Data re-uploading for a universal quantum classifier

By Adrián Pérez-Salinas, Alba Cervera-Lierta, Elies Gil-Fuster, José I. Latorre. Quantum, 2019

847 citations recorded by the source corpus.

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 multipledata 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.

Subfields: Artificial Intelligence, Atomic and Molecular Physics, and Optics

View Paper: https://www.semanticscholar.org/paper/7e066e2a44d0b643516f7d4756fd524d9e7c64af

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In Artificial Intelligence

In Atomic and Molecular Physics, and Optics

Citations in the corpus

Effect of data encoding on the expressive power of variational quantum-machine-learning models (2020, methodology): “[17] considered quantum models with sequentially repeated data encodings and conjectured that they are universal function approximators under a special kind of classical data pre-processing.”
Quantum machine learning models are kernel methods (2021, neutral): “I will also consider the embedding fixed and not trainable as proposed in [14, 18].”
Robust data encodings for quantum classifiers (2020, methodology): “We remark that a similar type of generalization was used in [36] with a single qubit classifier that allowed for repeated application of an arbitrary state preparation unitary.”