Implementation of Tensor Network Simulation TN-Sim under NWQ-Sim
Aaron C. Hoyt, Jonathan S. Bersson, Sean Garner, Chenxu Liu, Ang Li

TL;DR
This paper presents TN-Sim, a scalable tensor network simulation tool integrated into NWQ-Sim, leveraging high-performance computing to enable efficient quantum circuit simulations for classical quantum computing research.
Contribution
The paper introduces TN-Sim within NWQ-Sim, combining TAMM and ITensor frameworks for scalable tensor network simulations on HPC systems, including task-based parallelization for wide quantum circuits.
Findings
Successfully demonstrated on Perlmutter supercomputer
Supports both local and distributed HPC simulations
Potential for portability to other HPC clusters
Abstract
Large-scale tensor network simulations are crucial for developing robust complexity-theoretic bounds on classical quantum simulation, enabling circuit cutting approaches, and optimizing circuit compilation, all of which aid efficient quantum computation on limited quantum resources. Modern exascale high-performance computing platforms offer significant potential for advancing tensor network quantum circuit simulation capabilities. We implement TN-Sim, a tensor network simulator backend within the NWQ-Sim software package that utilizes the Tensor Algebra for Many-body Methods (TAMM) framework to support both distributed HPC-scale computations and local simulations with ITensor. To optimize the scale up in computation across multiple nodes we implement a task based parallelization scheme to demonstrate parallelized gate contraction for wide quantum circuits with many gates per layer.…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsQuantum many-body systems · Quantum Computing Algorithms and Architecture · Tensor decomposition and applications
