Abstract
As a wide variety of quantum computing platforms become available, methods for assessing and comparing the performance of these devices are of increasing interest and importance. Inspired by the success of single-qubit error rate computations for tracking the progress of gate-based quantum computers, this work proposes a quantum annealing single-qubit assessment (QASA) protocol for quantifying the performance of individual qubits in quantum annealing computers. The proposed protocol scales to large quantum annealers with thousands of qubits and provides unique insights into the distribution of qubit properties within a particular hardware device. The efficacy of the QASA protocol is demonstrated by analyzing the properties of a D-Wave 2000Q system, revealing unanticipated correlations in the qubit performance of that device. A study repeating the QASA protocol at different annealing times highlights how the method can be utilized to understand the impact of annealing parameters on qubit performance. Overall, the proposed QASA protocol provides a useful tool for assessing the performance of current and emerging quantum annealing devices.
Highlights
I N the current era of Noisy Intermediate-Scale Quantum (NISQ) [1] devices, measuring and tracking changes in the fidelity of quantum hardware platforms is essential to understanding the limitations of these devices and quantifying progress as these platforms continue to improve
The QASA protocol has further demonstrated its efficacy in this work by revealing, for the first time, an asymmetry in the performance of the qubits from the vertical and horizontal sections of the hardware graph considered
This observation provides a clear point for improving the fidelity and consistency of this particular quantum annealing (QA) hardware platform
Summary
I N the current era of Noisy Intermediate-Scale Quantum (NISQ) [1] devices, measuring and tracking changes in the fidelity of quantum hardware platforms is essential to understanding the limitations of these devices and quantifying progress as these platforms continue to improve. The fundamental challenge in conducting characterization, verification, and validation of quantum annealing devices (QAVV) is that available hardware platforms only allow measuring the state of the system in a fixed basis (the so-called computational z-basis) and at the completion of a specified annealing protocol. QAVV efforts began in earnest around 2010 with a number of quantum hardware validation efforts that were successful in demonstrating quantum state evolution in small systems with 8 to 20 qubits [13]–[16].1 After these initial efforts, QAVV has focused almost exclusively on systemlevel benchmarks that consider transverse field Ising models with 100s to 1000s of qubits [17]. This work begins by introducing the foundations of quantum annealing for a single qubit in Section II and derives an effective single-qubit model that can be reconstructed from the observations of a particular hardware device. Despite the simplicity of this model, the imperfections of real-world QA platforms make it a useful tool for assessing the performance of individual qubits in practice
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