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Freie Universität Berlin, Helmholtz-Zentrum Berlin fßr Materialien und Energie
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Classical algorithms struggle to learn quantum dynamics efficiently, revealing a stark separation that underscores the power of quantum machine learning.
Quantum machine learning inference can be quadratically sped up by estimating a single observable, rather than summing individual kernel values, achieving query optimality.
