Dr Francesco Cosco

Bayesian mitigation of measurement errors in multiqubit experiments

We introduce a Bayesian error mitigation implementation tailored for multiqubit experiments conducted on near-term quantum devices. Our approach leverages complete information from the readout signal, available prior to any binary state assignment of the qubits. We provide a detailed workflow of the algorithm, starting from the calibration of detector response functions to the post-processing of measurement outcomes, offering a computationally efficient solution suitable for the output size typical of current quantum computing devices. We benchmark our protocol on actual quantum computers with superconducting qubits where the readout signal encodes the measurement information in the IQ clouds before the qubit state assignment. Finally, we compare our algorithm performances against other measurement error methods.