Author

Mark M. Wilde

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Preprint Jul 2026

Quantum Spectral Anomaly Detection

A core task in quantum anomaly detection is to compute an anomaly score that quantifies how strongly a test quantum state deviates from a given quantum dataset assumed to be normal. Classically, principal component analysis (PCA) for centered data computes the anomaly score by evaluating the test sample relative to the...

Yewei Yuan, Michele Minervini, Mark M. Wilde et al. · 1 citation

Preprint Jul 2026

Canonical quantization of neurons

This work establishes canonical quantization as a principled framework for constructing quantum machine learning primitives and provides a foundation for developing neural architectures tailored to quantum data.

Alexander He, Nana Liu, Mark M. Wilde · 1 citation

Preprint Aug 2026

Unifying quantum measurement constructions via a relative-entropy minimum change principle

The minimum change principle provides an information-theoretic characterization of the Bayes reversal channel in classical probability theory and has recently been proposed as a framework for extending Bayes'rule to quantum information theory. Using quantum relative entropy, we investigate a minimum change principle fo...

Nana Liu, Mark M. Wilde · 2 citations