Abstract:
Given access to a quantum computer, the first thing one typically would like to find out is how well it works. Ideally, it is desirable to have a full characterization of its components (e.g., its quantum gates) and how well they work together (e.g., crosstalk estimates). Moreover, for a user, it is desirable to obtain such information on a logical level, i.e., in a platform-independent way. These are the main tasks addressed in the field of quantum system characterization.
This talk will start with a general motivation for the field. Then, as an important example, quantum gate set tomography will be discussed. It allows obtaining a tomographic description of an entire small quantum computer or a subpart of a larger one, as given by a set of quantum gates, initial state and readout. Finally, some recent progress will be presented that has been achieved by combining ideas from different areas of applied mathematics and machine learning.
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Zoom data, for the entire semester:
https://us02web.zoom.us/j/81663533633?pwd=Z0lCQ3JyRURvRktVOThhWGRsL3lwZz09
Meeting ID: 816 6353 3633
Passcode: 003850
SFB925/ ZOQ