Experimental verification of the quantum nature of a neural network

TL;DR

This paper explores whether classical neural networks exhibit quantum properties by proposing an experiment to detect entanglement arising from their operational rules, potentially revealing hidden quantum aspects.

Contribution

It introduces a conceptual framework to interpret neural networks as potentially possessing quantum remnants and suggests an experimental approach to verify this hypothesis.

Findings

Proposes a method to extract entanglement from neural network rules

Highlights the dual quantum nature of systems due to constituents and functioning rules

Provides a theoretical basis for neural networks having hidden quantum properties

Abstract

Neural networks are being used to improve the probing of the state spaces of many particle systems as approximations to wavefunctions and in order to avoid the recurring sign problem of quantum monte-carlo. One may ask whether the usual classical neural networks have some actual hidden quantum properties that make them such suitable tools for a highly coupled quantum problem. I discuss here what makes a system quantum and to what extent we can interpret a neural network as having quantum remnants. I suggest that a system can be quantum both due to its fundamental quantum constituents and due to the rules of its functioning, therefore, we can obtain entanglement both due to the quantum constituents' nature and due to the functioning rules, or, in category theory terms, both due to the quantum nature of the objects of a category and of the maps. From a practical point of view, I suggest a possible experiment that could extract entanglement from the quantum functioning rules (maps) of an otherwise classical (from the point of view of the constituents) neural network.