An Efficient User-Side Nulling Calibration for Quantum Annealing Computers

TL;DR

This paper introduces a user-side calibration method for quantum annealing computers that measures and corrects residual biases and estimates qubit temperatures, improving accuracy for Ising model-based quantum computations.

Contribution

It presents a novel, efficient calibration technique that measures residual biases and qubit temperatures, enhancing the performance of quantum annealing systems.

Findings

Residual biases can be effectively measured and nulled.

Qubit temperatures can be estimated using measured distributions.

Calibration improves the accuracy of quantum annealing computations.

Abstract

(Withdrawn) This work describes an efficient user-side method of calibrating and correcting quantum annealing computers. For quantum annealing computers based on the Ising model, the method measures the residual bias of the h and J coefficients. Once measured, these biases can then be nulled in subsequent runs for any problem of interest. This method also returns a temperature for each qubit based on the measured versus the expected qubit distributions computed from a Boltzmann distribution model.