Scaling up gate set tomography: efficient 4-qubit characterization on a superconducting qubit device
ORAL
Abstract
Gate Set Tomography (GST) has been a standard characterization tool for over a decade. However, scaling GST to multiple-qubit systems is challenging due to the rapidly increasing required experimental effort and subsequent data processing.
In this work, we extend GST to four qubits and use it to capture multi-qubit entangling errors and crosstalk dynamics accurately. To this end, we formulate the GST data-processing step as a constrained low-rank optimization problem and solve it using a second-order Riemannian method, as it is supported by convergence guarantees. In addition to enabling computational efficiency, the techniques employed allow us to study the algorithm’s complexity in detail. Finally, we demonstrate the applicability of our approach by running four-qubit GST experiments on IQM’s superconducting qubit devices.
In this work, we extend GST to four qubits and use it to capture multi-qubit entangling errors and crosstalk dynamics accurately. To this end, we formulate the GST data-processing step as a constrained low-rank optimization problem and solve it using a second-order Riemannian method, as it is supported by convergence guarantees. In addition to enabling computational efficiency, the techniques employed allow us to study the algorithm’s complexity in detail. Finally, we demonstrate the applicability of our approach by running four-qubit GST experiments on IQM’s superconducting qubit devices.
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Presenters
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Emiliano Godinez Ramirez
- IQM Germany