Integrating Julia-ITensors into the Tensor Network Quantum Virtual Machine (TNQVM)

Fuente: arXiv
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Main Authors: Windom, Zachary W., Claudino, Daniel, Leyton-Ortega, Vicente
Format: Preprint
Published: 2026
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author Windom, Zachary W.
Claudino, Daniel
Leyton-Ortega, Vicente
author_facet Windom, Zachary W.
Claudino, Daniel
Leyton-Ortega, Vicente
contents The Tensor Network Quantum Virtual Machine (TNQVM) is a high-performance classical circuit simulation backend for the eXtreme-scale ACCelerator (XACC) framework that leverages the Intelligent Tensor (ITensor) library for tensor network--based quantum circuit simulation. However, TNQVM's original C++ ITensor backend is tied to an older integrated release, limiting access to newer tensor network algorithms, diagnostics, and performance improvements available in the actively developed Julia-based ITensors ecosystem. We introduce JuliaITensorTNQVM, an interoperability layer that bridges TNQVM's C++ visitor infrastructure and the Julia-ITensors runtime through a C-compatible application binary interface. This design preserves the existing XACC/TNQVM programming model while enabling access to modern tensor network capabilities, including entanglement entropy diagnostics exposed directly to XACC. We evaluate the implementation through two studies: a Page-curve verification protocol using Haar-random states, and QAOA MaxCut simulations on 3-regular graphs. Within these tested regimes, results are consistent with expected entanglement behavior and established scaling trends, supporting JuliaITensorTNQVM as a practical modernization path for tensor network simulation in TNQVM.
format Preprint
id arxiv_https___arxiv_org_abs_2603_27037
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Integrating Julia-ITensors into the Tensor Network Quantum Virtual Machine (TNQVM)
Windom, Zachary W.
Claudino, Daniel
Leyton-Ortega, Vicente
Quantum Physics
The Tensor Network Quantum Virtual Machine (TNQVM) is a high-performance classical circuit simulation backend for the eXtreme-scale ACCelerator (XACC) framework that leverages the Intelligent Tensor (ITensor) library for tensor network--based quantum circuit simulation. However, TNQVM's original C++ ITensor backend is tied to an older integrated release, limiting access to newer tensor network algorithms, diagnostics, and performance improvements available in the actively developed Julia-based ITensors ecosystem. We introduce JuliaITensorTNQVM, an interoperability layer that bridges TNQVM's C++ visitor infrastructure and the Julia-ITensors runtime through a C-compatible application binary interface. This design preserves the existing XACC/TNQVM programming model while enabling access to modern tensor network capabilities, including entanglement entropy diagnostics exposed directly to XACC. We evaluate the implementation through two studies: a Page-curve verification protocol using Haar-random states, and QAOA MaxCut simulations on 3-regular graphs. Within these tested regimes, results are consistent with expected entanglement behavior and established scaling trends, supporting JuliaITensorTNQVM as a practical modernization path for tensor network simulation in TNQVM.
title Integrating Julia-ITensors into the Tensor Network Quantum Virtual Machine (TNQVM)
topic Quantum Physics
url https://arxiv.org/abs/2603.27037