Finding Solutions to Ising Problems Using the Scaffold Quantum Programming Language

Abstract

Quantum computing offers the potential for novel tractable solutions to a variety of problems, with one general class of problems being optimization. Methods like adiabatic quantum computing and the Quantum Approximate Optimization Algorithm stand out as candidates to find solutions to classically-challenging optimization problems. Here, my report demonstrates two versions of solvers for Ising spin chain problems using a digitized version of the Adiabatic Algorithm as well as the Quantum Approximate Optimization Algorithm. Written in the quantum programming language Scaffold, these solvers are able to run on different simulators and interfaces, and have the capacity to be applied to various types of Ising problems.