# Data re-uploading for a universal quantum classifier

## TL;DR

This paper demonstrates that a single qubit, with data re-uploading and classical assistance, can serve as a universal quantum classifier capable of handling complex, multi-dimensional data, with enhanced efficiency through multi-qubit entanglement.

## Contribution

It introduces a novel approach of data re-uploading in quantum circuits to achieve universal classification with a single qubit, extending to multi-qubit systems for improved performance.

## Key findings

- Single qubit with data re-uploading can classify complex data.
- Multi-qubit systems leverage entanglement for better efficiency.
- Extensive benchmarking confirms the method's effectiveness.

## Abstract

A single qubit provides sufficient computational capabilities to construct a universal quantum classifier when assisted with a classical subroutine. This fact may be surprising since a single qubit only offers a simple superposition of two states and single-qubit gates only make a rotation in the Bloch sphere. The key ingredient to circumvent these limitations is to allow for multiple data re-uploading. A quantum circuit can then be organized as a series of data re-uploading and single-qubit processing units. Furthermore, both data re-uploading and measurements can accommodate multiple dimensions in the input and several categories in the output, to conform to a universal quantum classifier. The extension of this idea to several qubits enhances the efficiency of the strategy as entanglement expands the superpositions carried along with the classification. Extensive benchmarking on different examples of the single- and multi-qubit quantum classifier validates its ability to describe and classify complex data.