SESSION 3: Quantum characterization and benchmarking

Chair: (Robin Blume-Kohout (Sandia))
1:30pm - 2:15pmSteven Flammia, University of Sydney (invited)
Efficient learning of quantum noise
Abstract. Noise is the central obstacle to building large-scale quantum computers. Quantum systems with sufficiently uncorrelated and weak noise could be used to solve computational problems that are intractable with current digital computers. There has been substantial progress towards engineering such systems. However, continued progress depends on the ability to characterize quantum noise reliably and efficiently with high precision. Here we introduce a protocol that completely and efficiently characterizes the error rates of quantum noise and we experimentally implement it on a 14-qubit superconducting quantum architecture. The method returns an estimate of the effective noise with relative precision and detects all correlated errors. We show how to construct a quantum noise correlation matrix allowing the easy visualization of all pairwise correlated errors, enabling the discovery of long-range two-qubit correlations in the 14 qubit device that had not previously been detected. These properties of the protocol make it exceptionally well suited for high-precision noise metrology in quantum information processors. Our results are the first implementation of a provably rigorous, full diagnostic protocol capable of being run on state of the art devices and beyond. These results pave the way for noise metrology in next-generation quantum devices, calibration in the presence of crosstalk, bespoke quantum error-correcting codes, and customized fault-tolerance protocols that can greatly reduce the overhead in a quantum computation.
2:15pm - 2:45pmSeth Merkel, IBM
Benchmarking near-term quantum computers
Abstract. As the field marches towards quantum advantage with near-term quantum processors, it becomes imperative to characterize, verify, and validate performance. An outstanding scientific challenge in the community is a scalable set of metrics or experiments which can shed light on the usability of a device for near-term algorithms. We propose a device-independent metric called the quantum volume and use it to characterize recent systems built at IBM. Moreover, it becomes critical to explore techniques to extend the computational reach of noisy systems, be it through understanding underlying physics, or more efficient circuit compilation.
2:45pm - 3:15pmJoseph Emerson, University of Waterloo, Quantum Benchmark Inc.
Full reconstruction of all correlated errors in large-scale quantum computers
Abstract. In this talk I will describe how the cycle benchmarking protocol enables teams to identify all errors and error correlations for any gate-combination of interest. I will provide experimental data from multi-qubit superconducting qubit and ion trap quantum computers, revealing that: (1) in leading platforms, cross-talk and other error correlations can be much more severe than expected, even many order-of-magnitude larger than expected based on independent error models; these cross-talk errors can induce errors on other qubits (e.g., idling qubits) that are an order of magnitude larger than the errors on the qubits in the domain of the gate operation; and thus (3) elementary gate error assessments such as standard and interleaved randomized benchmarking (RB) and gate-set tomography (GST) can give a very misleading picture of the actual "in vivo" errors limiting the performance of a large-scale circuit. I will then discuss how the aggregate error rates measured under cycle benchmarking can be applied to provide a bound on the accuracy of families of circuits implemented via randomized compiling. This will be an important tool for benchmarking algorithms and the `quantum processing power" of hardware performance in what I call the `quantum discovery regime', viz., the regime of large-scale quantum computations that lay beyond the horizon of classical digital computation, where cross-entropy benchmarking and quantum volume can no longer be measured.

SQuInT Chief Organizer
Akimasa Miyake, Associate Professor

SQuInT Co-Organizer
Brian Smith, Associate Professor UO

SQuInT Program Committee
Postdoctoral Fellows:
Markus Allgaier (UO OMQ)
Sayonee Ray (UNM CQuIC)
Pablo Poggi (UNM CQuIC)
Valerian Thiel (UO OMQ)

SQuInT Event Co-Organizers (Oregon)
Jorjie Arden
Holly Lynn

SQuInT Event Administrator (Oregon)
Brandy Todd

SQuInT Administrator (CQuIC)
Gloria Cordova
505 277-1850

SQuInT Founder
Ivan Deutsch, Regents' Professor, CQuIC Director

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