Implementing a distance-based classifier with a quantum interference circuit

Understand

Lately, much attention has been given to quantum algorithms that solve pattern recognition tasks in machine learning.

• Many of these quantum machine learning algorithms try to implement classical models on large-scale universal quantum computers that have access to non-trivial subroutines such as Hamiltonian simulation, amplitude amplification and phase estimation.
• We approach the problem from the opposite direction and analyse a distance-based classifier that is realised by a simple quantum interference circuit.
• After state preparation, the circuit only consists of a Hadamard gate as well as two single-qubit measurements, and computes the distance between data points in quantum parallel.