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Model-Based Optimization of Superconducting Qubit Readout

Andreas Bengtsson, Alex Opremcak, Mostafa Khezri, D. Sank, Alexandre Bourassa, Kevin J. Satzinger, Sabrina Hong, Catherine Erickson, Brian Lester, Kevin C. Miao, Alexander N. Korotkov, J. Kelly, Zijun Chen, Paul V. Klimov

2024Physical Review Letters32 citationsDOI

Abstract

Measurement is an essential component of quantum algorithms, and for superconducting qubits it is often the most error prone. Here, we demonstrate model-based readout optimization achieving low measurement errors while avoiding detrimental side effects. For simultaneous and midcircuit measurements across 17 qubits, we observe 1.5% error per qubit with a 500 ns end-to-end duration and minimal excess reset error from residual resonator photons. We also suppress measurement-induced state transitions achieving a leakage rate limited by natural heating. This technique can scale to hundreds of qubits and be used to enhance the performance of error-correcting codes and near-term applications.

Topics & Concepts

QubitSuperconductivityPhysicsReset (finance)Phase qubitQuantum computerResidualFlux qubitQuantumComputer scienceTopology (electrical circuits)Quantum mechanicsAlgorithmElectrical engineeringEconomicsEngineeringFinancial economicsQuantum Computing Algorithms and ArchitectureQuantum Information and CryptographyNeural Networks and Reservoir Computing