Characterizing and mitigating coherent errors in a trapped ion quantum processor using hidden inverses

Abstract

Quantum computing testbeds exhibit high-fidelity quantum control over small collections of qubits, enabling performance of precise, repeatable operations followed by measurements. Currently, these noisy intermediate-scale devices can support a sufficient number of sequential operations prior to decoherence such that small algorithms can be performed reliably. While the results of these algorithms are imperfect, these imperfections can help bootstrap quantum computer testbed development. Demonstrations of these small algorithms over the past few years, coupled with the idea that imperfect algorithm performance can be caused by several dominant noise sources in the quantum processor, which can be measured and calibrated during algorithm execution or in post-processing, has led to the use of noise mitigation to improve typical computational results. Conversely, small benchmark algorithms coupled with noise mitigation can help diagnose the nature of the noise, whether systematic or purely random. Here, we outline the use of coherent noise mitigation techniques as a characterization tool in trapped-ion testbeds. We perform model-fitting of the noisy data to determine the noise source based on realistic physics focused noise models and demonstrate that systematic noise amplification coupled with error mitigation schemes provides useful data for noise model deduction. Further, in order to connect lower level noise model details with application specific performance of near term algorithms, we experimentally construct the loss landscape of a variational algorithm under various injected noise sources coupled with error mitigation techniques. This type of connection enables application-aware hardware codesign, in which the most important noise sources in specific applications, like quantum chemistry, become foci of improvement in subsequent hardware generations.

Correcting Coherent Errors by Random Operation on Actual Quantum Hardware

“…For a single qubit N p = 12, these parameters have a simple intuitive interpretation in terms of rotations, deformations, and displacements of the Bloch sphere. Furthermore, coherent errors [9][10][11][12][13][14][15][16][17][18], that is, unitary errors that slowly vary relative to the gate time, can arise for several reasons, including miscalibration or drifts away from the control system calibration used to drive the qubit operations, crosstalk with neighboring qubits, external fields, and residual qubit-qubit interactions. Such errors cannot be removed with standard error-correcting codes [1] developed for stochastic (incoherent), uncorrelated, memoryless errors.…”