Quantum computers can now run interesting programs, but each processor's capability—the set of programs that it can run successfully—is limited by hardware errors. These errors can be complicated, making it difficult to accurately predict a processor's capability. Benchmarks can be used to measure capability directly, but current benchmarks have limited flexibility and scale poorly to many-qubit processors. In this talk, I will show how to construct scalable, efficiently verifiable benchmarks based on any program by using a technique that we call circuit mirroring. With it, we constructed two flexible, scalable benchmarks based on randomized and periodically ordered programs. I will present the results of experiments in which we used these benchmarks to map out the capabilities of twelve publicly available processors, and to measure the impact of program structure on each one. We find that standard error metrics are poor predictors of whether a program will run successfully on today's hardware, and that current processors vary widely in their sensitivity to program structure. Finally, I will show how circuit mirroring can be used to efficiently estimate the execution fidelity of n-qubit circuit layers and entire quantum circuits — and how it therefore enables efficient verification of algorithms run on any number of qubits.
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Meeting ID: 933 0458 4361
INQNET (INtelligent Quantum NEtworks & Technologies, inqnet.caltech.edu) is a research program that aims to bring together academia, national laboratories, and industry to advance quantum science and technology and address relevant fundamental questions in physics.