Quantum Computing

Q-CTRL Introduces a new QAOA Solving Feature in their Fire Opal Fault Mitigation Software

Diagram of How the Fire Opal QAOA Optimizer Provides Solutions. Credit: Q-CTRL

That Quantum Approximation Optimization Algorithm (QAOA) is a popular iterative classical/quantum algorithm that takes an iterative approach with two processors working together to find the optimal solution to a problem with a given set of inputs. While the algorithm may not be too hard to program, it can be much more challenging to use it and get an accurate solution.

Q-CTRL have introduced a new feature in their Python base Fire Opal Fault Mitigation software package which can automate and substantially improve the quality of answers when running a QAOA program on a real quantum computer. This simplifies the input process as the user only needs to enter the graph and objective, or cost function instead of submitting a quantum circuit. QAOA solvers will leverage Fire Opal’s built-in features, such as reduced gate depth, optimized gate placement, elimination of crosstalk, optimization of control pulses, mitigation of metering errors, and other techniques to substantially improve response quality while reducing the number of steps. For end users this will save time and money.

For more information about this new QAOA Solver, you can view the three documents posted on the Q-CTRL website. Blog post announcing it is available Heredocumentation page can be found Hereand tutorial examples of its use to troubleshoot MaxCut can be seen Here.

April 6, 2023


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