Noise Modeling of the IBM Quantum Platform
Yasuo Oda, Omar Shehab, Gregory Quiroz · 2023
The influence of noise in quantum dynamics is one of the main factors preventing current quantum processors from performing quantum computations. Errors must be addressed, which requires a thorough understanding of the nature and interplay of different sources of noise. In this work, we propose an effective error model of single-qubit operations on the IBM Quantum Platform (IBMQP), that possesses considerable predictive power. We showcase how Quantum Noise Spectroscopy (QNS) can be used alongside other error characterization techniques to obtain a more complete error model of the system. The model allows for both Markovian and spatio-temporally correlated non-Markovian environmental and control effects. Model parameters are obtained from a small set of characterization experiments. We show that simulations using this error model are capable of accurately predicting new experimental results.