The Augmented Tree Tensor Network Cookbook

Fuente: arXiv
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Auteurs principaux: Reinić, Nora, Pavešić, Luka, Jaschke, Daniel, Montangero, Simone
Format: Preprint
Publié: 2025
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author Reinić, Nora
Pavešić, Luka
Jaschke, Daniel
Montangero, Simone
author_facet Reinić, Nora
Pavešić, Luka
Jaschke, Daniel
Montangero, Simone
contents An augmented tree tensor network (aTTN) is a tensor network ansatz constructed by applying a layer of unitary disentanglers to a tree tensor network. The disentanglers absorb a part of the system's entanglement. This makes aTTNs suitable for simulating higher-dimensional lattices, where the entanglement increases with the lattice size even for states that obey the area law. These lecture notes serve as a detailed guide for implementing the aTTN algorithms. We present a variational algorithm for ground state search and discuss the measurement of observables, and offer an open-source implementation within the Quantum TEA library. We benchmark the performance of the ground state search for different parameters and hyperparameters in the square lattice quantum Ising model and the triangular lattice Heisenberg model for up to $32 \times 32$ spins. The benchmarks identify the regimes where the aTTNs offer advantages in accuracy relative to computational cost compared to matrix product states and tree tensor networks.
format Preprint
id arxiv_https___arxiv_org_abs_2507_21236
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle The Augmented Tree Tensor Network Cookbook
Reinić, Nora
Pavešić, Luka
Jaschke, Daniel
Montangero, Simone
Quantum Physics
An augmented tree tensor network (aTTN) is a tensor network ansatz constructed by applying a layer of unitary disentanglers to a tree tensor network. The disentanglers absorb a part of the system's entanglement. This makes aTTNs suitable for simulating higher-dimensional lattices, where the entanglement increases with the lattice size even for states that obey the area law. These lecture notes serve as a detailed guide for implementing the aTTN algorithms. We present a variational algorithm for ground state search and discuss the measurement of observables, and offer an open-source implementation within the Quantum TEA library. We benchmark the performance of the ground state search for different parameters and hyperparameters in the square lattice quantum Ising model and the triangular lattice Heisenberg model for up to $32 \times 32$ spins. The benchmarks identify the regimes where the aTTNs offer advantages in accuracy relative to computational cost compared to matrix product states and tree tensor networks.
title The Augmented Tree Tensor Network Cookbook
topic Quantum Physics
url https://arxiv.org/abs/2507.21236