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ally determine an optimal value for each parameter. The easiest way to implement
this approach is by varying one parameter at a time while holding all other parameters
fixed to find a local optimum along the resulting line through parameter
space. This process can be iteratively repeated for all free parameters.
The main benefit of this method of optimization is that it provides a rough
intuitive understanding of the behavior of S which can be used to expose flaws
in the experimental setup or potential loopholes. This method of optimization,
if implemented correctly, is also fairly immune to wasting time in parts of the
parameter space that are known to have no hope of yielding a good outcome.
There also are three shortcomings to this method:
• For one, this method becomes very hard to implement if different parameters
influence the value of S in a correlated way. For example, a change in the
bias pulses used to sweep the qubits on or off resonance will cause a change
in the Z-rotation associated with the pulse, which will in turn affect the
optimal value for the phase of the Bell rotation pulses.
• The duty cycle with which this method will be able to query the oracle is
fairly low as each completed run is followed by a period of analysis, parameter
adjustment, and preparation for the next run. Not only does this reduce
the rate at which information is learned about S, but the irregular breaks in
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