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QUILT: Effective Multi-Class Classification on Quantum Computers Using an Ensemble of Diverse Quantum Classifiers
Daniel Silver, Tirthak Patel, Devesh Tiwari·June 28, 2022·DOI: 10.1609/aaai.v36i8.20807
Computer SciencePhysics
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Abstract
Quantum computers can theoretically have significant acceleration over classical computers; but, the near-future era of quantum computing is limited due to small number of qubits that are also error prone. QUILT is a framework for performing multi-class classification task designed to work effectively on current error-prone quantum computers. QUILT is evaluated with real quantum machines as well as with projected noise levels as quantum machines become more noise free. QUILT demonstrates up to 85% multi-class classification accuracy with the MNIST dataset on a five-qubit system.