Projected impact: Disruptive
Timeframe: Within 10 years
Jonas Bylander, Chalmers university of technology
Per Olof Arnäs, Chalmers university of technology
Quantum computing was envisioned, in the 1980s, as a new way to process information by using quantum-superposition states – the strange properties of quantum particles allowing them to occupy multiple positions at the same time. Exploiting this, a new branch of applied mathematics emerged – quantum information science (https://en.wikipedia.org/wiki/Quantum_computing).
Whereas a conventional (classical) algorithm works by manipulating data bits (0 or 1), a quantum algorithm is a sequence of operations on quantum bits (qubits) in quantum superposition of 0 and 1. This “quantum parallelism” enables new ways of processing information which are impossible on a classical computer.
Here, quantum computing is explained by IBM:
Many large problems relevant to transportation and supply chain management – such as finding the optimal route or resource allocation – are computationally hard and require significant computer resources; they can even be impossible to solve within a realistic time on an ordinary, classical computer.
Instead, some hard problems can be mapped onto a mathematical expression describing the energy of a system of coupled qubits. The solution of the optimization problem is then given by the minimum-energy configuration of the qubits. One can build a quantum computer adapted to this type of problem and devise quantum algorithms to solve them. There is widespread belief in the quantum information science community that quantum algorithms can solve such problems efficiently, whereas a conventional computer algorithm cannot; this is sometimes called “quantum supremacy.”
Quantum computer technology is currently a very active research field worldwide, including academic groups, institutes, large companies, and venture-backed start-ups. There are still many hurdles on the road to constructing a practically useful quantum computer. Most significantly, there is need for research into better, scalable quantum hardware, which is prone to errors because of the very nature of the fragile quantum states of the qubits, and ways to operate quantum processors in the presence of errors. Also important are the development of software for the quantum computer as well as relevant use cases, for example within the transportation industry.
Chalmers hosts a big research effort in quantum computing within WACQT, the Wallenberg Centre for Quantum Technology, and through the project OpenSuperQ within the EU Flagship on Quantum Technology. Our quantum hardware is state of the art and we aim to build a Swedish quantum computer. As an industry partner of WACQT, the company Jeppesen (a subsidiary of Boeing specialized in flight crew scheduling) is actively participating with one industrial PhD student contributing to the development of quantum computing use cases relevant to optimization within logistics.
Examples from industry
Volkswagen is using quantum computing to forecast traffic volumes (https://www.volkswagen-newsroom.com/en/press-releases/volkswagen-ensures-intelligent-traffic-management-with-quantum-computers-4347)