Unlock quantum optimization on IonQ

With real-world applications in optimization, chemistry, materials science, and more, Fire Opal brings noise-resilient optimization directly to IonQ’s trapped ion processors, helping users abstract quantum hardware complexities and improve the success of algorithms by 1,000X.

By optimizing algorithms and reducing errors during runtime, Fire Opal lets you scale to larger problems: deeper circuits with more gates and qubits. At the same time, it delivers correct answers in fewer shots and with no additional overhead, reducing compute time and cost.

The Fire Opal Quantum Approximate Optimization Algorithm (QAOA) Solver lets you define complex combinatorial problems like Max-Cut or MaxSAT and execute them on IonQ hardware without manually writing quantum circuits. The solver automatically maps your problem to the hardware, optimizes circuit parameters, and automatically implements a comprehensive error-suppression pipeline with no manual adjustments, no settings, and no configuration required. This enables you to realize high-fidelity results and accelerate your time-to-solution for real-world optimization challenges.

With this native integration, Fire Opal helps you get the most out of your IonQ processor and handles the quantum complexities while you focus on innovation.