Bulletin of the American Physical Society
APS March Meeting 2018
Monday–Friday, March 5–9, 2018; Los Angeles, California
Session C39: Scaling up Quantum Computers
2:30 PM–5:30 PM,
Monday, March 5, 2018
LACC Room: 501B
Sponsoring Unit: DQI
Chair: Peter Groszkowski, Northwestern University
Abstract: C39.00007 : Machine Learning of Noise in Single-Qubit Hardware*
4:30 PM–4:42 PM
(Sandia Natl Laboratories)
As quantum information processors (QIPs) grow from 2, to 5, to 16 or more qubits, characterizing their behavior rapidly becomes challenging. Techniques commonly used today, such as tomography and randomized benchmarking, are unlikely to scale easily to many qubits while providing useful debugging information. QIP development will require fast, scalable, and accurate techniques that extract useful information about noise affecting QIPs and the errors they are likely to suffer in use. Machine learning tools are a promising alternative to the brute force and/or ad-hoc statistical methods that underlie most existing techniques. Here, we demonstrate a machine learning classifier that distinguishes whether the noise on a single-qubit QIP is stochastic or coherent. The classifier uses data from certain structured circuits, specifically those used for gate set tomography, but does not rely on any of the standard statistical tools for analyzing such data, and can in principle be applied to arbitrary data that contains information about the property of interest.
*Sandia National Laboratories is operated by National Technology and Engineering Solutions of Sandia, a wholly owned subsidiary of Honeywell International for the U.S. Department of Energy’s NNSA under contract DE-NA0003525.
The American Physical Society (APS) is a non-profit membership organization working to advance the knowledge of physics.
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