Quantum pattern recognition with liquid-state nuclear magnetic resonance

TL;DR

This paper introduces a quantum pattern recognition method that integrates Hopfield neural networks with adiabatic quantum computing, enabling recognition of multiple patterns simultaneously via superposition, demonstrated on a two-qubit liquid-state NMR system.

Contribution

It presents a novel quantum pattern recognition algorithm combining neural networks with quantum computation, capable of recognizing multiple patterns in superposition.

Findings

Algorithm successfully recognizes multiple patterns.

Demonstrated on a two-qubit liquid-state NMR quantum computer.

Shows potential for quantum-enhanced pattern recognition.

Abstract

A novel quantum pattern recognition scheme is presented, which combines the idea of a classic Hopfield neural network with adiabatic quantum computation. Both the input and the memorized patterns are represented by means of the problem Hamiltonian. In contrast to classic neural networks, the algorithm can return a quantum superposition of multiple recognized patterns. A proof of principle for the algorithm for two qubits is provided using a liquid state NMR quantum computer.