Toolkit for Characterizing Noisy Quantum Processors and Windows of Quantum Advantage

Suny At Stony Brook, Stony Brook NY

Investigators

Abstract

Quantum computers offer potential advantages and possibly exponential speedup over existing classical computers for certain computational tasks. Success in building large-scale functioning quantum computers will undoubtedly be a revolution in computer technology. However, many of these applications will require quantum computers with very small error rates and which use quantum error corrections for tolerating faults - a technology that is still out of reach for near-term noisy devices. Nevertheless, there are certain tasks that near-term quantum processors can perform but are still difficult for the current best classical computers. The demonstration of a quantum advantage will first require development of tools characterizing the operation of quantum gates, state preparation and measurement, as well as the corresponding errors. This project will integrate these tools to streamline their use in cloud quantum computers. Understanding the noise and errors also helps to devise mitigation strategies so as to extract as much as possible the correct computation. This project will also employ classical simulations to compare the expected outcomes with runs on quantum computers and analyze schemes for demonstrating potential quantum advantages. The goal of this project is to develop and assemble a toolkit for near-term quantum information processing that may yield quantum advantage. In particular, the PI will design and integrate tools for (1) noisy-gate characterization of tomographic tools, (2) randomized benchmarking, (3) error mitigation methods. These will be tested in actual runs on cloud quantum computers. Furthermore, (4) classical simulations will be developed, such as tensor-network methods, for noisy quantum circuits, and (5) schemes for quantum supremacy via short-depth quantum circuits will be assessed. Other new schemes will also be explored that will provide alternative playgrounds for showing the advantages of quantum devices over classical ones. Developing a toolkit that consists of technical approaches and software building will help to verify intermediate-scale noisy quantum information processing and identify windows of parameters guiding towards demonstrating quantum advantage. This project will also involve training of graduate students in research activities, presentation and writing skills, and mentoring in career planning. It will provide undergraduates and high-school students some first-hand experience in quantum information science (QIS) research. The PI will work with his colleagues to develop a quantum information science/quantum technology track in the Master's program in the Department of Physics and Astronomy. Creation of such a QIS track/program will help steadily train a quantum-smart workforce that is projected to be of high demand in the United States in the next few decades. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.