Real-world use cases
Accelerating the schedule for quantum-enhanced rail
Accelerate the usefulness of quantum computing for rail scheduling through custom solution development and performance optimization utilizing Fire Opal.
6X
increase in solvable problem size and accelerated timeline to practical quantum advantage by up to 3 years, now estimated for 2028.
We were pleasantly surprised to see the optimal routing of 26 trains over 18 minutes of real scheduling data for the full station topology being realised on a real quantum device, which otherwise wouldn’t have been possible without using Q-CTRL’s optimisation solver.
Nord Quantique is accelerating the path to useful quantum error correction with Boulder Opal
Nord Quantique used Boulder Opal to design a hardware-efficient QEC protocol for a superconducting system where quantum information is encoded in GKP states.
14%
increase in logical qubit lifetime
Given the complexity of the physics at play, being able to perform closed-loop optimization of a few physically motivated parameters of the quantum error correction protocol with Boulder Opal is very valuable to us.
Improving Army logistics with quantum computing
With Fire Opal, the Australian Army tested and validated a quantum computing solution on real hardware that promises to outperform their existing methods.
12X
improvement in the likelihood of finding an optimal solution with Fire Opal over the default hardware execution
Optimally routing 120 convoys can take more than a month of classical computation. The Australian Army is evaluating the potential of quantum computing to provide improvements; however, it’s been difficult to validate the feasibility of a quantum solution due to hardware noise. With Fire Opal, an algorithmic enhancement software, we are able to achieve results on quantum computers that build confidence in our quantum roadmap.
Delivering quantum computing for faster commuting
Improving algorithmic success for Transport for NSW's complex transport network management and congestion problems using quantum control infrastructure software
>200X
Improvement in algorithmic success.
A rare opportunity for leading transport innovators and quantum computing experts to tackle complex transport network management and congestion problems.
