Q-CTRL has developed a quantum-enhanced solver for rail scheduling in collaboration with Network Rail and the UK Department for Transport. Using its Fire Opal performance optimization platform, Q-CTRL executed real-world scheduling problems on IBM quantum hardware, setting a new record for the largest constrained quantum optimization problem solved to date. The approach enabled accurate train routing for 26 trains at London Bridge Station over an 18-minute period, using a formulation that required 103 qubits.
The project, supported by a £1 million ($1.4 million USD) award under the UK SBRI Quantum Catalyst Fund, targeted two rail scheduling sub-problems: station routing and train timetabling. Both were formulated as combinatorial MaxSAT problems, suitable for Fire Opal’s solver. The solver incorporates quantum error suppression, problem-specific workflows, and classical preprocessing to increase the tractability of large optimization problems, with tests showing up to a 6X increase in problem size solvable using current hardware.
Based on current hardware roadmaps, Q-CTRL estimates its solver could outperform classical methods as early as 2028. This collaboration demonstrates measurable progress toward quantum advantage for high-impact public sector challenges and reflects broader applicability in domains such as logistics, defense, and aerospace. The solver will be further productized for industry use.
For more, see the full case study here.
May 23, 2025
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