Spiking neuromorphic chip learns entangled quantum states

TL;DR

This paper demonstrates that a spike-based neuromorphic chip can effectively simulate and represent entangled quantum states, offering a high-energy-efficient platform for quantum system simulations.

Contribution

It introduces a neuromorphic hardware prototype capable of representing entangled quantum states with high fidelity, bridging neuromorphic computing and quantum simulation.

Findings

Successfully represented two-qubit entangled states

Captured Bell correlations in pure and mixed states

Demonstrated high fidelity in quantum state approximation

Abstract

The approximation of quantum states with artificial neural networks has gained a lot of attention during the last years. Meanwhile, analog neuromorphic chips, inspired by structural and dynamical properties of the biological brain, show a high energy efficiency in running artificial neural-network architectures for the profit of generative applications. This encourages employing such hardware systems as platforms for simulations of quantum systems. Here we report on the realization of a prototype using the latest spike-based BrainScaleS hardware allowing us to represent few-qubit maximally entangled quantum states with high fidelities. Bell correlations of pure and mixed two-qubit states are well captured by the analog hardware, demonstrating an important building block for simulating quantum systems with spiking neuromorphic chips.