qATG: Automatic Test Generation for Quantum Circuits
Chen-Hung Wu, Cheng-Yun Hsieh, Jiun‐Yun Li, James Chien-Mo Li · 2020
Researchers now use randomized benchmarking or quantum volume to test quantum circuits (QC) in the laboratory. However, these tests are long and their fault coverage is unclear. In this paper, we propose behavior fault models based on the function of quantum gates. These fault models are scalable because the number of faults is polynomial, not exponential, to the size of QC. We propose a novel test generation that uses gradient descent to generate test configuration with short length. We revise the chi-square statistical method to decide the number of test repetitions under the specified test escape and overkill. Experimental results on IBM Q systems show that our generated test configurations are effective, and our test lengths are 1,000X shorter than traditional test methods.