Leveraging Randomized Compiling for the QITE Algorithm

Abstract

The success of the current generation of Noisy Intermediate-Scale Quantum (NISQ) hardware shows that quantum hardware may be able to tackle complex problems even without error correction. One outstanding issue is that of coherent errors arising from the increased complexity of these devices. These errors can accumulate through a circuit, making their impact on algorithms hard to predict and mitigate. Iterative algorithms like Quantum Imaginary Time Evolution are susceptible to these errors. This article presents the combination of both noise tailoring using Randomized Compiling and error mitigation with a purification. We also show that Cycle Benchmarking gives an estimate of the reliability of the purification. We apply this method to the Quantum Imaginary Time Evolution of a Transverse Field Ising Model and report an energy estimation and a ground state infidelity both below 1\%. Our methodology is general and can be used for other algorithms and platforms. We show how combining noise tailoring and error mitigation will push forward the performance of NISQ devices.

arXiv commentData has been updated

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Cited by in corpus (7)

• Synergetic quantum error mitigation by randomized compiling and zero-noise extrapolation for the variational quantum eigensolver
• A quantum-classical co-processing protocol towards simulating nuclear reactions on contemporary quantum hardware
• Simulating nonlinear optical processes on a superconducting quantum device
• Estimating Coherent Contributions to the Error Profile Using Cycle Error Reconstruction
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• Quantum imaginary time evolution and UD-MIS problem
• Simplifying errors by symmetry and randomisation