the Qiskit Functions Catalog
Last year, researchers began exploring problems that are difficult to simulate with brute-force classical methods, thanks to utility-scale quantum computers available on IBM QuantumTM Platform. But those experiments required a deep understanding of not just the quantum processing unit (QPU), but also the various error suppression and mitigation methods required to scale each individual problem.
A new way to code with Qiskit
At present, researchers mostly write quantum programs at the circuit level, requiring hand-coding that incorporates the intricacies of our hardware. Therefore, there’s still a lot of development time and expertise required in order to access the utility-scale performance of our hardware and software. Further, utility-scale programming might sit beyond the abilities of those without the deepest quantum computing backgrounds. That’s what Qiskit Functions and the Qiskit Functions Catalog are for.
Qiskit Functions is a programming service that allow access to high-performance quantum hardware and software at a higher abstraction level. After importing the Qiskit Function Catalog and passing it their API token, users add the function to their code and pass it the required inputs — such as classical data they’d like to map and run on quantum circuits. The IBM-managed service runs the code on a quantum computer and applies error suppression and mitigation, then the user receives their results.
Taking optimization as an example, today, the user must take the linear system graph, map the graph to Ising circuits and observables, transpile the code for the target hardware, run the runtime primitives, and tweak the error mitigation and suppression so that you can get good result — requiring knowledge of what a good result looks like. You further need to iterate over the circuit running to establish the best parameters. But with Q-CTRL’s Fire Opal Optimization Solver, the user only needs to pass the graph to the function, and the Solver will return highly accurate solutions alongside various information about the optimization process, such as the number of iterations.
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