Injective norm of real and complex random tensors I: From spin glasses to geometric entanglement

TL;DR

This paper establishes high-probability bounds on the injective norm of Gaussian random tensors, linking quantum entanglement measures, spin glass models, and advanced probabilistic techniques.

Contribution

It introduces a novel application of the Kac--Rice formula to bound the injective norm, improving upon previous epsilon-net methods for random tensors.

Findings

Provides tight bounds on the injective norm of Gaussian tensors

Connects tensor norms to quantum entanglement and spin glass models

Uses Kac--Rice formula for probabilistic bounds

Abstract

The injective norm is a natural generalization to tensors of the operator norm of a matrix. In quantum information, the injective norm is one important measure of genuine multipartite entanglement of quantum states, where it is known as the geometric entanglement. In this paper, we give a high-probability upper bound on the injective norm of real and complex Gaussian random tensors, corresponding to a lower bound on the geometric entanglement of random quantum states, and to a bound on the ground-state energy of a particular multispecies spherical spin glass model. For some cases of our model, previous work used $\epsilon$-net techniques to identify the correct order of magnitude; in the present work, we use the Kac--Rice formula to give a one-sided bound on the constant which we believe to be tight.