Dresden 2020 – scientific programme
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AKPIK: Arbeitskreis Physik, moderne Informationstechnologie und Künstliche Intelligenz
AKPIK 2: AKPIK Posters
AKPIK 2.3: Poster
Monday, March 16, 2020, 18:45–19:30, P2/1OG
Tensor network completion for gate set tomography — •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 noise under realistic assumptions are crucial for the development of near term quantum simulators.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 provide an MPS completion algorithm that 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. We further discuss GST as a homogeneous polynomial optimization problem, where recovery guarantees are available at the cost of higher computational complexity. Our approach is a promising first step towards more scalable GST schemes amenable to theoretical guarantees.