Quantum Perceptron Models

Quantum computation is an emerging technology that utilizes quantum effects to achieve significant, and in some cases exponential, speedups of algorithms over their classical counterparts. The growing importance of machine learning has in recent years led to a host of studies that investigate the promise of quantum computers for machine learning [1, 2, 12, 13, 17, 21-23]. While a number of important quantum speedups have been found, the majority of these speedups are due to replacing a classical subroutine with an equivalent albeit faster quantum algorithm. The true potential of quantum algorithms may therefore remain underexploited since quantum algorithms have been constrainted to follow the same methodology behind traditional machine learning methods [2, 7, 22]. Here we consider an alternate approach: we devise a new machine learning algorithm that is tailored to the speedups that quantum computers can provide.