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Various noise models have been developed in quantum computing study to describe the propagation and effect of the noise that is caused by imperfect implementation of hardware. Identifying parameters such as gate and readout error rates is critical to these models. We use a Bayesian inference approach to identify posterior distributions of these parameters such that they can be characterized more elaborately. By characterizing the device errors in this way, we can further improve the accuracy of quantum error mitigation. Experiments conducted on IBM’s quantum computing devices suggest that our approach provides better error mitigation performance than existing techniques used by the vendor. Also, our approach outperforms the standard Bayesian inference method in some scenarios. 

Quantum linear system algorithms (QLSAs) have the potential to speed up algorithms that rely on solving linear systems. Interior point methods (IPMs) yield a fundamental family of polynomial-time algorithms for solving optimization problems. IPMs solve a Newton linear system at each iteration to compute the search direction; thus, QLSAs can potentially speed up IPMs. Due to the noise in contemporary quantum computers, quantum-assisted IPMs (QIPMs) only admit an inexact solution to the Newton linear system. Typically, an inexact search direction leads to an infeasible solution, so, to overcome this, we propose an inexact-feasible QIPM (IF-QIPM) for solving linearly constrained quadratic optimization problems. We also apply the algorithm to ℓ1-norm soft margin support vector machine (SVM) problems, and demonstrate that our algorithm enjoys a speedup in the dimension over existing approaches. This complexity bound is better than any existing classical or quantum algorithm that produces a classical solution. 

Abstract The relative roles of upper- and lower-level thermal forcing in shifting the eddy driven jet are investigated using a multi-level nonlinear quasi-geostrophic channel model. The numerical experiments show that the upper-level thermal forcing is more efficient in shifting the eddy-driven jet. The finite-amplitude wave activity diagnostics of numerical results show that the dominance of the upper-level thermal forcing over the lower-level thermal forcing can be understood from their different influence on eddy generation and dissipation that affects the jet shift. The upper-level thermal forcing shifts the jet primarily by affecting the baroclinic generation of eddies. The lower-level thermal forcing influences the jet mainly by affecting the wave breaking and dissipation. The former eddy response turns out to be more efficient for the thermal forcing to shift the eddy-driven jet. Furthermore, two quantitative relationships based on the imposed thermal forcing are proposed to quantify the response of both eddy generation and eddy dissipation, and thus to help predict the shift of eddy-driven jet in response to the vertically non-uniform thermal forcing. By conducting the overriding experiments in which the response of barotropic zonal wind is locked in the model and a multi-wavenumber theory in which the eddy diffusivity is decomposed to contributions from eddies and mean flow, we find that the eddy generation response is sensitive to the vertical structure of the thermal forcing and can be quantified by the imposed temperature gradient in the upper troposphere. In contrast, the response of eddy diffusivity is almost vertically independent of the imposed forcing, and can be quantified by the imposed vertically-averaged thermal wind.