Networks: Matrix Product States and Projected Entangled Pair States
• Efficient Simulation of One-Dimensional Quantum Many-Body Systems
• Efficient classical simulation of slightly entangled quantum computations
• Quantum phase transitions
• Quantum phase transitions

Discussions

• Paolo D'Alberto: GPU-First Heisenberg-Picture Tensor Network Dynamics for the 2D Transverse-Field Ising Model https://arxiv.org/abs/2606.30985 https://arxiv.org/pdf/2606.30985 https://arxiv.org/html/2 [bsky, 0 points, 0 comments]

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