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The geometry of quantum learning

Markus Hunziker·David A. Meyer·Jihun Park·James Pommersheim·Mitch Rothstein
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Abstract

Concept learning provides a natural framework in which to place the problems solved by the quantum algorithms of Bernstein-Vazirani and Grover. By combining the tools used in these algorithms--quantum fast transforms and amplitude amplification--with a novel (in this context) tool--a solution method for geometrical optimization problems--we derive a general technique for quantum concept learning. We name this technique "Amplified Impatient Learning" and apply it to construct quantum algorithms solving two new problems: BATTLESHIP and MAJORITY, more efficiently than is possible classically.

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Markus Hunziker, David A. Meyer, Jihun Park, James Pommersheim, Mitch Rothstein. 2003-09-05. The geometry of quantum learning. https://arxiv.org/abs/quant-ph/0309059

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