Analyzing the Temporal Behavior of Noisy Intermediate-Scale Quantum Nodes and Algorithm Fidelity

In the past decade, quantum computing has undergone rapid evolution, capturing the increasing interest of the scientific community, industry, and governments. This enthusiasm has resulted in ambitious growth plans which stimulate the development of more efficient quantum computing devices and programming environments. The easy accessibility of quantum platforms in the cloud has attracted individuals to explore quantum computing, prompting a comprehensive analysis and assessment of quantum device's behavior. The extensive benchmarking presented in this study involved all free available quantum computing devices within the IBM Quantum Platform. These devices are employed to execute tens of thousands of quantum program executions, with the objective of evaluating quantum computer behavior and performance over time and under different optimization options. Special emphasis has been placed on analyzing the transpile operation and the depth of generated quantum circuits. The machine analysis tests are conducted using Quantum Computing Run Assistant (QCRA), a versatile software tool specifically designed to streamline the effortless distribution of quantum programs across a range of quantum computing platforms. This software not only streamlines the optimization of benchmarking processes but also simplifies the assessment of different configurations and result quality through the collection of advanced job metadata. This study provides an extensive benchmark of Noisy Intermediate-Scale Quantum (NISQ) devices, assessing behavior and performance with thousands of runs. Emphasizing transpile operations and circuit depth, it explores the correlation between final result fidelity and quantum circuit depth, comparing results over time for specific quantum machines. Quantum Computing Run Assistant (QCRA) optimizes benchmark processes across various configurations. image