Booting a quantum computer: A QUA-based graph framework for automatic qubit calibration, measurement, and execution of hybrid classical-quantum algorithms

Deploying algorithms on real-world quantum computers requires calibration and optimization steps, the complexity of which scales with the system’s size. These typically involve an interplay between quantum circuit execution on quantum hardware and classical processing of results on classical hardware. Interestingly, some of the most promising candidate algorithms for demonstrating quantum advantage in the next decade are, in fact, quantum-classical hybrid algorithms. Therefore, an automated framework for hybrid execution for efficiently running such protocols is highly desired.
We have developed an open-source framework which allows arranging and executing quantum and classical experimental steps as a directed acyclic graph (DAG). The framework is built on top of Python and QUA, a pulse-level cross-quantum-platform programming language. We showcase these abilities by a reference implementation of automated calibration, followed by the HHL algorithm’s execution targeting a system containing two superconducting qudits.

Prepared in part by LLNL under Contract DE-AC52-07NA2734. LLNL-ABS-816411