Quantum Annealing as a Chemical Kinetics Solver for Pollutant Transport Models

Abstract

In the past years, quantum computing has been proved to have a huge potential in a wide range of applications, such as cryptography, finance and material science, although its applicability in the world of ambient intelligence and smart cities is still under study. This paper aims to shed light on this, specifically, regarding its application in the current models for air quality and dispersion of contaminants used in pollution monitoring, which typically imply large computational costs. Among all the procedures and techniques in the field, the quantum annealing paradigm is the one that has shown a more mature state of development and seems to be the most promising solution for industrial applications at the moment, particularly excelling in optimization problems. For this reason, quantum annealing was chosen to test its capability in solving chemical kinetic problems, which usually consist in sets of coupled differential equations whose linearity depends on the complexity of the system. A simple chemical system was proposed and solved by a quantum annealer, comparing its solution to one obtained by classical methods in terms of precision, time and scalability. The study shows that these problems can be already solved by quantum computers to a certain degree of accuracy but they lack some key features to be a viable substitute for classical methods at the moment. Quantum annealing is thus positioned as a promising tool due to its scalability, only awaiting suitable hardware that enables the proper treatment of these problems.