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equires to converge. Since the algorithm has much less built-in “smart” decision
making, it needs to draw its information from more data. But due to its
pipelineability and thus higher duty cycle, it does not run for much longer than
the Nelder-Mead Simplex algorithm before it converges.
11.4 Experimental Results
Even though the main result of the experiment consists of only the obtained
S-value together with its standard deviation, this number needs to be supplemented
with several datasets that test the experiment for flaws. The most useful
of this additional information are the parameters of the sequence found by the optimization,
since angles that match the theoretically expected values are a strong
indication that the implementation can be trusted. To claim a reliable violation,
the dataset should further address all known mechanism for the introduction of
artificial correlations during the time of measurement, e.g. microwave and measurement
crosstalk. Additional checks that show the variation of S as a function
of certain parameters can be of assistance in debugging the experiment, but are
of lesser importance for proving its correctness due to the robustness of the inequality.
Finally, to explain the obtained S-value, the performance parameters of
the involved qubits (and resonator), like T 1 and T 2 , can be used in a simulation
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