Classical Ensembles of Single-Qubit Quantum Variational Circuits for
Classification
- URL: http://arxiv.org/abs/2302.02964v1
- Date: Mon, 6 Feb 2023 17:51:47 GMT
- Title: Classical Ensembles of Single-Qubit Quantum Variational Circuits for
Classification
- Authors: Shane McFarthing, Anban Pillay, Ilya Sinayskiy and Francesco
Petruccione
- Abstract summary: Quantumally universal multi-feature (QAUM) encoding architecture was recently introduced and showed improved expressivity and performance in classifying pulsar stars.
This work reports on the design, implementation, and evaluation of ensembles of single-qubit QAUM classifiers using classical bagging and boosting techniques.
- Score: 0.0
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: The quantum asymptotically universal multi-feature (QAUM) encoding
architecture was recently introduced and showed improved expressivity and
performance in classifying pulsar stars. The circuit uses generalized trainable
layers of parameterized single-qubit rotation gates and single-qubit feature
encoding gates. Although the improvement in classification accuracy is
promising, the single-qubit nature of this architecture, combined with the
circuit depth required for accuracy, limits its applications on NISQ devices
due to their low coherence times. This work reports on the design,
implementation, and evaluation of ensembles of single-qubit QAUM classifiers
using classical bagging and boosting techniques. We demonstrate an improvement
in validation accuracy for pulsar star classification. We find that this
improvement is not problem-specific as we observe consistent improvements for
the MNIST Digits and Wisconsin Cancer datasets. We also observe that the
boosting ensemble achieves an acceptable level of accuracy with only a small
amount of training, while the bagging ensemble achieves higher overall accuracy
with ample training time. This shows that classical ensembles of single-qubit
circuits present a new approach for certain classification problems.
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