Gauging tensor networks with belief propagation

J Tindall, M Fishman - SciPost Physics, 2023 - scipost.org
Effectively compressing and optimizing tensor networks requires reliable methods for fixing
the latent degrees of freedom of the tensors, known as the gauge. Here we introduce a new …

Optimizing tensor network contraction using reinforcement learning

E Meirom, H Maron, S Mannor… - … on Machine Learning, 2022 - proceedings.mlr.press
Quantum Computing (QC) stands to revolutionize computing, but is currently still limited. To
develop and test quantum algorithms today, quantum circuits are often simulated on …

The first-kind flexible tensor SVD: innovations in multi-sensor data fusion processing

J Huang, F Zhang, T Coombs, F Chu - Nonlinear Dynamics, 2024 - Springer
High-order tensors, as a powerful tool for representation of higher-order data, have garnered
much attention across various applications including image data, data mining, and big data …

Algorithms for tensor network contraction ordering

F Schindler, AS Jermyn - Machine Learning: Science and …, 2020 - iopscience.iop.org
Contracting tensor networks is often computationally demanding. Well-designed contraction
sequences can dramatically reduce the contraction cost. We explore the performance of …

Fast search of the optimal contraction sequence in tensor networks

L Liang, J Xu, L Deng, M Yan, X Hu… - IEEE Journal of …, 2021 - ieeexplore.ieee.org
Tensor network and tensor computation are widely applied in scientific and engineering
domains like quantum physics, electronic design automation, and machine learning. As one …

On the optimal linear contraction order of tree tensor networks, and beyond

M Stoian, RM Milbradt, CB Mendl - SIAM Journal on Scientific Computing, 2024 - SIAM
The contraction cost of a tensor network depends on the contraction order. However, the
optimal contraction ordering problem is known to be NP-hard. We show that the linear …

NP-Hardness of Tensor Network Contraction Ordering

J Xu, H Zhang, L Liang, L Deng, Y Xie, G Li - arXiv preprint arXiv …, 2023 - arxiv.org
We study the optimal order (or sequence) of contracting a tensor network with a minimal
computational cost. We conclude 2 different versions of this optimal sequence: that minimize …

On the Optimal Linear Contraction Order for Tree Tensor Networks

M Stoian - arXiv preprint arXiv:2209.12332, 2022 - arxiv.org
Tensor networks are nowadays the backbone of classical simulations of quantum many-
body systems and quantum circuits. Most tensor methods rely on the fact that we can …

Tensor Network Simulations with Global SU (2) Symmetry

P Schmoll - 2020 - openscience.ub.uni-mainz.de
Die theoretische Beschreibung und Untersuchung von Quanten-Vielteilchensystemen ist ein
essentieller Bestandteil der Erforschung von Quantensystemen bei niedrigen Temperaturen …