Saved in:
Bibliographic Details
Main Authors: Malz, Daniel, Trivedi, Rahul
Format: Preprint
Published: 2024
Subjects:
Online Access:https://arxiv.org/abs/2402.07975
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1866912261460721664
author Malz, Daniel
Trivedi, Rahul
author_facet Malz, Daniel
Trivedi, Rahul
contents We determine the computational power of isometric tensor network states (isoTNS), a variational ansatz originally developed to numerically find and compute properties of gapped ground states and topological states in two dimensions. By mapping 2D isoTNS to 1+1D unitary quantum circuits, we find that computing local expectation values in isoTNS is $\textsf{BQP}$-complete. We then introduce injective isoTNS, which are those isoTNS that are the unique ground states of frustration-free Hamiltonians, and which are characterized by an injectivity parameter $δ\in(0,1/D]$, where $D$ is the bond dimension of the isoTNS. We show that injectivity necessarily adds depolarizing noise to the circuit at a rate $η=δ^2D^2$. We show that weakly injective isoTNS (small $δ$) are still $\textsf{BQP}$-complete, but that there exists an efficient classical algorithm to compute local expectation values in strongly injective isoTNS ($η\geq0.41$). Sampling from isoTNS corresponds to monitored quantum dynamics and we exhibit a family of isoTNS that undergo a phase transition from a hard regime to an easy phase where the monitored circuit can be sampled efficiently. Our results can be used to design provable algorithms to contract isoTNS. Our mapping between ground states of certain frustration-free Hamiltonians to open circuit dynamics in one dimension fewer may be of independent interest.
format Preprint
id arxiv_https___arxiv_org_abs_2402_07975
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Computational complexity of isometric tensor network states
Malz, Daniel
Trivedi, Rahul
Quantum Physics
Computational Complexity
We determine the computational power of isometric tensor network states (isoTNS), a variational ansatz originally developed to numerically find and compute properties of gapped ground states and topological states in two dimensions. By mapping 2D isoTNS to 1+1D unitary quantum circuits, we find that computing local expectation values in isoTNS is $\textsf{BQP}$-complete. We then introduce injective isoTNS, which are those isoTNS that are the unique ground states of frustration-free Hamiltonians, and which are characterized by an injectivity parameter $δ\in(0,1/D]$, where $D$ is the bond dimension of the isoTNS. We show that injectivity necessarily adds depolarizing noise to the circuit at a rate $η=δ^2D^2$. We show that weakly injective isoTNS (small $δ$) are still $\textsf{BQP}$-complete, but that there exists an efficient classical algorithm to compute local expectation values in strongly injective isoTNS ($η\geq0.41$). Sampling from isoTNS corresponds to monitored quantum dynamics and we exhibit a family of isoTNS that undergo a phase transition from a hard regime to an easy phase where the monitored circuit can be sampled efficiently. Our results can be used to design provable algorithms to contract isoTNS. Our mapping between ground states of certain frustration-free Hamiltonians to open circuit dynamics in one dimension fewer may be of independent interest.
title Computational complexity of isometric tensor network states
topic Quantum Physics
Computational Complexity
url https://arxiv.org/abs/2402.07975