Real-world use cases
Featured customer stories
Enabling data loading for quantum machine learning with Fire Opal
Using Fire Opal, BlueQubit demonstrated groundbreaking loading of complex “distribution” information onto 20 qubits for a QML application by reducing the effect of noise and error in the loading process. This is an exciting example of how Q-CTRL’s focus on “AI for quantum” can drive direct advances in our partners’ efforts to apply “Quantum for AI.”
8X
Better performance in terms of Total Variational Distance (TVD), which measures the deviation from perfect data loading.
As we develop novel techniques to solve some of the quantum industry’s hardest challenges, Fire Opal is an essential tool to reduce the impact of hardware noise and demonstrate successful results with deeper and wider circuits.
Improving Army logistics with quantum computing
Fire Opal improved the performance of quantum computers to a level that the early results could finally give the Army confidence that quantum route optimization could be a feasible way to improve convoy logistics, allowing them to build a roadmap toward implementing the solution at scale.
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.
Nord Quantique is accelerating the path to useful quantum error correction with Boulder Opal
Employing Boulder Opal’s closed-loop optimization engine, Nord Quantique successfully demonstrated a quantum error correction protocol that extends the lifetime of their logical qubit over the case without quantum error correction.
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.
Northwestern looks to the heart of the universe with robust quantum sensors
With Boulder Opal, Northwestern was able to design noise-robust pulses for cold atom interferometers 10x better than alternatives, opening the way to build devices capable of detecting dark matter and gravitational waves.
5
different noise sources can be suppressed simultaneously with a single optimized robust control pulse for atom interferometry.
The breadth and flexibility of Boulder Opal allowed us to create our own optimization scenario and obtain pulses robust to the five most relevant experimental noise sources at the same time!
