Cambridge Quantum has undertaken a partnership with rail service provider and Deutsche Bahn subsidiary Deutsche Bahn Netz AG (DB) to see how advanced computing can help the industry.
They are specifically examining how Quantum computing can improve the rescheduling of rail traffic as part of DB’s long-term transformative plan, Digitale Schiene Deutschland. This aims to improve DB’s infrastructure and railway system using next-generation technologies to achieve a higher capacity and optimal use of the rail network.
Bringing together Cambridge Quantum’s latest combinatorial optimisation algorithm, Filtering Variational Quantum Eigensolver (F-VQE) – which the company says has been demonstrated to outperform leading quantum algorithms – with DB’s operations research expertise, the team has already re-optimised realistic train timetables after simulated delays and are now identifying areas for continued study.
Cambridge Quantum says this collaboration evidences how innovations in both quantum algorithms and domain-specific modelling can inform a long-term vision for a faster and greener transportation network.
Ilyas Khan, CEO of Cambridge Quantum, said: “We are very excited to be working with Deutsche Bahn to explore and demonstrate the utility of today’s Noisy Intermediate Scale Quantum (“NISQ”) processors to solve real-world problems in the transport and logistics sector. Deutsche Bahn’s research and development efforts in this area are of critical importance, and we are confident that over time as quantum computers start to scale, our work with them will lead to a meaningful contribution towards a cleaner and greener future.”
Michael Küpper, lead of Capacity and Traffic Management System at Digitale Schiene Deutschland, said: “The collaboration with Cambridge Quantum is a perfect example of how Deutsche Bahn is working as a partner with industry providers and combining our relative expertise towards a goal neither side can achieve alone.
“By working with Cambridge Quantum, we have fine-tuned our research and development plans and taken the first steps in defining a future quantum-advantaged train timetabling system. We are excited to continue working with Cambridge Quantum to address some of the key challenges and contribute to the rapidly evolving field of NISQ quantum algorithm research.”