Noise is the main obstacle to building large-scale quantum computers.
To tame the noise (interference or instability), scientists need to understand how it affects an entire quantum system.
Until now this information was only available for very small devices or subsets of devices.
Work by Dr Robin Harper and colleagues published today in Nature Physics develops algorithms that will work across large quantum devices.
They demonstrate this by diagnosing the noise in an IBM Quantum Experience device, discovering correlations in the 14-qubit machine not previously detected.
Dr Harper said: "The results are the first implementation of provably rigorous and scalable diagnostic algorithms capable of being run on current quantum devices and beyond."
Dr Harper is a postdoctoral researcher at the University of Sydney Nano Institute and part of the Australian Research Council Centre of Excellence for Engineered Quantum Systems.
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INTERVIEWS
Dr Robin Harper | robin.harper@sydney.edu.au
Professor Steven Flammia | steven.flammia@sydney.edu.au
MEDIA ENQUIRIES
Marcus Strom | marcus.strom@sydney.edu.au | +61 423 982 485
DECLARATION
This work was supported in part by the US Army Research Office, the Australian Research Council Centre of Excellence for Engineered Quantum Systems (EQUS), the Government of Ontario, and the Government of Canada through the Canada First Research Excellence Fund (CFREF) and Transformative Quantum Technologies (TQT), the Natural Sciences and Engineering Research Council (NSERC), Industry Canada.
RESEARCH ARTICLE available on request.
'Efficient learning of quantum noise', Nature Physics , DOI: 10.1038/s41567-020-0992-8
Authors: Robin Harper1, Steven Flammia1,2 and Joel Wallman3,4
1 Centre for Engineered Quantum Systems, School of Physics, University of Sydney
2 Yale Quantum Institute, Yale University, USA
3 Institute for Quantum Computing, University of Waterloo, Canada
4 Quantum Benchmark Inc, Kitchener, Ontario, Canada
Nature Physics