Nomad_Soul - Fotolia

Cambridge Quantum tackles rail optimisation for German operator

Among the promises of quantum computing is to run combinational optimisation for tasks such as complex train scheduling to minimise disruption

DB Netz, a subsidiary of German railway company Deutsche Bahn, is working in partnership with Cambridge Quantum to explore how quantum computers can improve the rescheduling of rail traffic. The project is exploring how new algorithms running on smaller-scale quantum computers can be used to optimise rail planning.

DB Netz is the service provider managing a rail infrastructure comprising nearly 33,300km. As part of a sector-wide digitisation strategy, Digitale Schiene Deutschland,  DB Netz recently combined Cambridge Quantum’s latest combinatorial optimisation algorithm Filtering Variational Quantum Eigensolver (F-VQE) with its own operations research expertise to re-optimise realistic train timetables after simulated delays.

The collaboration is looking at how to apply Noisy Intermediate Scale Quantum (NISQ) processors to solve real-world problems in the transport and logistics sector.

F-VQE uses a technique that enables combinatorial optimisation problems to run on smaller quantum systems. A simple example of combinatorial optimisation is the traveling salesman problem. Given the (x, y) coordinates of a finite number of different cities, combinatorial optimisation involves calculating the shortest possible path in which the salesman visits each city exactly once.

While a human can easily draw an optimal route for the travelling salesman to visit a handful of cities, this becomes impossible as the number of cities, and therefore the complexity, increases. It is this type of problem area that is well suited to quantum computing, and one that transportation, logistics and rail operators need to tackle.

F-VQE enables quantum circuits to be decomposed into smaller circuits and run using fewer qubits without losing quantum advantage. When Cambridge Quantum demonstrated F-VQE earlier this year, it said a 23-qubit problem was solved by using no more than six hardware qubits at a time. 

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.”

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 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 will lead to a meaningful contribution towards a cleaner and greener future.”

Read more about quantum computing

Read more on Chips and processor hardware

Data Center
Data Management