Typical Correlation Length of Sequentially Generated Tensor Network States
Daniel Haag, Flavio Baccari, Georgios Styliaris

TL;DR
This paper investigates the typical correlation length in random tensor network states generated sequentially, revealing exponential decay of correlations and dimension-dependent effects of bond dimension on correlation length.
Contribution
It introduces ensembles of sequentially generated tensor network states in 1D and 2D, analyzing their correlation decay and deriving the typical correlation length behavior.
Findings
Correlation length depends only on spatial dimension.
Exponential decay of correlations in typical states.
Bond dimension increases correlation length in 1D, decreases it in 2D.
Abstract
The complexity of quantum many-body systems is manifested in the vast diversity of their correlations, making it challenging to distinguish the generic from the atypical features. This can be addressed by analyzing correlations through ensembles of random states, chosen to faithfully embody the relevant physical properties. Here, we focus on spins with local interactions, whose correlations are extremely well captured by tensor network states. Adopting an operational perspective, we define ensembles of random tensor network states in one and two spatial dimensions that admit a sequential generation. As such, they directly correspond to outputs of quantum circuits with a sequential architecture and random gates. In one spatial dimension, the ensemble explores the entire family of matrix product states, while in two spatial dimensions, it corresponds to random isometric tensor network…
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Taxonomy
TopicsQuantum many-body systems · Quantum Computing Algorithms and Architecture · Quantum and electron transport phenomena
