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When Quantum Meets AI: Quantum Methods for Machine Learning and Machine Learning Methods for Quantum Systems

arXiv · AI, language, vision and robotics · article · Sep 22, 2026 · UTC

This thesis studies the intersection of quantum computing and artificial intelligence in two directions: quantum methods for machine learning and machine learning methods for quantum systems. For quantum machine learning, Neural Quantum Embedding learns data representations that increase the trace distance between embedded class ensembles, lowering an embedding-dependent bound on empirical risk and improving classification on noisy quantum hardware. A training objective based on the Hilbert-Schmidt inner product extends this approach to deterministic quantum computation with one qubit (DQC1) a

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