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FM: Fall Meeting
FM 36: Quantum Computation: Benchmarking and Certification
FM 36.6: Talk
Dienstag, 24. September 2019, 15:30–15:45, 2006
Gate set tomography via tensor completion — •Raphael Brieger1, Ingo Roth2, and Martin Kliesch1 — 1Institute for Theoretical Physics, Heinrich Heine University Düsseldorf, Germany — 2Dahlem Center for Complex Quantum Systems, Freie Universität Berlin, Germany
Flexible characterization techniques that quantify and identify unwanted noise are crucial in the development of accurate quantum gates. Such techniques must work under realistic assumptions on the state-preparations and measurements available in NISQ devices. Gate set tomography (GST) has been proposed as a technique that simultaneously extracts tomographic information on an entire set of quantum gates, the state preparation and the measurements under minimal assumptions. We argue that the problem of reconstructing the gate set can naturally be cast as the problem of completing a translation-invariant matrix product state (MPS) from the knowledge of some of its entries. Such structured completion problems can be studied using the mathematical framework of compressed sensing. Extending recent results from the compressed sensing literature, we develop a new approach to the GST data processing task. We show numerically that an MPS completion algorithm can be used for the reconstruction of gate sets. Potential advantages of this approach are the ability to include physicality and low-rank constraints as well as prior knowledge on the gate implementations. Our approach is a promising first step towards more scalable GST schemes amenable to theoretical guarantees building on rigorous results available for MPS completion algorithms.