Publications

Constructing driver Hamiltonians for optimization problems with linear constraints

Abstract

Recent advances in the field of adiabatic quantum computing and the closely related field of quantum annealing have centered around using more advanced and novel Hamiltonian representations to solve optimization problems. One of these advances has centered around the development of driver Hamiltonians that commute with the constraints of an optimization problem—allowing for another avenue to satisfying those constraints instead of imposing penalty terms for each of them. In particular, the approach is able to use sparser connectivity to embed several practical problems on quantum devices in comparison to the standard approach of using penalty terms. However, designing the driver Hamiltonians that successfully commute with several constraints has largely been based on strong intuition for specific problems and with no simple general algorithm for generating them for arbitrary constraints. In this work …

Date
November 25, 2021
Authors
Hannes Leipold, Federico M Spedalieri
Journal
Quantum Science and Technology
Volume
7
Issue
1
Pages
015013
Publisher
IOP Publishing