Formulation and implementation of a support vector machine on D-Wave’s quantum annealer

The main focus is the mathematical formulation and implementation of a support vector machine (SVM) algorithm in D-Wave’s quantum annealer. The first step was to formulate the problem as a quadratic unconstrained binary optimization (QUBO) problem. With some adaptations, physical limitations of the quantum computer were overcome. Finally, I coded the algorithm and executed it in the quantum annealer, along with a local simulated annealing version, and its classification performance was compared against that of the classical algorithm. Through the proposal of a QUBO formulation of an SVM algorithm, it has been proven that it is possible to solve it in a quantum annealer and when executed with two datasets, excellent classifications were obtained, while not evidencing any quantum advantage.

Category: COMPUTING Country: SPAIN Year: 2021


Carla Caro Villanova