Self-Consistent Calibration of Quantum Gate Sets

Abstract

The precise and automated calibration of quantum gates is a key requirement for building a reliable quantum computer. Unlike errors from decoherence, systematic errors can in principle be completely removed by tuning experimental parameters. Here, we present an iterative calibration routine which can remove systematic gate errors on several qubits. A central ingredient is the construction of pulse sequences that extract independent indicators for every linearly independent error generator. We show that decoherence errors only moderately degrade the achievable infidelity due to systematic errors. Furthermore, we investigate the convergence properties of our approach by performing simulations for a specific qubit encoded in a pair of spins. Our results indicate that a gate set with 230 gate parameters can be calibrated in about ten iterations, after which incoherent errors limit the gate fidelity.

arXiv comment16 pages, 3 figures, 7 tables. Reprinted with permission from Pascal Cerfontaine, René Otten, and Hendrik Bluhm, Physical Review Applied 13, 044071 (2020). Copyright 2020 by the American Physical Society

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Cited by in corpus (13)

• Gate Set Tomography
• Computational advantage of quantum random sampling
• Closed-loop control of a GaAs-based singlet-triplet spin qubit with 99.5% gate fidelity and low leakage
• High-fidelity gate set for exchange-coupled singlet-triplet qubits
• Filter Functions for Quantum Processes under Correlated Noise
• qopt: An experiment-oriented Qubit Simulation and Quantum Optimal Control Package
• Natural parameterized quantum circuit
• Operational, gauge-free quantum tomography
• Semi-device-dependent blind quantum tomography
• Nonlinear Signal Distortion Corrections Through Quantum Sensing
• Correcting on-chip distortion of control pulses with silicon spin qubits
• Filter Function Formalism and Software Package to Compute Quantum Processes of Gate Sequences for Classical Non-Markovian Noise
• Quantum Process Tomography with Digital Twins of Error Matrices