Testing the robustness of robust phase estimation

Meier, Adam; Burkhardt, Karl A.; McMahon, Brian J.; Herold, Creston

doi:10.1103/physreva.100.052106

Cited by 9 publications

(4 citation statements)

References 18 publications

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“…A user who needs to recalibrate an existing qubit that may have drifted out of its specification probably does not want to run full GST-it is resource-intensive, and measures a lot of quantities that are already known. To characterize just a single gate rotation angle or phase, the user can use the robust phase estimation (RPE) [9] protocol as implemented in pyGSTi [58,90]. RPE measures the the phase of a single-qubit gate efficiently and accurately, and does so while remaining robust against a wide variety of SPAM and decoherence errors.…”

Section: Recalibrating a Gate Efficiently With Rpementioning

confidence: 99%

Probing quantum processor performance with pyGSTi

Nielsen

Rudinger

Proctor

et al. 2020

Quantum Sci. Technol.

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PyGSTi is a Python software package for assessing and characterizing the performance of quantum computing processors. It can be used as a standalone application, or as a library, to perform a wide variety of quantum characterization, verification, and validation (QCVV) protocols on as-built quantum processors. We outline pyGSTi’s structure, and what it can do, using multiple examples. We cover its main characterization protocols with end-to-end implementations. These include gate set tomography, randomized benchmarking on one or many qubits, and several specialized techniques. We also discuss and demonstrate how power users can customize pyGSTi and leverage its components to create specialized QCVV protocols and solve user-specific problems.

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Section: Recalibrating a Gate Efficiently With Rpementioning

confidence: 99%

Probing quantum processor performance with pyGSTi

Nielsen

Rudinger

Proctor

et al. 2020

Quantum Sci. Technol.

View full text Add to dashboard Cite

show abstract

“…A user who needs to recalibrate an existing qubit that may have drifted out of spec probably does not want to run full GST -it's resource-intensive, and measures a lot of quantities that are already known. To characterize just a single gate rotation angle or phase, the user can use the robust phase estimation (RPE) [9] protocol as implemented in pyGSTi [27,45]. RPE measures the the phase of a single-qubit gate efficiently and accurately, and does so while remaining robust against a wide variety of SPAM and decoherence errors.…”

Section: Recalibrating a Gate Efficiently With Rpementioning

confidence: 99%

Probing quantum processor performance with pyGSTi

Nielsen,

Rudinger,

Proctor

et al. 2020

Preprint

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PyGSTi is a Python software package for assessing and characterizing the performance of quantum computing processors. It can be used as a standalone application, or as a library, to perform a wide variety of quantum characterization, verification, and validation (QCVV) protocols on as-built quantum processors. We outline pyGSTi's structure, and what it can do, using multiple examples. We cover its main characterization protocols with end-to-end implementations. These include gate set tomography, randomized benchmarking on one or many qubits, and several specialized techniques. We also discuss and demonstrate how power users can customize pyGSTi and leverage its components to create specialized QCVV protocols and solve user-specific problems. ContentsI. What is pyGSTi? 1 II. Background

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“…Robust phase estimation (RPE) is one such protocol that was originally conceived as a method for characterizing single-qubit gates [14]. Recently, RPE implementations have been experimentally demonstrated on trapped-ion qubits [15,16] and used to simulate the ground state and low-lying electronic excitations of a hydrogen molecule on a superconducting cloud-based quantum computer [17]. RPE has Heisenberg scaling, so it is optimally fast up to constant factors.…”

Section: Introductionmentioning

confidence: 99%

Consistency testing for robust phase estimation

Russo,

Kirby,

Rudinger

et al. 2020

Preprint

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We present an extension to the robust phase estimation protocol, which can identify incorrect results that would otherwise lie outside the expected statistical range. Robust phase estimation is increasingly a method of choice for applications such as estimating the effective process parameters of noisy hardware, but its robustness is dependent on the noise satisfying certain threshold assumptions. We provide consistency checks that can indicate when those thresholds have been violated, which can be difficult or impossible to test directly. We test these consistency checks for several common noise models, and identify two possible checks with high accuracy in locating the point in a robust phase estimation run at which further estimates should not be trusted. One of these checks may be chosen based on resource availability, or they can be used together in order to provide additional verification.

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Testing the robustness of robust phase estimation

Cited by 9 publications

References 18 publications

Probing quantum processor performance with pyGSTi

Probing quantum processor performance with pyGSTi

Probing quantum processor performance with pyGSTi

Consistency testing for robust phase estimation

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